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Titlebook: Bio-inspired Computing: Theories and Applications; 13th International C Jianyong Qiao,Xinchao Zhao,Shanguo Huang Conference proceedings 201

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發(fā)表于 2025-3-21 19:06:57 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Bio-inspired Computing: Theories and Applications
期刊簡(jiǎn)稱13th International C
影響因子2023Jianyong Qiao,Xinchao Zhao,Shanguo Huang
視頻videohttp://file.papertrans.cn/187/186387/186387.mp4
學(xué)科分類Communications in Computer and Information Science
圖書封面Titlebook: Bio-inspired Computing: Theories and Applications; 13th International C Jianyong Qiao,Xinchao Zhao,Shanguo Huang Conference proceedings 201
影響因子.This two-volume set (CCIS 951 and CCIS 952) constitutes the proceedings of the 13th International Conference on Bio-inspired Computing: Theories and Applications, BIC-TA 2018, held in Beijing, China, in November 2018..The 88 full papers presented in both volumes were selected from 206 submissions. The papers deal with studies abstracting computing ideas such as data structures, operations with data, ways to control operations, computing models from living phenomena or biological systems such as evolution, cells, neural networks, immune systems, swarm intelligence..
Pindex Conference proceedings 2018
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U-NSGA-III: An Improved Evolutionary Many-Objective Optimization Algorithm,ity. However, in an evolutionary process, areas near certain reference points which have no solution attached cannot be searched. To ensure the algorithm searching the entire solution space, and in particular, to avoid some areas not being explored due to no solution existing in the regions currentl
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,Elman Neural Network Optimized by Firefly Algorithm for Forecasting China’s Carbon Dioxide Emissionous pressure of large amounts of carbon dioxide (.) emissions, China is now actively implementing development strategy of low-carbon and emission reduction. Through the analysis of the influencing factors of . emissions in China, five key influencing factors are selected: urbanization level, gross d
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Differential Grouping in Cooperative Co-evolution for Large-Scale Global Optimization: The Experimeriable grouping. DG2 proposed by Omidvar et al. is accurate for variable grouping. DG2, which is a parameter-free differential grouping method, can distinguish overlapping components of decision variables of a function. In this paper, we test DG2 on high-dimensional functions with more than 1000 dim
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Spiking Neural P Systems with Anti-spikes Based on the Min-Sequentiality Strategy,r modeling biological systems. The spiking neural P system based on the min-sequentiality strategy is a special kind of membrane computing model. Anti-spikes and inhibitory functions are introduced into spiking neural P systems based on the min-sequentiality strategy. We construct two sequential spi
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