All Stories

  1. Leveraging Feature Extraction to Perform Time-Efficient Selection for Machine Learning Applications
  2. Sonar-Based Deep Learning in Underwater Robotics: Overview, Robustness, and Challenges
  3. Enhancing Consumer Insights Through Multimodal Artificial Intelligence and Affective Computing
  4. Navigating the Future of Enterprises: Insights into Digital Transformation, Virtual Reality, and the Metaverse
  5. Optimization strategies in SEI: An analysis of SARIMA and additive Holt-Winters models
  6. A Machine Learning as a Service (MLaaS) Approach to Improve Marketing Success
  7. A Systematic Review on Responsible Multimodal Sentiment Analysis in Marketing Applications
  8. Augmented Reality in Omnichannel Marketing: A Systematic Review in the Retail Sector
  9. Deep learning for predicting respiratory rate from physiological signals
  10. Exploring Virtual Reality in Omnichannel Marketing: A Systematic Review
  11. Healing profiles in patients with a chronic diabetic foot ulcer: An exploratory study with machine learning
  12. Analysis of Constructive Heuristics with Cuckoo Search Algorithm, Firefly Algorithm and Simulated Annealing in Scheduling Problems
  13. Windy Energy Production Planning Considering Local Marginal Prices
  14. LSTS Toolchain Framework for Deep Learning Implementation into Autonomous Underwater Vehicle
  15. Roadmap on artificial intelligence and big data techniques for superconductivity
  16. A Collision Avoidance Method for Autonomous Underwater Vehicles Based on Long Short-Term Memories
  17. A Novel Approach to the Two-Dimensional Cargo Load Problem
  18. A Review on Artificial Intelligence Applications for Multiple Sclerosis Evaluation and Diagnosis
  19. A Review on Dimensionality Reduction for Machine Learning
  20. Analysing and Modeling Customer Success in Digital Marketing
  21. The Impact of the Size of the Partition in the Performance of Bat Algorithm
  22. Real-Time Automatic Wall Detection and Localization based on Side Scan Sonar Images
  23. Emerging Technologies and Applications for a Smart and Sustainable World
  24. Preface
  25. Machine Learning Methods for Signal, Image and Speech Processing
  26. A Novel Approach for Send Time Prediction on Email Marketing
  27. Artificial intelligence methods for applied superconductivity: material, design, manufacturing, testing, operation, and condition monitoring
  28. Deep Neural Networks Applied to Stock Market Sentiment Analysis
  29. A Self-Parametrization Framework for Meta-Heuristics
  30. A Review on MOEA and Metaheuristics for Feature-Selection
  31. A Tool for Air Cargo Planning and Distribution
  32. Data-Driven Disaster Management in a Smart City
  33. Deep Learning for Big Data
  34. Diagnostics of electrochemically exfoliated nanographite by infrared and Raman spectroscopy
  35. Remote Monitor System for Alzheimer Disease
  36. State of the Art of Wind and Power Prediction for Wind Farms
  37. State of the Art on Advanced Control of Electric Energy Transformation to Hydrogen
  38. Techno-Economic Feasibility Analysis and Optimal Design of Hybrid Renewable Energy Systems Coupled with Energy Storage
  39. Deep Learning in Biomedical and Health Informatics
  40. A Novel Discrete Particle Swarm Optimization Algorithm for the Travelling Salesman Problems
  41. Intelligent Scheduling with Reinforcement Learning
  42. A Hybrid Metaheuristics Parameter Tuning Approach for Scheduling through Racing and Case-Based Reasoning
  43. An Intelligent Monitoring System for Assessing Bee Hive Health
  44. Development of a Reinforcement Learning System to Solve the Job Shop Problem
  45. Solving the Job Shop Scheduling Problem with Reinforcement Learning: A Statistical Analysis
  46. The Fusion of Internet of Things, Artificial Intelligence, and Cloud Computing in Health Care
  47. Intelligent Systems Design and Applications
  48. Hybrid Intelligent Systems
  49. Proceedings of the Tenth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2018)
  50. Analysis of lot-sizing methods’ suitability for different manufacturing application scenarios oriented to MRP and JIT/Kanban environments
  51. Characterizing Parkinson’s Disease from Speech Samples Using Deep Structured Learning
  52. Application of the Simulated Annealing Algorithm to Minimize the makespan on the Unrelated Parallel Machine Scheduling Problem with Setup Times
  53. A Machine Learning Approach to Contact Databases’ Importation for Spam Prevention
  54. Decision Support Tool for Dynamic Scheduling
  55. Deep Reinforcement Learning as a Job Shop Scheduling Solver: A Literature Review
  56. Ontology-Based Meta-model for Hybrid Collaborative Scheduling
  57. Automatic detection of Parkinson’s disease based on acoustic analysis of speech
  58. Model Proposal to Evaluate the Quality of a Production Planning and Control Software in an Industrial Context
  59. An Industry 4.0 oriented tool for supporting dynamic selection of dispatching rules based on Kano model satisfaction scheduling
  60. Preface
  61. The Influence of Problem Specific Neighborhood Structures in Metaheuristics Performance
  62. A Dynamic Selection of Dispatching Rules Based on the Kano Model Satisfaction Scheduling Tool
  63. A low-cost automatic fall prevention system for inpatients
  64. Manufacturing Services Classification in a Decentralized Supply Chain Using Text Mining
  65. Neurodegenerative Diseases Detection Through Voice Analysis
