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Occurrence prediction of cotton pests and diseases by bidirectional long short-term memory networks with climate and atmosphere circulation

文献类型：期刊论文

作者Chen, Peng1,2,3,4; Xiao, Qingxin2,3; Zhang, Jun5; Xie, Chengjun6; Wang, Bing7
刊名COMPUTERS AND ELECTRONICS IN AGRICULTURE
出版日期2020-09-01
卷号176
关键词Occurrence of pests and diseases Climate Atmosphere circulation Pest counting Bi-directional long-short term memory
ISSN号0168-1699
DOI10.1016/j.compag.2020.105612
通讯作者Zhang, Jun() ; Xie, Chengjun(cjxie@iim.acn.cn) ; Wang, Bing(bingwang@ustc.edu)
英文摘要The occurrence of crop pests and diseases always affects the development of agriculture seriously, while pest meteorology showed that climate is important in affecting the occurrence. Recently, recurrent neural network (RNN) has been broadly applied in various fields, which was designed for modeling sequential data and has been testified to be quite efficient in time series problem. This paper proposes to use bi-directional RNN with long short-term memory (LSTM) units for predicting the occurrence of cotton pests and diseases with climate factors. First, the problem of occurrence prediction of pests and diseases is formulated as time series prediction. Then the bi-directional LSTM network (Bi-LSTM) is adopted to solve the problem, which can capture long-term dependencies on the past and future contexts of sequential data. Experimental results showed that Bi-LSTM shows good performance on the occurrence prediction of pests and diseases in cotton fields, and yields an Area Under the Curve (AUC) of 0.95. This work further verified that climate indeed have strong impact on the occurrence of pests and diseases, and circulation parameters also have certain influence.
资助项目National Natural Science Foundation of China[61672035] ; National Natural Science Foundation of China[61872004] ; National Natural Science Foundation of China[U19A2064] ; Educational Commission of Anhui Province[KJ2019ZD05] ; Anhui Province Funds for Excellent Youth Scholars in Colleges[gxyqZD2016068] ; fund of Co-Innovation Center for Information Supply & Assurance Technology in AHU[ADXXBZ201705] ; Anhui Scientific Research Foundation for Returness
WOS研究方向Agriculture ; Computer Science
语种英语
WOS记录号WOS:000612527400001
出版者ELSEVIER SCI LTD
资助机构National Natural Science Foundation of China ; Educational Commission of Anhui Province ; Anhui Province Funds for Excellent Youth Scholars in Colleges ; fund of Co-Innovation Center for Information Supply & Assurance Technology in AHU ; Anhui Scientific Research Foundation for Returness
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/119704]  
专题中国科学院合肥物质科学研究院
通讯作者Zhang, Jun; Xie, Chengjun; Wang, Bing
作者单位1.Anhui Univ, Natl Engn Res Ctr Agroecol Big Data Anal & Applic, Hefei 230601, Anhui, Peoples R China
2.Anhui Univ, Inst Phys Sci, Hefei 230601, Anhui, Peoples R China
3.Anhui Univ, Inst Informat Technol, Hefei 230601, Anhui, Peoples R China
4.Anhui Univ, Sch Internet, Hefei 230039, Anhui, Peoples R China
5.Anhui Univ, Sch Elect Engn & Automat, Hefei 230601, Anhui, Peoples R China
6.Chinese Acad Sci, Inst Intelligent Machines, Hefei 230031, Peoples R China
7.Anhui Univ Technol, Sch Elect & Informat Engn, Maanshan 243032, Anhui, Peoples R China
推荐引用方式
GB/T 7714		 Chen, Peng,Xiao, Qingxin,Zhang, Jun,et al. Occurrence prediction of cotton pests and diseases by bidirectional long short-term memory networks with climate and atmosphere circulation[J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE,2020,176.
APA Chen, Peng,Xiao, Qingxin,Zhang, Jun,Xie, Chengjun,&Wang, Bing.(2020).Occurrence prediction of cotton pests and diseases by bidirectional long short-term memory networks with climate and atmosphere circulation.COMPUTERS AND ELECTRONICS IN AGRICULTURE,176.
MLA Chen, Peng,et al."Occurrence prediction of cotton pests and diseases by bidirectional long short-term memory networks with climate and atmosphere circulation".COMPUTERS AND ELECTRONICS IN AGRICULTURE 176(2020).

入库方式： OAI收割

来源：合肥物质科学研究院

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