All Stories

  1. An Integrated Hydro-Geotechnical Framework for Landslide Susceptibility Zonation and Slope Stability Assessment: Application to the Pithoragarh Region, Uttarakhand, India
  2. Discussion of “Comparison of Analytical, Multiple Polynomial Regression, and Artificial Neural Networks to Estimate Wetting Parameters for Surface and Buried Drip Irrigation across Three Different Soil Textures”
  3. From raw signals to decomposed insights: boosting models enhanced by EMD variants for multi-depth soil temperature and moisture prediction
  4. River water temperature prediction using REMD, RLMD, and SVMD coupled with deep learning models
  5. Building a reliable coagulant dosage prediction framework for water purification processes using CatBoost and explainable AI (XAI)
  6. Integrated GIS-based multi-criteria and geospatial approach for seismic hazard mapping in the arabian–eurasian convergence zone
  7. Assessment of hydrological behaviour in a tropical humid climate basin under different land use and cover scenarios using EBA4SUB model
  8. Modeling soil water distribution under drip fertigation in chrysanthemum across soil types using HYDRUS-2D
  9. Metaheuristic-optimized ANN for flood susceptibility mapping: a case study in the Khiavchai Watershed, Iran
  10. Machine learning-based estimation of specific yield in single-well unconfined aquifers
  11. Cluster-based XGBoost framework for short-term rainfall–runoff prediction under uncertainty in the Sieber watershed, Germany
  12. Metaheuristic-optimized neuro-fuzzy models for meteorological drought prediction
  13. Accurate and interpretable prediction of chemical oxygen demand using explainable boosting algorithms with SHAP analysis
  14. Discussion of “Comparison of the Self-Organizing Map and the Adaptive Neuro-Fuzzy Inference System in Predicting the Paddy Crop Water Stress Index”
  15. Daily river water temperature prediction using regularized greedy forest enhanced TVF-EMD and empirical Fourier decomposition
  16. Interpretable Temperature‐Based Deep Learning for Evapotranspiration: SHAP ‐Based Feature Analysis in CNN ‐ GPU
  17. Ranking and comparison of temperature-, mass transfer- and radiation based daily reference evapotranspiration models by using compromise programming index (CPI) and global performance indicator (GPI)
  18. Sustaining Grape Yield and Soil Health Under Saline–Sodic Irrigation Through Amendments and Canal Water Application
  19. Spatial-temporal variation of precipitation in Niedersachsen, Germany, using statistical and graphical trend methods considering climatic drivers
  20. Novel Hybrid Approach for River Inflow Modeling: Case Study of the Indus River Basin, Pakistan
  21. Improving the prediction of global solar radiation using interpretable boosting algorithms coupled SHAP and LIME analysis: a comparative study
  22. Forecasting maximal and minimal air temperatures using explainable machine learning: Shapley additive explanation versus local interpretable model-agnostic explanations
  23. Predicting water quality variables using gradient boosting machine: global versus local explainability using SHapley Additive Explanations (SHAP)
  24. Harnessing Deep Learning and Snow Cover Data for Enhanced Runoff Prediction in Snow-Dominated Watersheds
  25. Enhancing solar radiation prediction accuracy: A hybrid machine learning approach integrating response surface method and support vector regression
  26. Enhancing the Prediction of Influent Total Nitrogen in Wastewater Treatment Plant Using Adaptive Neuro-Fuzzy Inference System–Gradient-Based Optimization Algorithm
  27. Correction: The influence of collar parameters on local scour mechanism around the circular pier at the bend
  28. A new method for monthly streamflow prediction using multi-source data: range-dependent multivariate adaptive regression splines–genetic algorithm
  29. A Comparative Study of Machine Learning Models for Daily and Weekly Rainfall Forecasting
  30. The influence of collar parameters on local scour mechanism around the circular pier at the bend
  31. Comparison Analysis of Seepage Through Homogenous Embankment Dams Using Physical, Mathematical and Numerical Models
  32. Sensitivity of daily reference evapotranspiration to weather variables in tropical savanna: a modelling framework based on neural network
  33. Utilizing Hybrid Machine Learning Techniques and Gridded Precipitation Data for Advanced Discharge Simulation in Under-Monitored River Basins
  34. An Investigation on Hydraulic Aspects of Rectangular Labyrinth Pool and Weir Fishway Using FLOW-3D
  35. Quantifying Landscape Pattern–Hydrological Process Linkage in Northwest Iran
  36. Estimation of Reference Evapotranspiration in Semi-Arid Region with Limited Climatic Inputs Using Metaheuristic Regression Methods
  37. Comparison of improved relevance vector machines for streamflow predictions
  38. Evaluating the effects of reservoir outflow and land-use change on the Zarrineh River basin
  39. A New Insight for Daily Solar Radiation Prediction by Meteorological Data Using an Advanced Artificial Intelligence Algorithm: Deep Extreme Learning Machine Integrated with Variational Mode Decomposition Technique
  40. Modeling Significant Wave Heights for Multiple Time Horizons Using Metaheuristic Regression Methods
