Forecasting the Catch Data of E.sinensis by Applying Continuous Time Markov Approach

The forecast model for catch data of E.sinensis was built by using continuous time Markov approach, combining with optimization method (0.618) based on of catch data of E.sinensis in Yangtze River estuary from 1970∼2012. And a forecast on the catch data of E.sinensis in 2013 was made in this paper....

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Published inIOP conference series. Materials Science and Engineering Vol. 394; no. 5; pp. 52006 - 52013
Main Authors Feng, Guangpeng, Li, Yanhua, Wu, Bin, Ma, Benhe, Hu, Huogen, Wang, Haihua
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.07.2018
Subjects
Estuaries
Optimization
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Abstract The forecast model for catch data of E.sinensis was built by using continuous time Markov approach, combining with optimization method (0.618) based on of catch data of E.sinensis in Yangtze River estuary from 1970∼2012. And a forecast on the catch data of E.sinensis in 2013 was made in this paper. The result showed that the forecast was corresponded to the catch data accurately and provides a new method for the prediction of crab resources.
AbstractList The forecast model for catch data of E.sinensis was built by using continuous time Markov approach, combining with optimization method (0.618) based on of catch data of E.sinensis in Yangtze River estuary from 1970∼2012. And a forecast on the catch data of E.sinensis in 2013 was made in this paper. The result showed that the forecast was corresponded to the catch data accurately and provides a new method for the prediction of crab resources.
Author Li, Yanhua
Hu, Huogen
Wu, Bin
Wang, Haihua
Feng, Guangpeng
Ma, Benhe
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Cites_doi 10.2307/3543591
10.2307/3543586
10.1111/j.1365-2338.1977.tb02736.x
10.1016/0304-3800(85)90052-3
10.2307/3543600
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Snippet The forecast model for catch data of E.sinensis was built by using continuous time Markov approach, combining with optimization method (0.618) based on of...
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SubjectTerms Estuaries
Optimization
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Title Forecasting the Catch Data of E.sinensis by Applying Continuous Time Markov Approach
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