基于T-S模糊神经网络的农业干旱评估与预测模型  

Evaluation and Prediction Model of Agricultural Drought Based on T-S Fuzzy Neural Network

作　　者：沈桂芳[1] 李敬明[1,2] 胡贤德[1] 陈秀明[1,2] 

机构地区：[1]安徽新华学院 [2]合肥工业大学

出　　处：《哈尔滨师范大学自然科学学报》2016年第6期34-37,共4页Natural Science Journal of Harbin Normal University

基　　金：安徽省教育厅自然科学研究重点项目(KJ2016A308;KJ20165A300);校级自然科学项目(2014zr019)

摘　　要：为了能够更加准确的对干旱等级进行评估与预测,提出一种基于神经模糊推理系统的旱情评估与预测模型,分析了影响农业干旱灾害的因素,探讨了T-S模糊模型建立的原理及算法步骤.并以蚌埠、亳州、宿州三个地区的干旱灾害历史数据作为实验仿真依据,实验结果表明了该模型的有效性和可行性,为农业干旱灾害评估与预测提供了一种科学的方法.In order to be more accurate assessment and prediction of the drought level, a drought assessment and prediction model of neural network based fuzzy inference system is proposed. The influence factors of agricultural drought disaster are analyzed, the principle and algorithm of T - S fuzzy step model are discussed. Aeeording to historical data of Bengbu, Bozhou, Suzhou three areas as the experimental basis for simulation, the experimental results show the effectiveness and feasibility of the model, which provides a new scientific method for the agricultural drought disaster assessment and prediction.

关 键 词：农业干旱评估与预测 模糊神经网络 T-S模糊系统 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]