  41. Investigating Landfill Leachate and Groundwater Quality Prediction Using a Robust Integrated Artificial Intelligence Model: Grey Wolf Metaheuristic Optimization Algorithm and Extreme Learning Machine
  42. Improving Significant Wave Height Prediction Using a Neuro-Fuzzy Approach and Marine Predators Algorithm
  43. Predicting and Optimizing the Influenced Parameters for Culvert Outlet Scouring Utilizing Coupled FLOW 3D-Surrogate Modeling
  44. Spatio-Temporal Analysis of Carbon Sequestration in Different Ecosystems of Iran and Its Relationship with Agricultural Droughts
  45. Application of novel binary optimized machine learning models for monthly streamflow prediction
  46. Prediction of Sediment Yields Using a Data-Driven Radial M5 Tree Model
  47. Discussion of “Improving Prediction Accuracy of Hydrologic Time Series by Least-Squares Support Vector Machine Using Decomposition Reconstruction and Swarm Intelligence”
  48. Predicting Discharge Coefficient of Triangular Side Orifice Using LSSVM Optimized by Gravity Search Algorithm
  49. Water Quality Prediction of the Yamuna River in India Using Hybrid Neuro-Fuzzy Models
  50. Groundwater level modeling using Augmented Artificial Ecosystem Optimization
  51. Optimization design of quality monitoring network of Urmia plain using genetic algorithm and vulnerability map
  52. Modeling Potential Evapotranspiration by Improved Machine Learning Methods Using Limited Climatic Data
  53. Water Temperature Prediction Using Improved Deep Learning Methods through Reptile Search Algorithm and Weighted Mean of Vectors Optimizer
  54. Random Forest Ensemble-Based Predictions of On-Road Vehicular Emissions and Fuel Consumption in Developing Urban Areas
  55. Predicting nitrate concentration in river using advanced artificial intelligence techniques
  56. Advanced Hybrid Metaheuristic Machine Learning Models Application for Reference Crop Evapotranspiration Prediction
  57. Modelling groundwater level fluctuations by ELM merged advanced metaheuristic algorithms using hydroclimatic data
  58. Prediction of the Discharge Coefficient in Compound Broad-Crested-Weir Gate by Supervised Data Mining Techniques
  59. The viability of extended marine predators algorithm-based artificial neural networks for streamflow prediction
  60. Monthly streamflow prediction using hybrid extreme learning machine optimized by Bat algorithm: a case study of Cheliff watershed, Algeria
  61. Approximation of the Discharge Coefficient of Radial Gates Using Metaheuristic Regression Approaches
  62. Monthly Streamflow Prediction by Metaheuristic Regression Approaches Considering Satellite Precipitation Data
  63. Hybridized Adaptive Neuro-Fuzzy Inference System with Metaheuristic Algorithms for Modeling Monthly Pan Evaporation
  64. Application of improved version of multi verse optimizer algorithm for modeling solar radiation
  65. Covariance Matrix Adaptation Evolution Strategy for Improving Machine Learning Approaches in Streamflow Prediction
  66. Improving accuracy of neuro fuzzy and support vector regression for drought modelling using grey wolf optimization
  67. The Effect of Dust Storm on Sea Surface Temperature in the Western Basin of Persian Gulf
  68. Drought forecasting using the Prophet model in a semi-arid climate region of western India
  69. Least square support vector machine-based variational mode decomposition: a new hybrid model for daily river water temperature modeling
  70. Predicting Daily Streamflow in a Cold Climate Using a Novel Data Mining Technique: Radial M5 Model Tree
  71. Spatio-Temporal Analysis of Rainfall Dynamics of 120 Years (1901–2020) Using Innovative Trend Methodology: A Case Study of Haryana, India
  72. Comparative evaluation of deep learning and machine learning in modelling pan evaporation using limited inputs
  73. Modeling Multistep Ahead Dissolved Oxygen Concentration Using Improved Support Vector Machines by a Hybrid Metaheuristic Algorithm
  74. Water level prediction using various machine learning algorithms: a case study of Durian Tunggal river, Malaysia
  75. The potential of a novel support vector machine trained with modified mayfly optimization algorithm for streamflow prediction
  76. Bidirectional long short-term memory-based empirical wavelet transform: A new hybrid artificial intelligence model for robust prediction of soil moisture content
  77. Random vector functional link network based on variational mode decomposition for predicting river water turbidity
  78. Improving Drought Modeling Using Hybrid Random Vector Functional Link Methods
  79. Modeling Multi-Objective Pareto-Optimal Reservoir Operation Policies using State-of-the-art Modeling Techniques
  80. Development of new machine learning model for streamflow prediction: case studies in Pakistan
  81. Predicting Water Availability in Water Bodies under the Influence of Precipitation and Water Management Actions Using VAR/VECM/LSTM
  82. Towards a Comprehensive Assessment of Statistical versus Soft Computing Models in Hydrology: Application to Monthly Pan Evaporation Prediction
  83. Machine Learning with Metaheuristic Algorithms for Sustainable Water Resources Management
  84. Advanced machine learning models development for suspended sediment prediction: comparative analysis study
  85. Novel Ensemble Forecasting of Streamflow Using Locally Weighted Learning Algorithm
