摘要
针对虫情预测的模糊性、相关性、非线性、实时性等特点,以及神经网络在小样本预测时泛化能力降低的问题,提出了一种基于模糊聚类的神经网络农作物虫情预测方法。仿真结果表明,该方法简单实用,能快速、准确预测虫情,特别在样本少及样本相关性较大的情况下,能取得较好效果。
Aimed to the characters of post forecast such as fuzziness, correlation, nonlinear and real-time as well as decline of generalization capacity of neural network in prediction with few observations, a method of pests forecasting using the method of neural network based on fuzzy clustering was proposed in this experiment. The simulation results demonstrated that the method was simple and practical and could forecast posts fast and accurately, particularly, the method could obtain good results with few samples and big samples correlation.
出处
《安徽农业科学》
CAS
北大核心
2009年第21期10047-10049,共3页
Journal of Anhui Agricultural Sciences
基金
广西科学研究与技术开发计划项目(桂科攻0815001-10)
关键词
神经网络
模糊聚类
虫情
预测
Neural network
Fuzzy clustering i Pest
Forecasting
