Browsing by Author "Kao, Han-Ying"

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Decision on enterprise computing solutions for an international tourism
(2007-12-01)
Huang, Chia-Hui
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Kao, Han-Ying
;
Li, Han-Lin
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
This study proposes a multi-objective decision approach for evaluating the enterprise computing solutions in international tourism. We first analyze one tour operator in Thailand as well as its specific requirements for enterprise computations. In the decision processes for enterprise computation, several experts are invited to evaluate the alternatives based on a multi-tier electronic business architecture. This study designs two models for evaluating the information systems investments in international tourism. The first model maximizes the overall utility for each criterion, and the other model maximizes the utility for every expert. Because each alternative for enterprise computation involves approximate costs and efforts, we represent the cost data with fuzzy sets and possibility distributions.
Intelligent decision support based on influence diagrams with rough sets
(2007)
Huang, Chia-Hui
;
Kao, Han-Ying
;
Li, Han-Lin
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Influence diagrams have been widely used as knowledge bases in business and engineering. In conventional influence diagrams, the numerical models of uncertainty are probability distributions associated with chance nodes and value tables for value nodes. However, when imprecise knowledge from large-scaled data set is involved in the systems, the suitability of probability distributions is questioned. This study proposes an alternative numerical model for influence diagrams: rough sets. In the proposed framework, the causal relationships among the nodes and the decision rules are expressed with rough sets from information systems. This study develops rough set-based framework in influence diagrams with an illustrative example.
Knowledge modeling in traditional Chinese medicine with fuzzy influence diagrams
(2008-08-01)
Kao, Han-Ying
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Huang, Chia-Hui
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Kao, Tai-Chi
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Kao, Han-Chung
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交大名義發表
Traditional Chinese medicine (TCM) has been developed for more than four thousand years. It is a complete medical system embracing diagnosis, treatment and prevention. However, the knowledge of TCM is linguistically vague and usually involves subjective judgments, which makes automated inference challenging. This study proposes a novel approach for knowledge modeling in TCM, fuzzy influence diagrams (FID). Considering the subjective knowledge as well as linguistic fuzziness in TCM, possibility distributions are used to model the uncertainty and causal relationships in influence diagrams, which extend the conventional influence diagrams into fuzzy influence diagrams. The FID provides a general platform for answering various queries in TCM, such as prognosis, diagnosis, and optimal treatment. The FID can bridge the qualitative fuzziness and quantitative numerical models in knowledge bases for TCM.