  86. Suspended Sediment Modeling Using a Heuristic Regression Method Hybridized with Kmeans Clustering
  87. Approaches for Optimizing the Performance of Adaptive Neuro-Fuzzy Inference System and Least-Squares Support Vector Machine in Precipitation Modeling
  88. Groundwater-Potential Mapping Using a Self-Learning Bayesian Network Model: A Comparison among Metaheuristic Algorithms
  89. Comparison of different methodologies for rainfall–runoff modeling: machine learning vs conceptual approach
  90. Artificial intelligence models for suspended river sediment prediction: state-of-the art, modeling framework appraisal, and proposed future research directions
  91. Modeling the fluctuations of groundwater level by employing ensemble deep learning techniques
  92. Prediction of Potential Evapotranspiration Using Temperature-Based Heuristic Approaches
  93. A Theoretical Approach for Forecasting Different Types of Drought Simultaneously, Using Entropy Theory and Machine-Learning Methods
  94. Bayesian Model Averaging: A Unique Model Enhancing Forecasting Accuracy for Daily Streamflow Based on Different Antecedent Time Series
  95. Application of Artificial Neural Networks, Support Vector Machine and Multiple Model-ANN to Sediment Yield Prediction
  96. Using the MODIS Sensor for Snow Cover Modeling and the Assessment of Drought Effects on Snow Cover in a Mountainous Area
  97. Rainfall-runoff modelling using improved machine learning methods: Harris hawks optimizer vs. particle swarm optimization
  98. Energy Loss in Skimming Flow over Cascade Spillways: Comparison of Artificial Intelligence-Based and Regression Methods
  99. Development of an indirect method for modelling the water footprint of electricity using wavelet transform coupled with the random forest model
  100. Modeling monthly streamflow in mountainous basin by MARS, GMDH-NN and DENFIS using hydroclimatic data
  101. Monthly suspended sediment load prediction using artificial intelligence: testing of a new random subspace method
  102. A minimalistic approach for evapotranspiration estimation using the Prophet model
  103. Comments on “Predicting permeability changes with injecting CO2 in coal seams during CO2 geological sequestration: A comparative study among six SVM-based hybrid models” Science of the Total Environment, 705, 135941 (2020)
  104. Pan Evaporation Estimation in Uttarakhand and Uttar Pradesh States, India: Validity of an Integrative Data Intelligence Model
  105. Improved Water Quality Prediction with Hybrid Wavelet-Genetic Programming Model and Shannon Entropy
  106. Reference Evapotranspiration Modeling Using New Heuristic Methods
  107. Human–Environment Natural Disasters Interconnection in China: A Review
  108. Estimating Soil Available Phosphorus Content through Coupled Wavelet–Data-Driven Models
  109. Combined Use of Graphical and Statistical Approaches for Analyzing Historical Precipitation Changes in the Black Sea Region of Turkey
  110. Improving artificial intelligence models accuracy for monthly streamflow forecasting using grey Wolf optimization (GWO) algorithm
  111. Comparison of three different bio-inspired algorithms to improve ability of neuro fuzzy approach in prediction of agricultural drought, based on three different indexes
  112. Investigation into the Effects of Climate Change on Reference Evapotranspiration Using the HadCM3 and LARS-WG
  113. On the applicability of maximum overlap discrete wavelet transform integrated with MARS and M5 model tree for monthly pan evaporation prediction
  114. Least square support vector machine and multivariate adaptive regression splines for streamflow prediction in mountainous basin using hydro-meteorological data as inputs
  115. Prediction of Suspended Sediment Load Using Data-Driven Models
  116. Daily streamflow prediction using optimally pruned extreme learning machine
  117. Comprehensive assessment of 12 soft computing approaches for modeling reference evapotranspiration in humid locations
  118. Drought forecasting using novel heuristic methods in a semi-arid environment
  119. Novel approaches for air temperature prediction: Comparison of four hybrid evolutionary fuzzy models
  120. The Implementation of a Hybrid Model for Hilly Sub-Watershed Prioritization Using Morphometric Variables: Case Study in India
  121. Long-term modeling of wind speeds using six different heuristic artificial intelligence approaches
  122. Modelling reference evapotranspiration using a new wavelet conjunction heuristic method: Wavelet extreme learning machine vs wavelet neural networks
  123. A new wavelet conjunction approach for estimation of relative humidity: wavelet principal component analysis combined with ANN
  124. Quantifying Hourly Suspended Sediment Load Using Data Mining Models: Case Study of a Glacierized Andean Catchment in Chile
  125. Simulation of suspended sediment based on gamma test, heuristic, and regression-based techniques
  126. Stable alluvial channel design using evolutionary neural networks
  127. Stream Flow Forecasting of Poorly Gauged Mountainous Watershed by Least Square Support Vector Machine, Fuzzy Genetic Algorithm and M5 Model Tree Using Climatic Data from Nearby Station
  128. Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
