Optimal Design and Performance Analysis of Thermoelectric Power Generation Device Based on Multi‐Objective Genetic Algorithm

2021 ◽  
pp. 2000271
Author(s):  
Jinmeng Wu ◽  
Yan Chen ◽  
Yinke Dou ◽  
Chunyan Ma ◽  
Qian Du ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Power Generation ◽  
Optimal Design ◽  
Performance Analysis ◽  
Thermoelectric Power ◽  
Thermoelectric Power Generation ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Power Generation Device ◽  
And Performance

Research on a Multi-Objective Genetic Algorithm for Rational Agent Learning Model

2011 ◽  
Vol 58-60 ◽  
pp. 1232-1239
Author(s):  
Ming Li ◽  
Zhen Hong Xiao ◽  
Zan Fu Xie ◽  
Xiao Yun Mo
Keyword(s):  
Genetic Algorithm ◽  
Global Convergence ◽  
Dynamic Environment ◽  
Learning Model ◽  
Dynamic Learning ◽  
Learning Capability ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Wide Perspective ◽  
And Performance

As a software component which is capable of learning in an autonomous way, software agent should have the capability of learning in a dynamic environment. Genetic Algorithm has a wide perspective in the machine learning because of its unique characteristic (e.g. dynamic adaptability, self-organization, global convergence and robustness). But when applying GA to agent’s dynamic learning model, it encounters a series of problem. In this paper, a Modifided Multi-Objective Genetic Algorithm(MMOGA) will be introduced to solve these problems. Finally, an Agent’s Dynamic learning model based on a MMOGA which has the flexible dynamic learning capability, better global convergence and performance, will be introduced.

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