Advances in Swarm Intelligence: Lecture Notes in Computer Science, cartea 16011
Editat de Ying Tan, Yuhui Shien Limba Engleză Paperback – 13 oct 2025
The 104 full papers presented in this volume were carefully reviewed and selected from 177 submissions. They cover topics such as: Swarm Intelligence and Nature-Inspired Computing; Swarm-based Computing Algorithms for Optimization; Particle Swarm Optimization; Ant Colony Optimization; Differential Evolution; Genetic Algorithm and Evolutionary Computation; Fireworks Algorithms; Brain Storm Optimization Algorithm; Bacterial Foraging Optimization Algorithm; DNA Computing Methods; Multi-Objective Optimization; Swarm Robotics and Multi-Agent System; UAV Cooperation and Control; Machine Learning; Data Mining; and Other Applications.
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Specificații
ISBN-13: 9789819509812
ISBN-10: 9819509815
Pagini: 369
Ilustrații: Approx. 500 p.
Dimensiuni: 155 x 235 mm
Greutate: 0.59 kg
Editura: Springer Verlag GmbH
Seria Lecture Notes in Computer Science
ISBN-10: 9819509815
Pagini: 369
Ilustrații: Approx. 500 p.
Dimensiuni: 155 x 235 mm
Greutate: 0.59 kg
Editura: Springer Verlag GmbH
Seria Lecture Notes in Computer Science
Cuprins
.- Particle Swarm Optimization.
.- Set-Based Particle Swarm Optimization for the Multi-Objective Multi-Dimensional Knapsack Problem.
.- Proposal of a Memory-Based Ensemble Particle Swarm Optimizer.
.- A Tri-swarm Particle Swarm Optimization Considering the Cooperation and the Fitness Value.
.- A Modified Variable Velocity Strategy Particle Swarm Optimization Algorithm for Multi-objective Feature Selection.
.- Multi-Strategy Enhanced Particle Swarm Optimization Algorithm for Elevator Group Scheduling.
.- A Self-Learning Particle Swarm Optimization Algorithm for Dynamic Job Shop Scheduling Problem with New Jobs Insertion.
.- Convolutional Neural Network Architecture Design Using An Improved Surrogate-assisted Particle Swarm Optimization Algorithm.
.- Swarm Intelligence Computing.
.- Cooperative Search and Rescue Target Assignment Based on Improved Ant Colony Algorithm.
.- A Metabolic Pathway Design Method based on surrogate-assisted Fireworks Algorithm.
.- Circle Chaotic Search-Based Butterfly Optimization Algorithm.
.- An Adaptive Bacterial Foraging Optimization Algorithm Based on Chaos-Enhanced Non-Elite Reverse Learning.
.- Enhanced Bacterial Foraging Optimization with Dynamic Disturbance Learning and Bilayer Nested Structure.
.- Improved Kepler Optimization Algorithm Based on Mixed Strategy.
.- Harmony Search with Dynamic Dimensional-reduction Adjustment Strategy for Large-scale Absolute Value Equation.
.- Massive Conscious Neighborhood-based Crow Search Algorithm for the Pseudo-Coloring Problem.
.- Multi-Strategy Integration Model Based on Black-Winged Kite Algorithm and Artificial Rabbit Optimization.
.- Differential Evolution.
.- Fractional Order Differential Evolution to Solve Parameter Estimation Problem of Solar Photovoltaic Models.
.- Enhanced Dingo Optimization Algorithm Based on Differential Evolution and Chaotic Mapping for Engineering Optimization.
.- Hierarchical Adaptive Differential Evolution with Local Search for Extreme Learning Machine.
.- Metaheuristic Algorithms for Enhancing Multicepstral Representation in Voice Spoofing Detection: An Experimental Approach.
.- Evolutionary Algorithms.
.- A Multi-modal Multi-objective Evolutionary Algorithm Based on Multi-criteria Grouping.
.- Constructing Robust and Influential Networks against Cascading Failures via a Multi-objective Evolutionary Algorithm.
.- Fault Reconfiguration of Distribution Networks Using an Enhanced Multimodal Multi-objective Evolutionary Algorithm.
.- Attacking Evolutionary Algorithms via SparseEA.
.- Evolutionary Computation with Distance-based Pretreatment for Multimodal Problems.
.- Multi-Agent Reinforcement Learning.
.- Stock Price Prediction Model Based on Blending Model Improved with Sentiment Factors and Double Q-learning.
.- Stock price prediction mdoel integrating an improved NSGA-III with Random Forest.
.- Unveiling the Decision-Making Process in Reinforcement Learning with Genetic Programming.
.- Diversity Improved Genetic Algorithm for Weapon Target Assignment.
.- An Investigation of Underground Rescue Scheduling with Multi-Agent Reinforcement Learning.
