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Titlebook: DNA Computing Based Genetic Algorithm; Applications in Indu Jili Tao,Ridong Zhang,Yong Zhu Book 2020 Springer Nature Singapore Pte Ltd. 202

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書目名稱DNA Computing Based Genetic Algorithm
副標(biāo)題Applications in Indu
編輯Jili Tao,Ridong Zhang,Yong Zhu
視頻videohttp://file.papertrans.cn/261/260121/260121.mp4
概述Provides step-by-step tutorials and program codes.Presents GA applications for single-objective and multi-objective optimization in connection with nonlinear system modeling and distributed parameter
圖書封面Titlebook: DNA Computing Based Genetic Algorithm; Applications in Indu Jili Tao,Ridong Zhang,Yong Zhu Book 2020 Springer Nature Singapore Pte Ltd. 202
描述This book focuses on the implementation, evaluation and application of DNA/RNA-based genetic algorithms in connection with neural network modeling, fuzzy control, the Q-learning algorithm and CNN deep learning classifier. It presents several DNA/RNA-based genetic algorithms and their modifications, which are tested using benchmarks, as well as detailed information on the implementation steps and program code. In addition to single-objective optimization, here genetic algorithms are also used to solve multi-objective optimization for neural network modeling, fuzzy control, model predictive control and PID control. In closing, new topics such as Q-learning and CNN are introduced. The book offers a valuable reference guide for researchers and designers in system modeling and control, and for senior undergraduate and graduate students at colleges and universities.?
出版日期Book 2020
關(guān)鍵詞Genetic algorithm; Neural network; Multi-objective optimization; Model predictive control; Fuzzy control
版次1
doihttps://doi.org/10.1007/978-981-15-5403-2
isbn_softcover978-981-15-5405-6
isbn_ebook978-981-15-5403-2
copyrightSpringer Nature Singapore Pte Ltd. 2020
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DNA Double-Helix and SQP Hybrid Genetic Algorithm, (HGA) is proposed in this chapter for the highly nonlinear constrained functions. Thereafter, the theoretical analysis for the convergence of the HGA is then made. In the global exploration phase, the Hamming cliff problem is solved by DNA double-helix structure, and DNA computing inspired operator
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DNA Computing Based Multi-objective Genetic Algorithm,, the inconsistent multi-objective functions are converted into Pareto rank value and density information of solution distribution. Then, the archive is introduced to keep the Pareto front individuals by Pareto sorting, and the maintaining scheme is executed to maintain the evenness of individual di
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Parameter Identification and Optimization of Chemical Processes,e the modeling and optimization problems. In this chapter, the estimation of model parameters for heavy oil thermal cracking is firstly solved by RNA-GA. Then, we use DNA-DHGA to solve the recipe optimization problem of gasoline blending with heavy nonlinear inequality constraints. DNA computing bas
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Further Idea on Optimal Q-Learning Fuzzy Energy Controller for FC/SC HEV,ol problems. GA can also be efficient to optimize the new emerging intelligent algorithm. Here, an adaptive fuzzy energy management control strategy (EMS) based on Q-Learning algorithm is presented for the real-time power split between the fuel cell and supercapacitor in the hybrid electric vehicle
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