首页 | 本学科首页   官方微博 | 高级检索  
     检索      

集成GASA混合学习策略的BP神经网 络在水稻虫害预测中的应用
引用本文:汪 璇,吕家恪,谢德体,魏朝富.集成GASA混合学习策略的BP神经网 络在水稻虫害预测中的应用[J].中国农学通报,2007,23(4):404-404.
作者姓名:汪 璇  吕家恪  谢德体  魏朝富
作者单位:1. 西南大学计算机与信息科学学院,重庆,400716;重庆市数字农业重点实验室,重庆,400716
2. 重庆市数字农业重点实验室,重庆,400716
基金项目:西南大学校科研和教改项目
摘    要:为改进受多变量、时变和不确定因素影响的作物虫情预测的效率和准确性,以重庆市永川区为研究区域,将1996-2004年的气象和虫害数据分为独立的训练和检验数据集,以研究集成GASA混合学习策略的BP神经网络应用于水稻虫情预测中的可行性。与广泛应用的时间序列分析法和传统BP神经网络相比,集成混合学习策略的BP神经网络预测精度和拟合性能都有了很大提高,因而具有较好的应用前景。

关 键 词:户用沼气技术    户用沼气技术    转化    制约因素    对策
修稿时间:2007-01-252007-01-29

Application of BP Networks Based on GASA Hybrid Strategy to Rices Pests Prediction
Wang Xuan,Lv JiaKe,Xie DeTi,Wei Chaofu.Application of BP Networks Based on GASA Hybrid Strategy to Rices Pests Prediction[J].Chinese Agricultural Science Bulletin,2007,23(4):404-404.
Authors:Wang Xuan  Lv JiaKe  Xie DeTi  Wei Chaofu
Institution:1.College of Computer and Information Science, Southwest University, Chongqing 400716; 2.Key Laboratory of Digital agriculture, Chongqing 400716
Abstract:To improve pests' prediction efficiency and precision, Laifu town of Yongchuan, Chongqing was selected for the study. Local meteorological and pets data from 1996-2004 were divided into training and validation datum sets, Rice prediction applied by GASA-based BPNN was operated. Compared with general used time series and BP Neuron Network prediction, the accuracy achieved by GASA-based BPNN was much better. The potential ability of GASA-based BPNN was also discussed.
Keywords:Artificial neuron network  Genetic Algorithm  Simulated annealing algorithm  Rice pets occurrence level prediction
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《中国农学通报》浏览原始摘要信息
点击此处可从《中国农学通报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号