基于案例推理的砀山酥梨黑星病预测系统研究
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摘要
砀山酥梨栽培历史悠久，是安徽省乃至全国的名优品种。在黄河故道地区的砀山酥梨产区，为害酥梨的病害有十多种，其中最关键的是梨黑星病（Venturia nashicola Tanaka et Yamamoto），如果预防不及时，常造成流行或大暴发，导致生产上的重大损失。因此，梨黑星病防治就成为砀山酥梨病害防治的重中之重，而对其准确预测预报是进行有效防治的基础与前提。
本研究依据黄河故道地区砀山酥梨病害测报资料及气象等相关生态因子资料，研制开发了砀山酥梨黑星病预测专家系统。使病害的预测完全交由计算机处理，提高预测的正确率。为砀山酥梨黑星病的预测预报提供一条新的具有前景的途径。
本研究采用的主要技术有基于案例的推理（Case-Based Reasoning, CBR）和模糊ISODATA聚类。CBR是一种基于过去求解类似问题的经验来获得当前问题求解结果的一种新型专家系统推理模式，其应用案例来表示以前黑星病的发生情况，知识获取和表示自然直接，克服了传统的基于规则推理的专家系统中知识获取的“瓶颈”问题，而且系统可以将每次解决的典型的问题作为一个新的案例存储于案例库中，不断地对案例库进行更新，系统的效率也会不断地得到提高。模糊ISODATA聚类是一种是基于模糊划分的思想，利用迭代方法，在泛函极值意义下，不断修正聚类中心的局部优化算法。本研究将模糊ISODATA聚类技术与CBR技术相结合，实现CBR在案例检索时的模糊不精确匹配推理，较好地仿真专家经验推理。
本研究的CBR梨黑星病预测系统采用面向对象的VB编程设计实现。系统利用Access数据库来建立酥梨黑星病案例库；通过VB与Access数据库技术实现砀山酥梨黑星病案例库维护部分以及系统的预测部分等。人机交互界面友好，可视化的操作简单易学。将酥梨黑星病的实测数据与预测数据进行相关性统计分析，表明用该系统来预测酥梨的黑星病发生趋势是有效的。
Dangshansu pear has a long cultivation history and it is a good breed around the world. At Dangshansu pear planting district in the area of Yellow River valley, There are many kinds of diseases that harm Dangshansu pear, and the most serious disease is pear scab. If it is not prevented timely, this disease often endangers serious incidence and causes great loss. So the prevention against pear scab is the most important among all diseases, and accurate forecasting is the foundation to take valid prevention.
In this research, based on the pear diseases’ observations and weather data in the area of the Yellow River valley, we developed the forecasting system for Dangshansu pear scab, which had improved the forecasting accuracy and depended fully on computer. The system provided a new and perspective forecasting approach for the Dangshansu pear scab.
The main used technologies were CBR and Fuzzy ISODATA clustering in this research. CBR is a modern expert system reasoning mode based on obtaining the problem’s solution from the past experiences of solving the similar problems. Case was used to represent the past occurrence circumstance of pear scab, and knowledge acquisition and representation were natural and direct, which had overcome the bottleneck question of knowledge acquisition in the traditional RBR system. Moreover, the solved typical problem could be considered as a new case and retained in the casebase, which could get further updating. At the same time, the efficiency of the system can also get enhancement. Fuzzy ISODATA clustering is a local optimal algorithm which revises the center of the clustering unceasingly based on the extreme value of panto-function. It is based on the thought of the fuzzy partition and the iterating method. This study combined Fuzzy ISODATA clustering technology with CBR and realized the fuzzy imprecise matching reasoning in case retrieval, which emulates the reasoning of the expert experience.
The forecasting system for Dangshansu pear scab was realized by VB, which is an object-oriented programming. Access was used to establish the scab casebase. The system used VB and Access to realize the maintenance of casebase and the forecasting. The interface of the system was friendly and the visual operation process was very simple to learn. Relativity statistical analysis was conducted between the real data and the forecasting data of Dangshansu pear scab, which showed the system was valid to forecast the occurrence tendency of Dangshansu pear scab.
本研究依据黄河故道地区砀山酥梨病害测报资料及气象等相关生态因子资料，研制开发了砀山酥梨黑星病预测专家系统。使病害的预测完全交由计算机处理，提高预测的正确率。为砀山酥梨黑星病的预测预报提供一条新的具有前景的途径。
本研究采用的主要技术有基于案例的推理（Case-Based Reasoning, CBR）和模糊ISODATA聚类。CBR是一种基于过去求解类似问题的经验来获得当前问题求解结果的一种新型专家系统推理模式，其应用案例来表示以前黑星病的发生情况，知识获取和表示自然直接，克服了传统的基于规则推理的专家系统中知识获取的“瓶颈”问题，而且系统可以将每次解决的典型的问题作为一个新的案例存储于案例库中，不断地对案例库进行更新，系统的效率也会不断地得到提高。模糊ISODATA聚类是一种是基于模糊划分的思想，利用迭代方法，在泛函极值意义下，不断修正聚类中心的局部优化算法。本研究将模糊ISODATA聚类技术与CBR技术相结合，实现CBR在案例检索时的模糊不精确匹配推理，较好地仿真专家经验推理。
本研究的CBR梨黑星病预测系统采用面向对象的VB编程设计实现。系统利用Access数据库来建立酥梨黑星病案例库；通过VB与Access数据库技术实现砀山酥梨黑星病案例库维护部分以及系统的预测部分等。人机交互界面友好，可视化的操作简单易学。将酥梨黑星病的实测数据与预测数据进行相关性统计分析，表明用该系统来预测酥梨的黑星病发生趋势是有效的。
Dangshansu pear has a long cultivation history and it is a good breed around the world. At Dangshansu pear planting district in the area of Yellow River valley, There are many kinds of diseases that harm Dangshansu pear, and the most serious disease is pear scab. If it is not prevented timely, this disease often endangers serious incidence and causes great loss. So the prevention against pear scab is the most important among all diseases, and accurate forecasting is the foundation to take valid prevention.
In this research, based on the pear diseases’ observations and weather data in the area of the Yellow River valley, we developed the forecasting system for Dangshansu pear scab, which had improved the forecasting accuracy and depended fully on computer. The system provided a new and perspective forecasting approach for the Dangshansu pear scab.
The main used technologies were CBR and Fuzzy ISODATA clustering in this research. CBR is a modern expert system reasoning mode based on obtaining the problem’s solution from the past experiences of solving the similar problems. Case was used to represent the past occurrence circumstance of pear scab, and knowledge acquisition and representation were natural and direct, which had overcome the bottleneck question of knowledge acquisition in the traditional RBR system. Moreover, the solved typical problem could be considered as a new case and retained in the casebase, which could get further updating. At the same time, the efficiency of the system can also get enhancement. Fuzzy ISODATA clustering is a local optimal algorithm which revises the center of the clustering unceasingly based on the extreme value of panto-function. It is based on the thought of the fuzzy partition and the iterating method. This study combined Fuzzy ISODATA clustering technology with CBR and realized the fuzzy imprecise matching reasoning in case retrieval, which emulates the reasoning of the expert experience.
The forecasting system for Dangshansu pear scab was realized by VB, which is an object-oriented programming. Access was used to establish the scab casebase. The system used VB and Access to realize the maintenance of casebase and the forecasting. The interface of the system was friendly and the visual operation process was very simple to learn. Relativity statistical analysis was conducted between the real data and the forecasting data of Dangshansu pear scab, which showed the system was valid to forecast the occurrence tendency of Dangshansu pear scab.
引文
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