TY - GEN
T1 - WEB-based intelligent diagnosis system for cotton diseases control
AU - Li, Hui
AU - Ji, Ronghua
AU - ZHANG, Jianhua
AU - Yuan, Xue
AU - Hu, Kaiqun
AU - Qi, Lijun
N1 - Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
KW - Cotton
KW - Diseases
KW - Intelligent Diagnosis System
UR - http://www.scopus.com/inward/record.url?scp=79951614621&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-18354-6_57
DO - 10.1007/978-3-642-18354-6_57
M3 - Conference proceeding
AN - SCOPUS:79951614621
SN - 9783642183539
T3 - IFIP Advances in Information and Communication Technology
SP - 483
EP - 490
BT - Computer and Computing Technologies in Agriculture IV - 4th IFIP TC 12 Conference, CCTA 2010, Selected Papers
T2 - 4th IFIP International Conference on Computer and Computing Technologies in Agriculture and the 4th Symposium on Development of Rural Information, CCTA 2010
Y2 - 22 October 2010 through 25 October 2010
ER -