Zhang / Li / Hao | Neural Computing for Advanced Applications | E-Book | sack.de
E-Book

E-Book, Englisch, Band 2182, 352 Seiten, eBook

Reihe: Communications in Computer and Information Science

Zhang / Li / Hao Neural Computing for Advanced Applications

5th International Conference, NCAA 2024, Guilin, China, July 5–7, 2024, Proceedings, Part II
Erscheinungsjahr 2024
ISBN: 978-981-97-7004-5
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark

5th International Conference, NCAA 2024, Guilin, China, July 5–7, 2024, Proceedings, Part II

E-Book, Englisch, Band 2182, 352 Seiten, eBook

Reihe: Communications in Computer and Information Science

ISBN: 978-981-97-7004-5
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark



This book constitutes the refereed proceedings of the 5th International Conference on Neural Computing for Advanced Applications, NCAA 2024, held in Guilin, China, during July 5–7, 2024.The 89 revised full papers presented in these proceedings were carefully reviewed and selected from 227 submissions. The papers are organized in the following topical sections:Part I: Neural network (NN) theory, NN-based control systems, neuro-system integration and engineering applications; Computer vision, and their engineering applications.Part II: Computational intelligence, nature-inspired optimizers, their engineering applications, and benchmarks.Part III: Natural language processing, knowledge graphs, recommender systems, multimodal Deep Learning, and their applications; Fault diagnosis and forecasting, prognostic management, Time-series analysis, and cyber-physical system security.
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Weitere Infos & Material


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Computational intelligence, nature-inspired optimizers, their engineering applications, and benchmarks
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.- Path planning of mobile robot with improved RRT algorithm.

.- Adaptive allocation method of terminal container parameters based on evolutionary game.

.- Unmanned Combat Aerial Vehicle Air Combat Decision-Making Method Based on Trust Region-based Proximal Policy Optimization with Rollback.

.- Anomaly Detection of Residential Electricity Consumption Based on Ensemble Model of PSO-AE-XGBOOST.

.- Hybrid neuro-fuzzy modeling for electricity consump-tion Prediction in middle-income Gauteng, South Afri-ca: utilizing fuzzy c-means method.

.- Differential Evolution Algorithm Based on Staged Adaptive Mutation Strategy Selection.

.- Dual-Population Adaptive Strategy Comprehensive Learning Particle Swarm Optimization.

.- Many-objective artificial bee colony algorithm based on dual indicators.

.- Towards Efficient Federated Learning via Vehicle Selection and Resource Optimization in IoV.

.- Application of machine learning in enterprise financial risk assessment: A study about China’s A-share listed manufacturing companies.

.- A Decision Method Combining Multi granularity Rough Set and VIKOR Method.

.- A method for identifying fraudulent behavior in electricity bill collection based on nearest neighbor metric matching.

.- Fuzzy PID-Based Control Method for Thickness Uniformity in Blown Film.

.- Many-objective Artificial Bee Colony Algorithm Based on Decision Variable Grouping.

.- A NOVEL ELM OPTIMIZATION AND ITS APPLICATION IN IoT INTRUSION DETECTION.

.- Optimization of Rural Integrated Energy System with Shared Energy Storage on Multiple-timescales.

.- Synergistic Integration of Renewable Energy and HVDC Technology for Enhanced Multi-objective Economic Emission Dispatch using the Salp Swarm Algorithm.

.- Switched Data-Driven Model based Precise Forecasting of Photovoltaic Energy Generation.

.- Carbon Emission Efficiency Analysis of Pearl River Delta Ports Based on the Super-SBM-GML Index Model.

.- MWOA-SVM Based Algorithm in Tumor Cell Detection Research.

.- Rapid Detection of Formaldehyde Emission from Wood-based Panels Based on the IPOA-XGBoost.

.- Enhancing Rural Electrification: Delivering Affordable and Clean Electricity through Mobile Battery Solutions.

.- A novel electricity measurement system based on electricity usage identification.

.- Shared Task on NCAA 2024: Chinese Diabetes Question Classification.



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