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Titlebook: Bio-Inspired Computing: Theories and Applications; 16th International C Linqiang Pan,Zhihua Cui,Lianghao Li Conference proceedings 2022 Spr

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樓主: 拖累
11#
發(fā)表于 2025-3-23 10:45:07 | 只看該作者
A Differential Evolution Algorithm for Multi-objective Mixed-Variable Optimization Problemsmultiple complex functions, constraints and mixed types of decision variables. Compared with single objective mixed-variable optimization problems (MVOPs), the decision space of MO-MVOPs presents more complex spatial distribution features. These features of MO-MVOPs make solving such problems face a
12#
發(fā)表于 2025-3-23 17:46:10 | 只看該作者
13#
發(fā)表于 2025-3-23 20:33:33 | 只看該作者
Adaptive Multi-strategy Learning Particle Swarm Optimization with Evolutionary State Estimation mode is relatively fixed, and it is easy to be trapped in the local optimum. Most variants of PSO use only one learning strategy in the entire evolution process, which may affect their performance when different learning strategies are required under different evolution states. In order to deal wit
14#
發(fā)表于 2025-3-24 01:40:05 | 只看該作者
15#
發(fā)表于 2025-3-24 05:08:10 | 只看該作者
Adaptive Differential Privacy Budget Allocation Algorithm Based on Random Foresty protection method is to add differential privacy in the process of data mining, but the unreasonable privacy budget allocation leads to unsatisfactory classification results. To solve this problem, an adaptive differential privacy budget allocation algorithm RFDPP-weight based on random forest is
16#
發(fā)表于 2025-3-24 06:59:22 | 只看該作者
A Node Influence Based Memetic Algorithm for Community Detection in Complex Networksion treats finding the community structure as an optimization problem, which has received great attentions in a variety of fields these years. Several community detection methods have been proposed. To make an approach of detecting the community structure in a more efficient way, a node influence ba
17#
發(fā)表于 2025-3-24 13:14:39 | 只看該作者
18#
發(fā)表于 2025-3-24 18:15:00 | 只看該作者
A Hybrid Multi-objective Coevolutionary Approach for the Multi-user Agile Earth Observation Satellitagement. In this study, a MU-AEOSSP is addressed to tackle the failure rate and the fairness of different users simultaneously. A hybrid multi-objective coevolutionary approach (HMOCA) is then proposed to handle the complicate constraints and to optimize the objectives. HMOCA evolves two populations
19#
發(fā)表于 2025-3-24 19:11:32 | 只看該作者
Conference proceedings 2022: Theories and Applications, BIC-TA 2021, held in Taiyuan, China, in December 2021.?.The 67 papers presented were thoroughly reviewed and selected from 211 submissions. The papers are organized in the following topical sections: ?evolutionary computation and swarm intelligence; DNA and molecular computing; ?machine learning and computer vision..
20#
發(fā)表于 2025-3-25 02:41:24 | 只看該作者
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