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Application of Dueling DQN and DECGA for Parameter Estimation in Variogram Models

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成果类型:
期刊论文
作者:
Liu, Yu;Zhang, Cong*
通讯作者:
Zhang, Cong
作者机构:
[Liu, Yu; Zhang, Cong] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Peoples R China.
通讯机构:
[Zhang, Cong] W
Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Peoples R China.
语种:
英文
关键词:
Mathematical model;Parameter estimation;Genetic algorithms;Computational modeling;Correlation;Convergence;Analytical models;Parameter estimation;variogram;variogram models;dueling DQN;DECGA
期刊:
IEEE ACCESS
ISSN:
2169-3536
年:
2020
卷:
8
页码:
38112-38122
基金类别:
This work was supported in part by the Hubei Provincial Major Science and Technology Special Projects under Grant 2018ABA099, in part by the Natural Science Foundation of Hubei Province under Grant 2015CFA061 and Grant 2018CFB408, in part by the National Natural Science Foundation of China under Grant 61272278, and in part by the Wuhan Polytechnic University Talent Introduction (Training) Scientific Research Project under Grant 2019RZ02.
机构署名:
本校为第一且通讯机构
院系归属:
数学与计算机学院
摘要:
Parameter estimation of variogram models is an important problem in geostatistics and environmental engineering. Most of existing works aim to estimate parameters of variogram single models, while neglecting the parameter estimation of variogram nested model. Most recently, the evolutionary algorithms(EA), including genetic algorithm(GA), are exploited to calculate the parameters of variogram model, which can obtain a more accurate solution. These methods have some hyper-parameters to set and suffer from the well-recognized premature convergence and slow global convergence problem of EA. In th...

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