International Conference on Neural Computing for Advanced Applications

ISBN-13: 9789819958436 / Angielski / Miękka / 2023

Opis

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.

Spis treści

​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 Alzheimer’s 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.- Prediction of 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.