All Stories

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