模糊聚类在砀山酥梨黑星病预测专家系统中的应用

对黑星病的及时、有效预报和防治是保证砀山酥梨正常生长发育,获取高产的重要因素。植物病害的发生发展是一个受众多因素影响的动态系统,其规律复杂多变且经验性强,要想建立因果模型或抽取成传统专家系统中的规则形式表示,在大多数情况下不现实,也不符实,但要举出具体“实例”则要现实、方便的多。同时病虫害预测和防治具有很大程度的模糊性。为此,本文将模糊聚类技术与CBR技术相结合,研制开发了砀山酥梨黑星病预测专家系统。该系统不仅具有模糊推理的性能,而且克服了传统统计建模的缺陷性。

A Dangshan Su Pear Scab Forecasting Expert System Based on Fuzzy Clustering

Timely and effective forecasting for DangShan Su Pear scab is an important factor to ensure normal growth and high output, The production and development of plant disease is a dynamic system influenced by many factors, The regularity of the system is complex and changeful and it assumes strong experience . It is not actual in many cases to set up cause -effect model or express using rule layout like traditional expert system . But it is more realistic to exemplify concrete " examples" . At the same time , Forecasting of plant disease assumes fuzziness to a large extent. So combining CBR with fuzzy clustering , A Dang Shan Su Pear scab forecasting expert system which assumes the property of fuzzy reasoning and gets over the defect of statistic model is developed .