  129. Evaluation of the support vector machine, random forest and geo-statistical methodologies for predicting long-term air temperature
  130. Comparison of four heuristic regression techniques in solar radiation modeling: Kriging method vs RSM, MARS and M5 model tree
  131. Modified Response-Surface Method: New Approach for Modeling Pan Evaporation
  132. Pre-processing data to predict groundwater levels using the fuzzy standardized evapotranspiration and precipitation index (SEPI)
  133. M5 model tree and Monte Carlo simulation for efficient structural reliability analysis
  134. Pan evaporation modeling using four different heuristic approaches
  135. Impurity effect on clear water evaporation: toward modelling wastewater evaporation using ANN, ANFIS-SC and GEP techniques
  136. Daily Mean Streamflow Prediction in Perennial and Non-Perennial Rivers Using Four Data Driven Techniques
  137. Prediction of Ultimate Strain and Strength of FRP-Confined Concrete Cylinders Using Soft Computing Methods
  138. Discussion of “Prediction of Discharge Capacity over Two-Cycle Labyrinth Side Weir Using ANFIS” by M. Cihan Aydin and Korhan Kayisli
  139. Prediction of diffuse photosynthetically active radiation using different soft computing techniques
  140. Modeling soil bulk density through a complete data scanning procedure: Heuristic alternatives
  141. Wavelet-linear genetic programming: A new approach for modeling monthly streamflow
  142. Extreme learning machines: a new approach for modeling dissolved oxygen (DO) concentration with and without water quality variables as predictors
  143. A comparative assessment of GIS-based data mining models and a novel ensemble model in groundwater well potential mapping
  144. A new approach for simulating and forecasting the rainfall-runoff process within the next two months
  145. Modeling of air pollutants using least square support vector regression, multivariate adaptive regression spline, and M5 model tree models
  146. Fast convergence optimization model for single and multi-purposes reservoirs using hybrid algorithm
  147. Modeling soil cation exchange capacity using soil parameters: Assessing the heuristic models
  148. Spatial monitoring and zoning water quality of Sistan River in the wet and dry years using GIS and geostatistics
  149. Groundwater quality ranking for drinking purposes, using the entropy method and the spatial autocorrelation index
  150. Evaporation modelling using different machine learning techniques
  151. Impact of climate change on runoff in Lake Urmia basin, Iran
  152. Modeling groundwater fluctuations by three different evolutionary neural network techniques using hydroclimatic data
  153. Drought forecasting in eastern Australia using multivariate adaptive regression spline, least square support vector machine and M5Tree model
  154. Pan evaporation modeling using six different heuristic computing methods in different climates of China
  155. Improving Accuracy of River Flow Forecasting Using LSSVR with Gravitational Search Algorithm
  156. Erratum to: A New Approach for Modeling Sediment-Discharge Relationship: Local Weighted Linear Regression
  157. Joint modelling of annual maximum drought severity and corresponding duration
  158. Applicability of Several Soft Computing Approaches in Modeling Oxygen Transfer Efficiency at Baffled Chutes
  159. Discussion of “Estimation of Furrow Irrigation Sediment Loss Using an Artificial Neural Network” by Bradley A. King, David L. Bjorneberg, Thomas J. Trout, Luciano Mateos, Danielle F. Araujo, and Raimundo N. Costa
  160. Strength prediction of rotary brace damper using MLR and MARS
  161. Novel Predictive Model of the Debonding Strength for Masonry Members Retrofitted with FRP
  162. Modelling daily reference evapotranspiration in humid locations of South Korea using local and cross-station data management scenarios
  163. Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq
  164. Trend Analysis of Maximum Hydrologic Drought Variables Using Mann-Kendall and Şen's Innovative Trend Method
  165. A New Approach for Modeling Sediment-Discharge Relationship: Local Weighted Linear Regression
  166. Estimation of dissolved oxygen by using neural networks and neuro fuzzy computing techniques
  167. Prediction of Water-Level in the Urmia Lake Using the Extreme Learning Machine Approach
  168. A nonlinear mathematical modeling of daily pan evaporation based on conjugate gradient method
  169. Evaluating the generalizability of GEP models for estimating reference evapotranspiration in distant humid and arid locations
  170. Discussion of “Monthly Mean Streamflow Prediction Based on Bat Algorithm-Support Vector Machine” by Bing Xing, Rong Gan, Guodong Liu, Zhongfang Liu, Jing Zhang, and Yufeng Ren
  171. Solar radiation prediction using different techniques: model evaluation and comparison
  172. Evaluation of peak and residual conditions of actively confined concrete using neuro-fuzzy and neural computing techniques
  173. Enhancing Long-Term Streamflow Forecasting and Predicting using Periodicity Data Component: Application of Artificial Intelligence
  174. Reply to the comments on “Comparison of Mann–Kendall and innovative trend method for water quality parameters of the Kizilirmak River, Turkey” by Kisi, O. and Ay, M. [J. Hydrol. 513 (2014) 362–375] and “An innovative method for trend analysis of monthl...
