Runoff time series prediction using LSTM dynamic neural network optimized by logistic chaotic mappin...
Runoff time series prediction using LSTM dynamic neural network optimized by logistic chaotic mapping chicken swarm algorithm
About this item
Full title
Author / Creator
Yang, Wenyu , Li, Junfeng , Gu, XueGe , Qu, Wenying , Ma, Chengxiao and Feng, Xueting
Publisher
IWA Publishing
Journal title
Language
English
Formats
Publication information
Publisher
IWA Publishing
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Scope and Contents
Contents
An algorithm, named long short-term memory (LSTM)-logistic chaos mapping chicken swarm algorithm (LCCSA), is proposed for initializing the weights and thresholds of LSTM neural networks using the Logistic chaotic mapping chicken swarm algorithm (CSA). This algorithm aims to improve mid- to long-term runoff sequence prediction in river basins. In th...
Alternative Titles
Full title
Runoff time series prediction using LSTM dynamic neural network optimized by logistic chaotic mapping chicken swarm algorithm
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Author / Creator
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_54fbb3e667cf462daad8632b6ae57912
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_54fbb3e667cf462daad8632b6ae57912
Other Identifiers
ISSN
2040-2244
E-ISSN
2408-9354
DOI
10.2166/wcc.2023.435