.- Distributed Advantage-based Weights Reshaping Algorithm with Sparse Reward.
.- Multi-objective Optimization.
.- A Joint Prediction Strategy based on Multiple Feature Points for Dynamic Multi-objective Optimization.
.- An Expensive Multi-objective Optimization Algorithm Based on Regional Density Ratio.
.- Robust Lightweight Neural Network Architecture Search-based on Multi-objective Particle Swarm Optimization.
.- Surrogate-Assisted Multi-Objective Evolutionary Algorithm Guided by Multi-Reference Points.
.- Multi-objective Path planning of Multiple Unmanned Air Vehicles Using the CCMO Algorithm.
.- Multi-UAV Collaborative Detection Based on Reinforcement Learning.
.- Set-Based Particle Swarm Optimization for the Multi-Objective Multi-Dimensional Knapsack Problem.
.- Proposal of a Memory-Based Ensemble Particle Swarm Optimizer.
.- A Tri-swarm Particle Swarm Optimization Considering the Cooperation and the Fitness Value.
.- A Modified Variable Velocity Strategy Particle Swarm Optimization Algorithm for Multi-objective Feature Selection.
.- Multi-Strategy Enhanced Particle Swarm Optimization Algorithm for Elevator Group Scheduling.
.- A Self-Learning Particle Swarm Optimization Algorithm for Dynamic Job Shop Scheduling Problem with New Jobs Insertion.
.- Convolutional Neural Network Architecture Design Using An Improved Surrogate-assisted Particle Swarm Optimization Algorithm.
.- Swarm Intelligence Computing.
.- Cooperative Search and Rescue Target Assignment Based on Improved Ant Colony Algorithm.
.- A Metabolic Pathway Design Method based on surrogate-assisted Fireworks Algorithm.
.- Circle Chaotic Search-Based Butterfly Optimization Algorithm.
.- An Adaptive Bacterial Foraging Optimization Algorithm Based on Chaos-Enhanced Non-Elite Reverse Learning.
.- Enhanced Bacterial Foraging Optimization with Dynamic Disturbance Learning and Bilayer Nested Structure.
.- Improved Kepler Optimization Algorithm Based on Mixed Strategy.
.- Harmony Search with Dynamic Dimensional-reduction Adjustment Strategy for Large-scale Absolute Value Equation.
.- Massive Conscious Neighborhood-based Crow Search Algorithm for the Pseudo-Coloring Problem.
.- Multi-Strategy Integration Model Based on Black-Winged Kite Algorithm and Artificial Rabbit Optimization.
.- Differential Evolution.
.- Fractional Order Differential Evolution to Solve Parameter Estimation Problem of Solar Photovoltaic Models.
.- Enhanced Dingo Optimization Algorithm Based on Differential Evolution and Chaotic Mapping for Engineering Optimization.
.- Hierarchical Adaptive Differential Evolution with Local Search for Extreme Learning Machine.
.- Metaheuristic Algorithms for Enhancing Multicepstral Representation in Voice Spoofing Detection: An Experimental Approach.
.- Evolutionary Algorithms.
.- A Multi-modal Multi-objective Evolutionary Algorithm Based on Multi-criteria Grouping.
.- Constructing Robust and Influential Networks against Cascading Failures via a Multi-objective Evolutionary Algorithm.
.- Fault Reconfiguration of Distribution Networks Using an Enhanced Multimodal Multi-objective Evolutionary Algorithm.
.- Attacking Evolutionary Algorithms via SparseEA.
.- Evolutionary Computation with Distance-based Pretreatment for Multimodal Problems.
.- Multi-Agent Reinforcement Learning.
.- Stock Price Prediction Model Based on Blending Model Improved with Sentiment Factors and Double Q-learning.
.- Stock price prediction mdoel integrating an improved NSGA-III with Random Forest.
.- Unveiling the Decision-Making Process in Reinforcement Learning with Genetic Programming.
.- Diversity Improved Genetic Algorithm for Weapon Target Assignment.
.- An Investigation of Underground Rescue Scheduling with Multi-Agent Reinforcement Learning.
.- Distributed Advantage-based Weights Reshaping Algorithm with Sparse Reward.
.- Multi-objective Optimization.
.- A Joint Prediction Strategy based on Multiple Feature Points for Dynamic Multi-objective Optimization.
.- An Expensive Multi-objective Optimization Algorithm Based on Regional Density Ratio.
.- Robust Lightweight Neural Network Architecture Search-based on Multi-objective Particle Swarm Optimization.
.- Surrogate-Assisted Multi-Objective Evolutionary Algorithm Guided by Multi-Reference Points.
.- Multi-objective Path planning of Multiple Unmanned Air Vehicles Using the CCMO Algorithm.
.- Multi-UAV Collaborative Detection Based on Reinforcement Learning.