  175. Water temperature prediction in a subtropical subalpine lake using soft computing techniques
  176. River Stage Forecasting Using Wavelet Packet Decomposition and Machine Learning Models
  177. Suspended Sediment Modeling Using Neuro-Fuzzy Embedded Fuzzy c-Means Clustering Technique
  178. A nonlinear modelling-based high-order response surface method for predicting monthly pan evaporations
  179. A new approach for modeling suspended sediment: Evolutionary fuzzy approach
  180. Modifying Hargreaves–Samani equation with meteorological variables for estimation of reference evapotranspiration in Turkey
  181. Comparison of six different soft computing methods in modeling evaporation in different climates
  182. Prediction of solar radiation in China using different adaptive neuro-fuzzy methods and M5 model tree
  183. Groundwater budget forecasting, using hybrid wavelet-ANN-GP modelling: a case study of Azarshahr Plain, East Azerbaijan, Iran
  184. Soil temperature modeling at different depths using neuro-fuzzy, neural network, and genetic programming techniques
  185. Modeling reference evapotranspiration using three different heuristic regression approaches
  186. Predicting river daily flow using wavelet-artificial neural networks based on regression analyses in comparison with artificial neural networks and support vector machine models
  187. Evaluation of data driven models for river suspended sediment concentration modeling
  188. Modeling and comparison of hourly photosynthetically active radiation in different ecosystems
  189. Multiple linear regression, multi-layer perceptron network and adaptive neuro-fuzzy inference system for forecasting precipitation based on large-scale climate signals
  190. Application of least square support vector machine and multivariate adaptive regression spline models in long term prediction of river water pollution
  191. Daily pan evaporation modeling using chi-squared automatic interaction detector, neural networks, classification and regression tree
  192. Assessment of rainfall aggregation and disaggregation using data-driven models and wavelet decomposition
  193. Predicting behavior of FRP-confined concrete using neuro fuzzy, neural network, multivariate adaptive regression splines and M5 model tree techniques
  194. Flood Hazard Mapping by Using Geographic Information System and Hydraulic Model: Mert River, Samsun, Turkey
  195. Hydrological Hazards in a Changing Environment: Early Warning, Forecasting, and Impact Assessment
  196. Modeling shear stress distribution in natural small streams by soft computing methods
  197. Damage detection in structural beam elements using hybrid neuro fuzzy systems
  198. A Wavelet and Neuro-fuzzy Conjunction Model to Forecast Air Temperature Variations at Coastal Sites
  199. Short-term and long-term streamflow prediction by using 'wavelet–gene expression' programming approach
  200. A survey of water level fluctuation predicting in Urmia Lake using support vector machine with firefly algorithm
  201. Corrigendum to “An innovative method for trend analysis of monthly pan evaporations” [J. Hydrol. 527 (2015) 1123–1129]
  202. Lake Level Forecasting Using Wavelet-SVR, Wavelet-ANFIS and Wavelet-ARMA Conjunction Models
  203. Discussion of “Comparison of Wavelet-Based ANN and Regression Models for Reservoir Inflow Forecasting” by Krishna Budu
  204. Discussion of “Evapotranspiration Modeling Using Second-Order Neural Networks” by Sirisha Adamala, N. S. Raghuwanshi, Ashok Mishra, and Mukesh K. Tiwari
  205. Applicability of a Fuzzy Genetic System for Crack Diagnosis in Timoshenko Beams
  206. Pan evaporation modeling using least square support vector machine, multivariate adaptive regression splines and M5 model tree
  207. Independent testing for assessing the calibration of the Hargreaves–Samani equation: New heuristic alternatives for Iran
  208. Discussion of “Improved Particle Swarm Optimization–Based Artificial Neural Network for Rainfall-Runoff Modeling” by Mohsen Asadnia, Lloyd H. C. Chua, X. S. Qin, and Amin Talei
  209. Streamflow Forecasting and Estimation Using Least Square Support Vector Regression and Adaptive Neuro-Fuzzy Embedded Fuzzy c-means Clustering
  210. An investigation on generalization ability of artificial neural networks and M5 model tree in modeling reference evapotranspiration
  211. Extreme Learning Machines: A new approach for prediction of reference evapotranspiration
  212. An innovative method for trend analysis of monthly pan evaporations
  213. Discussion of “Runoff Estimation by Machine Learning Methods and Application to the Euphrates Basin in Turkey” by Abdullah Gokhan Yilmaz and Nitin Muttil
  214. Long-term monthly evapotranspiration modeling by several data-driven methods without climatic data
  215. Predicting daily pan evaporation by soft computing models with limited climatic data
  216. Plunging Flow Depth Estimation in a Stratified Dam Reservoir Using Neuro-Fuzzy Technique
  217. Damage diagnosis in beam-like structures by artificial neural networks
  218. Time series analysis on marine wind-wave characteristics using chaos theory
  219. Closure to “Comparison of Different Empirical Methods for Estimating Daily Reference Evapotranspiration in Mediterranean Climate” by Ozgur Kisi
  220. Discussion of “Comparison of Different Empirical Methods for Estimating Daily Reference Evapotranspiration in Mediterranean Climate” by Ozgur Kisi
  221. Prediction of debonding strength for masonry elements retrofitted with FRP composites using neuro fuzzy and neural network approaches
  222. Prediction of long-term monthly precipitation using several soft computing methods without climatic data
  223. Importance of hybrid models for forecasting of hydrological variable