  66. Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016)
  67. Evaluation of the Simulated Annealing and the Discrete Artificial Bee Colony in the Weight Tardiness Problem with Taguchi Experiments Parameterization
  68. Industrial Plant Layout Analyzing Based on SNA
  69. Metaheuristics Parameter Tuning Using Racing and Case-Based Reasoning in Scheduling Systems
  70. Specification of an Architecture for Self-organizing Scheduling Systems
  71. Intelligent Systems Design and Applications
  72. Evaluating the effectiveness of Bayesian and Neural Networks for Adaptive Schedulling Systems
  73. Study on the impact of the NS in the performance of meta-heuristics in the TSP
  74. Self-Optimizing A Multi-Agent Scheduling System: A Racing Based Approach
  75. User modelling in scheduling system with artificial neural networks
  76. Racing based approach for Metaheuristics parameter tuning
  77. Q-learning based hyper-heuristic for scheduling system self-parameterization
  78. Scheduling single-machine problem oriented by Just-in-Time principles — A case study
  79. An integer programming approach for balancing and scheduling in extended manufacturing environment
  80. Scheduling and batching in multi-site flexible flow shop environments
  81. Selection constructive based hyper-heuristic for dynamic scheduling
  82. An ordered heuristic for the allocation of resources in unrelated parallel-machines
  83. A hybrid framework for supporting scheduling in extended manufacturing environments
  84. Using personas for supporting user modeling on scheduling systems
  85. An ordered approach to Minimum Completion Time in unrelated parallel-machines for the makespan optimization
  86. Alternative approaches analysis for scheduling in an Extended Manufacturing Environment
  87. An architecture for user modeling on Intelligent and Adaptive Scheduling Systems
  88. Cooperation Mechanism for Distributed resource scheduling through artificial bee colony based self-organized scheduling system
  89. Manufacturing rush orders rescheduling: a supervised learning approach
  90. Parallel machines scheduling with fuzzy simulated annealing
  91. Prototype of an Adaptive Decision Support System for Interactive Scheduling with MetaCognition and User Modeling Experience
  92. Ordered minimum completion time heuristic for unrelated parallel-machines problems
  93. Negotiation mechanism for self-organized scheduling system with collective intelligence
  94. Collaborative Framework for Dynamic Scheduling Supporting in Networked Manufacturing Environments
  95. Learning-Assisted Intelligent Scheduling System
  96. Towards Scheduling Optimization through Artificial Bee Colony Approach
  97. Desenvolvimento e avaliação de um interface com o utilizador para um sistema de escalonamento
  98. Self-Optimization module for Scheduling using Case-based Reasoning
  99. Developing Issues for Ant Colony System Based Approach for Scheduling Problems
  100. Tuning Meta-Heuristics Using Multi-agent Learning in a Scheduling System
  101. A User-Centered Interface for Scheduling Problem Definition
  102. Cooperative Scheduling System with Emergent Swarm Based Behavior
  103. Editorial A Successful Change From TNN to TNNLS and a Very Successful Year
  104. Ant Colony System based approach to single machine scheduling problems: Weighted tardiness scheduling problem
  105. Multi-apprentice learning for meta-heuristics parameter tuning in a Multi Agent Scheduling System
  106. Conflicts Management in Retail Systems with Self-Regulation
  107. Meta-heuristics Self-Parameterization in a Multi-agent Scheduling System Using Case-Based Reasoning
  108. Negotiation mechanism for self-organized scheduling system
  109. Self-organization for scheduling in agile manufacturing
  110. Computational Intelligence for Engineering Systems
  111. Scheduling a Cutting and Treatment Stainless Steel Sheet Line with Self-Management Capabilities
  112. Case-based reasoning for Self-Optimizing behavior
  113. Meta-heuristics tunning using CBR for dynamic scheduling
  114. Collective intelligence on dynamic manufacturing scheduling optimization
  115. Intelligent Bio-Inspired system for manufacturing scheduling under uncertainties
  116. Self-optimizing through CBR learning
  117. Self-Optimization for Dynamic Scheduling in Manufacturing Systems
  118. Inter-Machine Cooperation Mechanism for Dynamic Scheduling
  119. MASDScheGATS - Scheduling System for Dynamic Manufacturing Environmemts
  120. A Hybrid Intelligent System for Distributed Dynamic Scheduling
  121. Hybrid Multi-agent System for Cooperative Dynamic Scheduling Through Meta-Heuristics
  122. Hybrid Multi-agent System for Cooperative Dynamic Scheduling Through Meta-Heuristics
  123. An Inter-Machine Activity Coordination based Approach for Dynamic Job Shop Scheduling
  124. A Genetic Algorithm for the Dynamic Single Machine Scheduling Problem
  125. Hybrid Meta-Heuristics Based System for Dynamic Scheduling
  126. Hybrid Meta-Heuristics Based System for Dynamic Scheduling
  127. Hybrid Meta-Heuristics Based System for Dynamic Scheduling
  128. Broker's Direct Cost and Time Variables and Expressions
  129. Developing a Multi-Agent System for Dynamic Scheduling Trough Aose Perspective
  130. Resource-oriented scheduling for real world manufacturing systems
  131. A coordination mechanism for real world scheduling problems using genetic algorithms