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Advances in swarm intelligence15th International Conference on Swarm Intelligence, ICSI 2024, Xining, China, August 23-26, 2024 : proceedings.Part I /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Advances in swarm intelligenceedited by Ying Tan, Yuhui Shi.
Reminder of title:	15th International Conference on Swarm Intelligence, ICSI 2024, Xining, China, August 23-26, 2024 : proceedings.
remainder title:	ICSI 2024
other author:	Tan, Ying.
corporate name:
Published:	Singapore :Springer Nature Singapore :2024.
Description:	xxii, 478 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Swarm intelligenceCongresses.
Online resource:	https://doi.org/10.1007/978-981-97-7181-3
ISBN:	9789819771813$q(electronic bk.)

Advances in swarm intelligence15th International Conference on Swarm Intelligence, ICSI 2024, Xining, China, August 23-26, 2024 : proceedings.Part I /
Advances in swarm intelligence15th International Conference on Swarm Intelligence, ICSI 2024, Xining, China, August 23-26, 2024 : proceedings.Part I /[electronic resource] :ICSI 2024edited by Ying Tan, Yuhui Shi. - Singapore :Springer Nature Singapore :2024. - xxii, 478 p. :ill., digital ;24 cm. - Lecture notes in computer science,147880302-9743 ;. - Lecture notes in computer science ;4891..

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.

This two-volume set LNCS 14788 and 14789 constitutes the refereed post-conference proceedings of the 15th International Conference on Advances in Swarm Intelligence, ICSI 2024, held in Xining, China, during August 23-26, 2024. The 74 revised full papers presented in these proceedings were carefully reviewed and selected from 156 submissions. The papers are organized in the following topical sections: Part I - Particle swarm optimization; Swarm intelligence computing; Differential evolution; Evolutionary algorithms; Multi-agent reinforcement learning & Multi-objective optimization. Part II - Route planning problem; Machine learning; Detection and prediction; Classification; Edge computing; Modeling and optimization & Analysis of review.

ISBN: 9789819771813$q(electronic bk.)

Standard No.: 10.1007/978-981-97-7181-3doiSubjects--Topical Terms:

442896
Swarm intelligence
--Congresses.

LC Class. No.: Q337.3

Dewey Class. No.: 006.3824

Advances in swarm intelligence15th International Conference on Swarm Intelligence, ICSI 2024, Xining, China, August 23-26, 2024 : proceedings.Part I /
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