基于证据可信度不确定推理的大豆病害诊断方法
针对大豆病害专家系统中诊断特征条件的复杂性和不确定性等问题,将病害证据可信度和不确定性推理的传递算法有机结合,提出了一种基于证据可信度不确定推理的大豆病害诊断方法。由植保知识库的专家先验知识和作物病害发生时期、部位和症状等表现特征,构成可信度权重作为推理依据;利用该文提出的基于证据可信度的不确定推理方法及推理规则,实现了大豆病害的自动诊断与决策。应用实践表明：该方法简单、可靠、易于实现,对大豆病害的诊断准确率达到87.62%,为植物病害的智能远程诊断和科学管理提供了一种高效的新途径。...
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| Published in | 农业工程学报 Vol. 29; no. 1; pp. 109 - 114 |
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| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
黑龙江八一农垦大学信息技术学院,大庆 163319%中国农业大学信息与电气工程学院,北京 100083
2013
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| Subjects | |
| Online Access | Get full text |
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| Summary: | 针对大豆病害专家系统中诊断特征条件的复杂性和不确定性等问题,将病害证据可信度和不确定性推理的传递算法有机结合,提出了一种基于证据可信度不确定推理的大豆病害诊断方法。由植保知识库的专家先验知识和作物病害发生时期、部位和症状等表现特征,构成可信度权重作为推理依据;利用该文提出的基于证据可信度的不确定推理方法及推理规则,实现了大豆病害的自动诊断与决策。应用实践表明：该方法简单、可靠、易于实现,对大豆病害的诊断准确率达到87.62%,为植物病害的智能远程诊断和科学管理提供了一种高效的新途径。 |
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| Bibliography: | 11-2047/S Soybean diseases are the important factors for restricting high-yield, high-quality, and high efficiency of sustainable agriculture, so soybean diseases should been diagnosed timely and accurately for intelligent agriculture. But the widely used traditional visual diagnostic methods could not meet the agricultural producers’ request of timely, because the high degree of subjective factors made it time-consuming and inaccurate. So it is very important to develop the intelligent disease diagnosis system. In this paper, we present a diagnostic method of soybean diseases based on uncertain reasoning of evidence credibility, which is combined evidence theory and uncertainty pass algorithm of credibility to overcome the complexity and uncertainty of the characteristic conditions for soybean disease expert system. In this paper, soybean diseases were set for study objects, and the automatic diagnosis model of soybean has been established through expression of credibility of knowledge for diseases of evidenc |
| ISSN: | 1002-6819 |
| DOI: | 10.3969/j.issn.1002-6819.2013.z1.016 |