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This book provides a comprehensive presentation on energy-efficient management in subway system via operations research and uncertain optimization methods. It is suitable for researchers, engineers, and students in the fields of transport management. The readers will learn numerous new modeling ideas on reducing traction energy consumption and improving regenerative energy utilization, and find this work a useful reference.
Public finance. --- Business. --- Environmental management. --- Public Economics. --- Popular Science in Business and Management. --- Environmental Management. --- Environmental stewardship --- Stewardship, Environmental --- Environmental sciences --- Management --- Trade --- Economics --- Commerce --- Industrial management --- Cameralistics --- Public finance --- Public finances --- Currency question
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Expert systems (Computer science) --- Sustainable engineering
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This book provides a comprehensive presentation on energy-efficient management in subway system via operations research and uncertain optimization methods. It is suitable for researchers, engineers, and students in the fields of transport management. The readers will learn numerous new modeling ideas on reducing traction energy consumption and improving regenerative energy utilization, and find this work a useful reference.
Public finance --- Environmental protection. Environmental technology --- Business management --- milieubeleid --- organisatiecultuur --- overheidsfinanciën
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This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.
Engineering. --- Artificial intelligence. --- Data mining. --- Computational Intelligence. --- Artificial Intelligence. --- Data Mining and Knowledge Discovery. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Natural computation. --- Machine learning. --- Learning, Machine --- Artificial intelligence --- Biologically-inspired computing --- Bio-inspired computing --- Natural computing --- Computational intelligence. --- Intelligence, Computational --- Soft computing
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This book discusses all the major nature-inspired algorithms with a focus on their application in the context of solving navigation and routing problems. It also reviews the approximation methods and recent nature-inspired approaches for practical navigation, and compares these methods with traditional algorithms to validate the approach for the case studies discussed. Further, it examines the design of alternative solutions using nature-inspired techniques, and explores the challenges of navigation and routing problems and nature-inspired metaheuristic approaches. .
Mathematical optimization. --- Algorithms. --- Algorism --- Algebra --- Arithmetic --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Foundations --- Computational intelligence. --- Computer science—Mathematics. --- Computer simulation. --- Computational Intelligence. --- Algorithm Analysis and Problem Complexity. --- Mathematics of Computing. --- Simulation and Modeling. --- Computer modeling --- Computer models --- Modeling, Computer --- Models, Computer --- Simulation, Computer --- Electromechanical analogies --- Mathematical models --- Model-integrated computing --- Intelligence, Computational --- Artificial intelligence --- Soft computing
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Public finance --- Environmental protection. Environmental technology --- Business management --- milieubeleid --- organisatiecultuur --- overheidsfinanciën
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This book discusses all the major nature-inspired algorithms with a focus on their application in the context of solving navigation and routing problems. It also reviews the approximation methods and recent nature-inspired approaches for practical navigation, and compares these methods with traditional algorithms to validate the approach for the case studies discussed. Further, it examines the design of alternative solutions using nature-inspired techniques, and explores the challenges of navigation and routing problems and nature-inspired metaheuristic approaches. .
Mathematics --- Computer science --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- neuronale netwerken --- fuzzy logic --- cybernetica --- informatica --- mineralen (chemie) --- externe fixatie (geneeskunde --- mijnbouw --- algoritmen --- KI (kunstmatige intelligentie) --- AI (artificiële intelligentie)
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This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.
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