WEB-Based Intelligent Diagnosis System for Cotton Diseases Control

Abstract : Diseases control is always an issue in cotton production, the timely detection and effective control of diseases depend on, in most cases, an effective diagnosis system. Based on the distribution of cotton diseases in the main yielding areas of China in recent years, the main species and characters of cotton diseases were listed classified in the study and a database was established for this purpose. BP neural network as a decision-making system was used to establish an intelligent diagnosis model. Based on the model, a WEB-based Intelligent Diagnosis System for Cotton Diseases Control was developed. An experiment scheme was designed for the system test, in which 80 samples, including 8 main species of diseases, 10 samples in each sort were included. The result showed the rate of correctness that system could identify the symptom was 89.5% in average, and the average running time for a diagnosis was 900ms.
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Communication dans un congrès
Daoliang Li; Yande Liu; Yingyi Chen. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. Springer, IFIP Advances in Information and Communication Technology, AICT-346 (Part III), pp.483-490, 2011, Computer and Computing Technologies in Agriculture IV. 〈10.1007/978-3-642-18354-6_57〉
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Hui Li, Ronghua Ji, Jianhua Zhang, Xue Yuan, Kaiqun Hu, et al.. WEB-Based Intelligent Diagnosis System for Cotton Diseases Control. Daoliang Li; Yande Liu; Yingyi Chen. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. Springer, IFIP Advances in Information and Communication Technology, AICT-346 (Part III), pp.483-490, 2011, Computer and Computing Technologies in Agriculture IV. 〈10.1007/978-3-642-18354-6_57〉. 〈hal-01563443〉

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