  224. Modelling solar radiation reached to the Earth using ANFIS, NN-ARX, and empirical models (Case studies: Zahedan and Bojnurd stations)
  225. RETRACTED ARTICLE: Evaluating groundwater level fluctuation by support vector regression and neuro-fuzzy methods: a comparative study
  226. Modelling long-term monthly temperatures by several data-driven methods using geographical inputs
  227. Comparison of Different Data-Driven Approaches for Modeling Lake Level Fluctuations: The Case of Manyas and Tuz Lakes (Turkey)
  228. Daily water level forecasting using wavelet decomposition and artificial intelligence techniques
  229. Prediction of Millers Ferry Dam Reservoir Level in USA Using Artificial Neural Network
  230. Forecasting Sea Water Levels at Mukho Station, South Korea Using Soft Computing Techniques
  231. Estimation of mean monthly air temperatures in Turkey
  232. Comparison of heuristic and empirical approaches for estimating reference evapotranspiration from limited inputs in Iran
  233. Determining Flow Friction Factor in Irrigation Pipes Using Data Mining and Artificial Intelligence Approaches
  234. Corrigendum to “Applications of hybrid wavelet–Artificial Intelligence models in hydrology: A review” [J. Hydrol. 514 (2014) 358–377]
  235. Modeling soil temperatures at different depths by using three different neural computing techniques
  236. Discussion of “Simple ET0 Forms of Penman’s Equation without Wind and/or Humidity Data. I: Theoretical Development” by John D. Valiantzas
  237. Investigation of Empirical Mode Decomposition in Forecasting of Hydrological Time Series
  238. Investigation of trend analysis of monthly total precipitation by an innovative method
  239. Applications of hybrid wavelet–Artificial Intelligence models in hydrology: A review
  240. Discussion of “Evaluation of MLP-ANN Training Algorithms for Modeling Soil Pore-Water Pressure Responses to Rainfall” by M. R. Mustafa, R. B. Rezaur, S. Saiedi, H. Rahardjo, and M. H. Isa
  241. Determination of Mean Velocity and Discharge in Natural Streams Using Neuro-Fuzzy and Neural Network Approaches
  242. Comparison of Two Different Adaptive Neuro-Fuzzy Inference Systems in Modelling Daily Reference Evapotranspiration
  243. Runoff Estimation by Machine Learning Methods and Application to the Euphrates Basin in Turkey
  244. Comparison of Mann–Kendall and innovative trend method for water quality parameters of the Kizilirmak River, Turkey
  245. Modelling of chemical oxygen demand by using ANNs, ANFIS and k-means clustering techniques
  246. Discussion of “Comparison of Artificial Neural Network Models for Sediment Yield Prediction at Single Gauging Station of Watershed in Eastern India” by Ajai Singh, Mohd Imtiyaz, R. K. Isaac, and D. M. Denis
  247. Modeling solar radiation of Mediterranean region in Turkey by using fuzzy genetic approach
  248. Comparison of Different Empirical Methods for Estimating Daily Reference Evapotranspiration in Mediterranean Climate
  249. Modeling of Suspended Sediment Concentration Carried in Natural Streams Using Fuzzy Genetic Approach
  250. Generalizability of Gene Expression Programming-based approaches for estimating daily reference evapotranspiration in coastal stations of Iran
  251. Local vs. external training of neuro-fuzzy and neural networks models for estimating reference evapotranspiration assessed through k-fold testing
  252. Modeling of Dissolved Oxygen in River Water Using Artificial Intelligence Techniques
  253. Performance of radial basis and LM-feed forward artificial neural networks for predicting daily watershed runoff
  254. Estimation of Monthly Mean Reference Evapotranspiration in Turkey
  255. Applicability of Mamdani and Sugeno fuzzy genetic approaches for modeling reference evapotranspiration
  256. Comparison of different methods for developing a stage-discharge curve of the Kizilirmak River
  257. Monthly pan evaporation modeling using linear genetic programming
  258. Anfis to estimate discharge capacity of rectangular side weir
  259. A genetic programming technique for lake level modeling
  260. Modeling dimensionless longitudinal dispersion coefficient in natural streams using artificial intelligence methods
  261. Estimation of daily dew point temperature using genetic programming and neural networks approaches
  262. Evolutionary neural networks for monthly pan evaporation modeling
  263. “Comparison of genetic programming with neuro-fuzzy systems for predicting short-term water table depth fluctuations” by Jalal Shiri & Ozgur Kisi [Computers and Geosciences (2011) 1692–1701]
  264. Predicting groundwater level fluctuations with meteorological effect implications—A comparative study among soft computing techniques
  265. Fuzzy Genetic Approach for Estimating Reference Evapotranspiration of Turkey: Mediterranean Region
  266. Prediction of long-term monthly air temperature using geographical inputs
  267. Neuro-fuzzy and neural network techniques for forecasting sea level in Darwin Harbor, Australia
  268. Evaluation of different data management scenarios for estimating daily reference evapotranspiration
  269. Estimating Daily Pan Evaporation Using Different Data-Driven Methods and Lag-Time Patterns
  270. Estimation of dew point temperature using neuro-fuzzy and neural network techniques
  271. Modeling rainfall-runoff process using soft computing techniques
  272. Global cross-station assessment of neuro-fuzzy models for estimating daily reference evapotranspiration
  273. Prediction of Discharge Coefficient for Trapezoidal Labyrinth Side Weir Using a Neuro-Fuzzy Approach
  274. Estimation of Reference Evapotranspiration: Need for Generalized Models
  275. Modeling monthly pan evaporations using fuzzy genetic approach
