Genetic and Evolutionary Computing

Proceedings of the Seventeen International Conference on Genetic and Evolutionary Computing, December 18–23, 2025, Fuzhou and Nanyang, China
Erscheinungsjahr 2026
ISBN: 978-981-9255-64-1
Verlag: Springer

Buch, Englisch, Format (B × H): 155 mm x 235 mm

Reihe: Lecture Notes in Electrical Engineering

This book contains accepted papers presented at ICGEC 2025, the 17th International Conference on Genetic and Evolutionary Computing, held from 18-23 December, 2025, in Fuzhou (Fujian province) and Nanyang (Henan province), China. The conference is intended as an international forum for the researchers and professionals in all areas of genetic and evolutionary computing. And the readers know the up-to-date techniques of the mentioned topics, including swarm intelligence, artificial intelligence, information hiding, and data mining techniques, which can help them to bring new ideas or apply the designed approaches from the collected papers to their professional jobs.

Zielgruppe

Research

Autoren/Hrsg.

Lin, Jerry Chun-Wei

Chu, Shu-Chuan

Pan, Jeng-Shyang

Liu, Liming

Fachgebiete

• Naturwissenschaften Biowissenschaften Biowissenschaften Evolutionsbiologie
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Optimierung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker

Inhaltsverzeichnis

A Data-Driven Framework for Intelligent Carbon Emission Regulation: Integrating Machine Learning with an Extended Kaya Identity.- Matching Ontologies via Dual-Population based Particle Swarm Optimization with Elite Aware Local Search.- An Enhanced Black-Winged Kite Algorithm and Its Application in the Capacitated Vehicle Routing Problem.- An adaptive-threshold warm-start improvement for the L-SHADE method for numerical optimization and analysis.- Lithium-Ion Battery SOC Optimized Estimation Via Improved Genetic Algorithm-Assisted BP Neural Network.- An excellent parallel dragonfly algorithm with compact strategy for numerical optimization.- RLMSROA: A Reinforcement Learning Driven Multi-Subpopulation Rafflesia Optimization Algorithm.- A Hybrid Meta-Heuristic for Multi-Objective Robot Path Planning in Complex Environments.- NCP-YOLOv11: A Dual Evolutionary Optimization-Driven Model for Small Target Detection in Remote Sensing Images.- Bilingual LLM-Powered Smart Assistant for Foreign-Related Legal Research.- AI drives the innovation of undergraduate vocational education courses: An innovative practice with "Web Technology Foundation".- Beyond Plain RF: SSA-BP Feature Gating for Clutch Failure Detection.- Market Response to Smart Bands Among Chinese University Students: A BERTopic Analysis of Online Reviews.- An Enhanced DV-Hop Localization Method for Power Grid Safety Inspection Applications.- Transmission Line Target Recognition and Ranging Based on Point Cloud Segmentation-Clutter Immunosuppression Filter.- Big Data-driven battery capacity refinement for electric vehicles: A machine learning-based multi-feature collaborative framework.

Über Autor(innen)

Jerry Chun-Wei Lin is currently working as the full professor at the Department of Distributed Systems and IT Devices, Silesian University of Technology, Poland. His research interests include data mining and analytics, soft computing, deep learning/machine learning, optimization, IoT applications, and privacy-preserving and security technologies. He is the leader of the well-known SPMF project, which provides more than 260 data mining algorithms and has been widely cited in many different applications (around 900 citation). He is the fellow of IET (FIET), ACM distinguished member (Scientist), and IEEE senior member.

Shu-Chuan Chu received a Ph.D. from Flinders University in Australia in 2004. Worked at Cheng Shiu University in Taiwan for 9 years, then joined Flinders University in 2009, served as a research fellow and an adjunct associate professor till 2019. From August 2019, she has been a professor at Shandong University of Science and Technology until 2024. Currently, she serves as a professor at Nanjing University of Information Science and Technology, interested in swarm intelligence, wireless sensor networks, and artificial intelligence.

Jeng-Shyang Pan received the M.S. degree in communication engineering from National Chiao Tung University, Hsinchu, Taiwan, in 1988, and the Ph.D. degree in electrical engineering from the University of Edinburgh, Edinburgh, U.K., in 1996. He is currently a professor and Ph.D. supervisor at the School of Artificial Intelligence, Nanjing University of Information Science and Technology, China. His current research interests include soft computing, information security, and signal processing.

Liming Liu, a professor and master’s supervisor, is an expert in computer engineering education accreditation recognized by the China Software Industry Association. He serves as a council member of the Information Technology New Engineering Education Alliance, a member of the National Research Association for Basic Computer Education in Higher Education Institutions, and an executive committee member of the National Conference for Deans and Department Heads of Applied Computer Science Programs. He is also an executive council member of the 5th Henan Computer Education Research Association and Secretary-General of the Nanyang Software Industry Technology Innovation Strategic Alliance. Additionally, he has served as a visiting scholar at Victoria University of Wellington, New Zealand, and is the secretary-general of the Nanyang Software Industry Technology Alliance. Professor Liu has presided over a project that received the Third Prize for Scientific and Technological Progress in Henan Province and holds two national patents.