All Stories

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