  276. Evaluation of MLP-ANN Training Algorithms for Modeling Soil Pore-Water Pressure Responses to Rainfall
  277. System dynamics simulation of soil water resources with data support from the Yucheng Comprehensive Experimental Station, North China
  278. Estimating soil wetting patterns for drip irrigation using genetic programming
  279. Damage detection in Timoshenko beam structures by multilayer perceptron and radial basis function networks
  280. Comparison of Gene Expression Programming with neuro-fuzzy and neural network computing techniques in estimating daily incoming solar radiation in the Basque Country (Northern Spain)
  281. Estimation of Daily Pan Evaporation Using Two Different Adaptive Neuro-Fuzzy Computing Techniques
  282. Estimation of Daily Suspended Sediment Load by Using Wavelet Conjunction Models
  283. Forecasting daily stream flows using artificial intelligence approaches
  284. Modeling discharge-suspended sediment relationship using least square support vector machine
  285. Estimating daily reference evapotranspiration using available and estimated climatic data by adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN)
  286. Prediction of fatty acid composition of vegetable oils based on rheological measurements using nonlinear models
  287. Suspended sediment modeling using genetic programming and soft computing techniques
  288. Application of Non-linear Models to Predict Inhibition Effects of Various Plant Hydrosols on Listeria monocytogenes Inoculated on Fresh-Cut Apples
  289. Pan Evaporation Modeling Using Neural Computing Approach for Different Climatic Zones
  290. SVM, ANFIS, regression and climate based models for reference evapotranspiration modeling using limited climatic data in a semi-arid highland environment
  291. River suspended sediment estimation by climatic variables implication: Comparative study among soft computing techniques
  292. Modeling of Dissolved Oxygen Concentration Using Different Neural Network Techniques in Foundation Creek, El Paso County, Colorado
  293. Precipitation forecasting by using wavelet-support vector machine conjunction model
  294. Forecasting Water Level Fluctuations of Urmieh Lake using Gene Expression Programming and Adaptive Neuro-Fuzzy Inference System
  295. Modeling antimicrobial effect of different grape pomace and extracts on S. aureus and E. coli in vegetable soup using artificial neural network and fuzzy logic system
  296. Letter to the Editor on “Precipitation Forecasting Using Wavelet-Genetic Programming and Wavelet-Neuro-Fuzzy Conjunction Models” by Ozgur Kisi & Jalal Shiri [Water Resources Management 25 (2011) 3135–3152]
  297. REPLY to Discussion of “Precipitation Forecasting Using Wavelet-Genetic Programming and Wavelet-Neuro-Fuzzy Conjunction Models”
  298. Least squares support vector machine for modeling daily reference evapotranspiration
  299. Forecasting daily lake levels using artificial intelligence approaches
  300. Generalized Neurofuzzy Models for Estimating Daily Pan Evaporation Values from Weather Data
  301. Modeling discharge–sediment relationship using neural networks with artificial bee colony algorithm
  302. Prediction of lateral outflow over triangular labyrinth side weirs under subcritical conditions using soft computing approaches
  303. River Flow Estimation and Forecasting by Using Two Different Adaptive Neuro-Fuzzy Approaches
  304. Investigating chaos in river stage and discharge time series
  305. Daily reference evapotranspiration modeling by using genetic programming approach in the Basque Country (Northern Spain)
  306. Wavelet and neuro-fuzzy conjunction model for streamflow forecasting
  307. A combined generalized regression neural network wavelet model for monthly streamflow prediction
  308. Prediction of Short-Term Operational Water Levels Using an Adaptive Neuro-Fuzzy Inference System
  309. Intermittent Streamflow Forecasting by Using Several Data Driven Techniques
  310. Modeling Reference Evapotranspiration Using Evolutionary Neural Networks
  311. Comparison of genetic programming with neuro-fuzzy systems for predicting short-term water table depth fluctuations
  312. Wind Speed Prediction by using Different Wavelet Conjunction Models
  313. River Suspended Sediment Load Prediction: Application of ANN and Wavelet Conjunction Model
  314. Application of Artificial Intelligence to Estimate Daily Pan Evaporation Using Available and Estimated Climatic Data in the Khozestan Province (South Western Iran)
  315. Precipitation Forecasting Using Wavelet-Genetic Programming and Wavelet-Neuro-Fuzzy Conjunction Models
  316. Comparison of three artificial intelligence techniques for discharge routing
  317. Two hybrid Artificial Intelligence approaches for modeling rainfall–runoff process
  318. Performance Evaluation of ANN and ANFIS Models for Estimating Garlic Crop Evapotranspiration
  319. Prediction of Effect of Natural Antioxidant Compounds on Hazelnut Oil Oxidation by Adaptive Neuro-Fuzzy Inference System and Artificial Neural Network
  320. Use of artificial neural networks for prediction of discharge coefficient of triangular labyrinth side weir in curved channels
  321. An Empirical Investigation of the Impact of Individual and Work Characteristics on Telecommuting Success
  322. A wavelet-support vector machine conjunction model for monthly streamflow forecasting
  323. Neural networks for estimation of discharge capacity of triangular labyrinth side-weir located on a straight channel
  324. Neural networks with artificial bee colony algorithm for modeling daily reference evapotranspiration
  325. A probe into the chaotic nature of daily streamflow time series by correlation dimension and largest Lyapunov methods
