Exploration of Novel Intelligent Optimization Algorithms

Exploration of Novel Intelligent Optimization Algorithms

12th International Symposium, ISICA 2021, Guangzhou, China, November 20-21, 2021, Revised Selected Papers

Wang, Wenxiang; Li, Kangshun; Liu, Yong

Springer Verlag, Singapore

08/2022

510

Mole

Inglês

9789811941085

15 a 20 dias

801

Descrição não disponível.
?Session 1: New Frontier of Multi-objective Evolutionary Algorithms.-Improved particle swarm algorithm and its application in sensor network optimization.-Image Segmentation by Improved Conical Area Evolutionary Algorithm.-An Efficient Multi-objective Algorithm with High Abundant Elite Information and Evolutionary Phase Self-adjusting for Many Objective Optimization.-Multi-objective Evolutionary Architecture Search of U-Net with Diamond Atrous Convolution.-A Multi-objective Evolutionary Algorithm Based on Piecewise Parallel Decomposition for Portfolio Optimization.-A Many-objective Anomaly Detection Model for Vehicle Network Based on Federated Learning and Differential Privacy Protection.-An Adaptive Reference Vector Strategy with Shape Estimation for Many-objective Optimization Problem.-Manifold learning algorithm based on constrained particle swarm multi-objective optimization.-Session 2: Intelligent Multi-media-The use of trusted log storage and verification system based on blockchain for Manufacturing Execution System.-The Combination of GRU and Dense Block for Image Denoising Network.-Construction Methods of Dujiangyan Tourism Culture Image Based on Text Information Mining Technology.-Research on Self-driving Lane and Traffic Marker Recognition Based on Deep Learning.-Measurement system for energy consumption of runtime software in embedded system.-Experiment analysis on Fast Features Bag approach for Pedestrian Re-recognition.-Contrast retention de-coloring based on cosine similarity.-Design and Implementation of Intelligent Garbage Sorting System Based on TensorFlow.
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artificial intelligence;computer hardware;computer networks;computer systems;computer vision;correlation analysis;data modeling;deep learning;evolutionary algorithms;genetic algorithms;image analysis;image processing;machine learning;network protocols;optimization problems;recognition detection;signal processing