Updating or conditioning a body of evidence modeled within the DS framework plays an important role in most of Artificial Intelligence (AI) applications. Rule is one of the most important methods to represent knowledg...Updating or conditioning a body of evidence modeled within the DS framework plays an important role in most of Artificial Intelligence (AI) applications. Rule is one of the most important methods to represent knowledge in AI. The appearance of uncertain reasoning urges us to measure the belief of rule. Now,most of uncertain reasoning models represent the belief of rule by conditional probability. However,it has many limitations when standard conditional probability is used to measure the belief of expert system rule. In this paper,AI rule is modelled by conditional event and the belief of rule is measured by conditional event probability,then we use random conditional event to construct a new evidence updating method. It can overcome the drawback of the existed methods that the forms of focal sets influence updating result. Some examples are given to illustrate the effectiveness of the proposed method.展开更多
The Middle Jurassic Daohugou Biota has yielded very rich fossil plants, vertebrates, and inver tebrates. The particularly famous fossil insects are represented by at least 24 orders, revealing one of the most diverse ...The Middle Jurassic Daohugou Biota has yielded very rich fossil plants, vertebrates, and inver tebrates. The particularly famous fossil insects are represented by at least 24 orders, revealing one of the most diverse Mesozoic insect communities. Among them, the occurrence of Emhioptera, Mantophasma- todea, and Siphonaptera increased respectively as supported by fossil evidence from Daohugou. Moreover, the early co-evolution of ectoparasites and their hosts may be analyzed by the presence of various giant fleas and the co-occurred potential hosts such as mammals, feather dinosaurs, and pterosaurs from Daohugou.展开更多
基金Supported by the NSFC (No. 60772006, 60874105)the ZJNSF (Y1080422, R106745)Aviation Science Foundation (20070511001)
文摘Updating or conditioning a body of evidence modeled within the DS framework plays an important role in most of Artificial Intelligence (AI) applications. Rule is one of the most important methods to represent knowledge in AI. The appearance of uncertain reasoning urges us to measure the belief of rule. Now,most of uncertain reasoning models represent the belief of rule by conditional probability. However,it has many limitations when standard conditional probability is used to measure the belief of expert system rule. In this paper,AI rule is modelled by conditional event and the belief of rule is measured by conditional event probability,then we use random conditional event to construct a new evidence updating method. It can overcome the drawback of the existed methods that the forms of focal sets influence updating result. Some examples are given to illustrate the effectiveness of the proposed method.
基金supported by the National Basic Research Program of China(2012CB821903)Outstanding Youth Foundation of Jiangsu Province(BK 2012049)the National Natural Science Foundation of China(91114201)
文摘The Middle Jurassic Daohugou Biota has yielded very rich fossil plants, vertebrates, and inver tebrates. The particularly famous fossil insects are represented by at least 24 orders, revealing one of the most diverse Mesozoic insect communities. Among them, the occurrence of Emhioptera, Mantophasma- todea, and Siphonaptera increased respectively as supported by fossil evidence from Daohugou. Moreover, the early co-evolution of ectoparasites and their hosts may be analyzed by the presence of various giant fleas and the co-occurred potential hosts such as mammals, feather dinosaurs, and pterosaurs from Daohugou.