  326. Reply to the Discussion of “Evapotranspiration modelling using support vector machines” by R. J. Abrahartet al.
  327. Discussion of “Application of neural network and adaptive neuro-fuzzy inference systems for river flow prediction”*
  328. Frequency analyses of annual extreme rainfall series from 5 min to 24 h
  329. Short-term and long-term streamflow forecasting using a wavelet and neuro-fuzzy conjunction model
  330. Estimation of Suspended Sediment Yield in Natural Rivers Using Machine-coded Linear Genetic Programming
  331. Evapotranspiration Modeling Using Linear Genetic Programming Technique
  332. Wavelet Regression Model as an Alternative to Neural Networks for River Stage Forecasting
  333. Evapotranspiration modeling using a wavelet regression model
  334. Wavelet regression model for short-term streamflow forecasting
  335. Discussion of “Daily Pan Evaporation Modeling in a Hot and Dry Climate” by J. Piri, S. Amin, A. Moghaddamnia, A. Keshavarz, D. Han, and R. Remesan
  336. Daily pan evaporation modeling using linear genetic programming technique
  337. River suspended sediment concentration modeling using a neural differential evolution approach
  338. A machine code-based genetic programming for suspended sediment concentration estimation
  339. Application of two different neural network techniques to lateral outflow over rectangular side weirs located on a straight channel
  340. Reply to comment on ‘Kişi Ö. 2009. Daily pan evaporation modelling using multi-layer perceptrons and radial basis neural networks. Hydrological Processes 23(2): 213-223’
  341. Discussion of “Comparative Study of ANNs versus Parametric Methods in Rainfall Frequency Analysis” by Jianxun He and Caterina Valeo
  342. Fuzzy Genetic Approach for Modeling Reference Evapotranspiration
  343. Predicting discharge capacity of triangular labyrinth side weir located on a straight channel by using an adaptive neuro-fuzzy technique
  344. Wavelet regression model as an alternative to neural networks for monthly streamflow forecasting
  345. An artificial neural network model for the prediction of critical submergence for intake in a stratified fluid medium
  346. Comparison of two different data-driven techniques in modeling lake level fluctuations in Turkey
  347. Evapotranspiration modelling using support vector machines / Modélisation de l'évapotranspiration à l'aide de ‘support vector machines’
  348. Bridge afflux analysis through arched bridge constrictions using artificial intelligence methods
  349. Neural Networks and Wavelet Conjunction Model for Intermittent Streamflow Forecasting
  350. Neural network and wavelet conjunction model for modelling monthly level fluctuations in Turkey
  351. Daily suspended sediment estimation using neuro-wavelet models
  352. Comments on
  353. Evolutionary fuzzy models for river suspended sediment concentration estimation
  354. Adaptive neuro-fuzzy computing technique for suspended sediment estimation
  355. Modeling monthly evaporation using two different neural computing techniques
  356. Suspended sediment concentration estimation by an adaptive neuro-fuzzy and neural network approaches using hydro-meteorological data
  357. Modeling River Stage-Discharge Relationships Using Different Neural Network Computing Techniques
  358. Daily pan evaporation modelling using multi-layer perceptrons and radial basis neural networks
  359. Comment on ‘Nourani V, Mogaddam AA, Nadiri AO. 2008. An ANN-based model for spatiotemporal groundwater level forecasting.Hydrological Processes22: 5054-5066’
  360. Modelling daily suspended sediment of rivers in Turkey using several data-driven techniques / Modélisation de la charge journalière en matières en suspension dans des rivières turques à l'aide de plusieurs techniques empiriques
  361. Constructing neural network sediment estimation models using a data-driven algorithm
  362. Stream flow forecasting using neuro-wavelet technique
  363. Reply to comment on ‘Kisi O. 2007. Evapotranspiration modelling from climatic data using a neural computing technique.Hydrological Processes21:1925–1934’
  364. The potential of different ANN techniques in evapotranspiration modelling
  365. Initial assessment of bridge backwater using an artificial neural network approach
  366. A genetic programming approach to suspended sediment modelling
  367. Predicting the compressive strength of steel fiber added lightweight concrete using neural network
  368. River flow forecasting and estimation using different artificial neural network techniques
  369. Streamflow Forecasting Using Different Artificial Neural Network Algorithms
  370. Comparison of different ANN techniques in river flow prediction
  371. Wavelet and neuro-fuzzy conjunction model for precipitation forecasting
  372. Adaptive Neurofuzzy Computing Technique for Evapotranspiration Estimation
  373. Estimation of total sediment load concentration obtained by experimental study using artificial neural networks
  374. Prediction of Hydropower Energy Using ANN for the Feasibility of Hydropower Plant Installation to an Existing Irrigation Dam
  375. Türkçede Üçüncü Kişi Buyrum Yapıları
  376. Evapotranspiration modelling from climatic data using a neural computing technique
  377. Suspended sediment prediction using two different feed-forward back-propagation algorithms
  378. Generalized regression neural networks for evapotranspiration modelling
  379. Daily pan evaporation modelling using a neuro-fuzzy computing technique
  380. Evapotranspiration estimation using feed-forward neural networks
  381. Methods to improve the neural network performance in suspended sediment estimation
  382. River suspended sediment modelling using a fuzzy logic approach
  383. Discussion of ȁFuzzy logic model approaches to daily pan evaporation estimation in western Turkeyȁ
  384. Discussion of “Forecasting of Reference Evapotranspiration by Artificial Neural Networks” by Slavisa Trajkovic, Branimir Todorovic, and Miomir Stankovic
  385. Suspended sediment estimation using neuro-fuzzy and neural network approaches/Estimation des matières en suspension par des approches neurofloues et à base de réseau de neurones
  386. Closure to “Forecasting of Reference Evapotranspiration by Artificial Neural Networks” by Slavisa Trajkovic, Branimir Todorovic, and Miomir Stankovic
  387. Discussion of “Estimating Actual Evapotranspiration from Limited Climatic Data Using Neural Computing Technique” by K. P. Sudheer, A. K. Gosain, and K. S. Ramasastri
  388. Multi-layer perceptrons with Levenberg-Marquardt training algorithm for suspended sediment concentration prediction and estimation / Prévision et estimation de la concentration en matières en suspension avec des perceptrons multi-couches et l’algorithm...
  389. Daily suspended sediment modelling using a fuzzy differential evolution approach / Modélisation journalière des matières en suspension par une approche d’évolution différentielle floue
  390. River Flow Modeling Using Artificial Neural Networks
  391. Forecasting of Reference Evapotranspiration by Artificial Neural Networks
  392. Estimating Actual Evapotranspiration from Limited Climatic Data Using Neural Computing Technique
  393. Ten-Stage Discrete Flood Routing for Dams Having Gated Spillways