Automating Knowledge Acquisition and Refinement for Decision Support: A Connectionist Inductive Inference Model
作者： Pi-Sheng Deng
DOI: 10.1111/J.1540-5915.1993.TB00479.X
关键词: Intelligent decision support system 、 Artificial intelligence 、 Machine learning 、 Computer science 、 Influence diagram 、 Decision support system 、 Expert system 、 Knowledge base 、 Knowledge acquisition 、 Decision engineering 、 R-CAST 、 Management of Technology and Innovation 、 Strategy and Management 、 General Business, Management and Accounting 、 Information Systems and Management
摘要: An important application of expert systems technology is to provide support for nonstructured decision making. Usually, making characterized by heavy reliance on heuristic knowledge, which very difficult articulate or document, and therefore traditional knowledge acquisition approaches are not successful. The quality effectiveness an system supporting unstructured affected when used. To alleviate this problem a model proposed that combines inductive inference neural network computing, example presented illustrates the potential in support.
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