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Author

Fan Yang

Bio: Fan Yang is an academic researcher from Hubei University. The author has contributed to research in topics: Wait-for graph & Graph (abstract data type). The author has co-authored 2 publications.

Papers
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Journal ArticleDOI
Yi Wang1, Han Ding1, Fan Yang1
TL;DR: A test method for process deadlock based on graph grammars through constructing process resource diagram that can construct and judge the validity of the process resource diagrams and test if there is the deadlock in the process.
Abstract: This paper proposes a test method for process deadlock based on graph grammars through constructing process resource diagram. Through using the construction rules, it can construct and judge the validity of the process resource diagram. Through using the test rules, it can test if there is the deadlock in the process. The method is a graphical approach; it is simple and intuitive with strong operability. DOI : http://dx.doi.org/10.11591/telkomnika.v12i5.4945
Journal ArticleDOI
Yi Wang1, Han Ding1, Fan Yang1
TL;DR: This paper proposed a evaluation method based on neural networks, based on the indexed of the analytic hierarchy process, through using the expert evaluation samples, by the BP neural network to study, so as to get the objective weight of the indexes, and then reflect the real situation of the evaluation objects.
Abstract: In human social life, it is often need to make comprehensive evaluation for person, thing , or a project to carry on the classification or evaluation. Analytic hierarchy process is relatively common and the most simple evaluation model. It draw up a series of evaluation index according to the evaluation object. The index may contain multiple child index, according to the relationship between the indexes or artificial factors to determine tie index weight, and get the overall evaluation for objects. The artificial factor is too much, it can not objectively reflect the real situation of the evaluation object. This paper proposed a evaluation method based on neural networks, based on the indexed of the analytic hierarchy process, through using the expert evaluation samples, by the BP neural network to study, so as to get the objective weight of the indexes, and then reflect the real situation of the evaluation objects.