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International Conference on Neural Computing for Advanced Applications: 4th International Conference, NCAA 2023, Hefei, China, July 79, 2023, Proceedings, Part I 1st ed. 2023 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 576 pages, height x width: 235x155 mm, weight: 908 g, 218 Illustrations, color; 69 Illustrations, black and white; XXIII, 576 p. 287 illus., 218 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 1869
  • Izdošanas datums: 01-Sep-2023
  • Izdevniecība: Springer Verlag, Singapore
  • ISBN-10: 9819958431
  • ISBN-13: 9789819958436
  • Mīkstie vāki
  • Cena: 91,53 €*
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  • Formāts: Paperback / softback, 576 pages, height x width: 235x155 mm, weight: 908 g, 218 Illustrations, color; 69 Illustrations, black and white; XXIII, 576 p. 287 illus., 218 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 1869
  • Izdošanas datums: 01-Sep-2023
  • Izdevniecība: Springer Verlag, Singapore
  • ISBN-10: 9819958431
  • ISBN-13: 9789819958436
The two-volume set CCIS 1869 and 1870 constitutes the refereed proceedings of the 4th International Conference on Neural Computing for Advanced Applications, NCAA 2023, held in Hefei, China, in July 2023.

The 83 full papers and 1 short paper presented in these proceedings were carefully reviewed and selected from 211 submissions. The papers have been organized in the following topical sections: Neural network (NN) theory, NN-based control systems, neuro-system integration and engineering applications; Machine learning and deep learning for data mining and data-driven applications; Computational intelligence, nature-inspired optimizers, and their engineering applications; Deep learning-driven pattern recognition, computer vision and its industrial applications; Natural language processing, knowledge graphs, recommender systems, and their applications; Neural computing-based fault diagnosis and forecasting, prognostic management, and cyber-physical system security; Sequence learning for spreading dynamics, forecasting, and intelligent techniques against epidemic spreading (2); Applications of Data Mining, Machine Learning and Neural Computing in Language Studies; Computational intelligent Fault Diagnosis and Fault-Tolerant Control, and Their Engineering Applications; and Other Neural computing-related topics.
Neural network (NN) theory, NN-based control systems, neuro-system
integration and engineering applications: ESN-based Control of Bending
Pneumatic Muscle with Asymmetric and Rate-dependent Hysteresis.- Image
Reconstruction and Recognition of Optical Flow Based on Local Feature
Extraction Mechanism of Visual Cortex.- Conditional Diffusion Model-Based
Data Augmentation for Alzheimers Prediction.- Design of dissolved oxygen
online controller based on adaptive dynamic programming theory.- Ascent
Guidance for Airbreathing Hypersonic Vehicle based on Deep Neural Network and
Pseudo-Spectral Method.- Machine learning and deep learning for data mining
and data-driven applications: Image Intelligence-Assisted Time-Series
Analysis Method for Identifying Dispersed, Disordered, and Polluting Sites
Based on Power Consumption Data.- Non-intrusive Load Identiffcation Based on
Steady-state V-I Trajectory.- Predictionof TP in effluent at multiple scales
based on ESN.- Application of WOA-SVM based algorithm in tumor cell detection
research.- MM-VTON: A Multi-stage Virtual Try-on Method Using Multiple Image
Features.- Self-Attention-Based Reconstruction for Planetary Magnetic
Field.- Semi-supervised Multi-class Classification Methods Based on Laplacian
Vector Projection.-  Integrating EMD, LMD and TCN Methods for COVID-19
Forecasting.- Computational intelligence, nature-inspired optimizers, and
their engineering applications: LOS Guidance Law for Unmanned Surface Vehicle
Path Following with Unknown Time-Varying Sideslip Compensation.- Application
of Bat Algorithm To Reduce Power Loss In Electrical Power Systems.- An
enhanced subregion dominance relation for evolutionary many-objective
optimization.- A stacked autoencoder based meta-learning model for global
optimization.- Optimization Design of Photovoltaic Power Generation System
under Complex Lighting Conditions.- Analysis of the impact of regional
customer charging on the grid under the aggregator model.- Indicators
directed multi-strategy artificial bee colony algorithm.- Energy-Efficient
Cellular Offloading Optimization for UAV-Aided Network.- Artificial bee
colony based on adaptive search strategies and elite selection
mechanism.- Minimization of Active Power Loss Using Enhanced Particle Swarm
Optimization.- Preference Weight Vector Adjustment Strategy Based Dynamic
Multiobjective Optimization.- Complementary environmental selection for
evolutionary many-objective optimization.- An Investigation on Effects of
Exemplars Selection to Convergence and Diversity in Large-Scale Particle
Swarm Optimizer.- A LSTM assisted Prediction Strategy for Evolutionary
Dynamic Multiobjective Optimization.- An Adaptive Brain Storm Optimization
Based on Hierarchical Learning for Community Detection.- Optimization Method
Of Multi-Body Integrated Energy System Considering Air Compression Energy
Storage.- Sequential Seeding Initialization for SNIC Superpixels.- Dynamic
multi-objective prediction strategy for transfer learning based on imbalanced
data classification.- A twin learning evolutionary algorithm for capacitated
vehicle routing problem.- Research on Full-coverage Path Planning Method of
Steel Rolling Shop Cleaning Robot.- Deep Reinforcement Learning Method of
Target Hunting for Multi-agents with Flocking Property.- Design of particle
swarm optimized fuzzy PID controller and its application in superheat degree
control.- A multi-style interior floor plan design approach based on
generative adversarial networks.- Linear Model-based Optimal VVC Intercoding
Rate Control Scheme.- Detection and analysis of hanging basket wire rope
broken strands based on Mallat algorithm.- PointAF: A Novel Semantic
Segmentation Network for Point Cloud.- Accurate Detection of the Workers and
Machinery in Construction Sites Considering the Occlusions.- Research on
crack identification of Highway Asphalt Pavement Based on deep learning.