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A probabilistic inference method with multiple evidences and its implementation using a layered network

机译:具有多种证据的概率推理方法及其在分层网络中的实现

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The inference method can deal with multiple ambiguous evidences, and can describe effectiveness of evidences and relationships between evidences. Therefore, it is more advantageous than the Dempster-Shafer theory because of its ability to describe relationships between evidences. This method divides the whole world into possible worlds according to element value combinations. The probability of each possible world is decided so as to satisfy constraints corresponding to a priori knowledge and to maximize the entropy of the whole world. Furthermore, the method can be implemented using a layered network. In this network, individual network units do not have to perform complicated operations and connections between the layers are restricted. In other words, this network consists of simple units and restricted connections, thus, high speed processing will be possible using parallel processing.
机译:推理方法可以处理多个模糊的证据,并且可以描述证据的有效性以及证据之间的关系。因此,它比Dempster-Shafer理论更具优势,因为它具有描述证据之间关系的能力。此方法根据元素值组合将整个世界划分为可能的世界。确定每个可能世界的概率,以满足与先验知识相对应的约束,并使整个世界的熵最大化。此外,可以使用分层网络来实现该方法。在该网络中,各个网络单元不必执行复杂的操作,并且各层之间的连接受到限制。换句话说,该网络由简单的单元和受限制的连接组成,因此,使用并行处理可以进行高速处理。

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