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A Fuzzy Cognitive Map‐Based Bi‐Directional Inference Mechanism: An Application to Stock Investment Analysis

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  • KUN CHANG LEE
  • HYUN SOO KIM

Abstract

The objective of this paper is to apply fuzzy cognitive map (FCM)‐related techniques to (1) extract causal knowledge from a specific problem‐domain, (2) construct a hierarchical knowledge base, and (3) perform a bi‐directional inference. The causal knowledge base built by FCM can be described as a matrix form, guaranteeing mathematically compact operation compared with a production (if–then) knowledge base. Based on the causal knowledge base, we can break down a given decision problem into a multi‐leveled one. Then bi‐directional (downward or upward) inference can be applied to the multi‐leveled problem to find a more robust solution. We applied our method to a stock investment analysis problem which is typical of highly unstructured problems in OR/MS fields. © 1997 by John Wiley & Sons, Ltd.

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  • Kun Chang Lee & Hyun Soo Kim, 1997. "A Fuzzy Cognitive Map‐Based Bi‐Directional Inference Mechanism: An Application to Stock Investment Analysis," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 6(1), pages 41-57, March.
    • Handle: RePEc:wly:isacfm:v:6:y:1997:i:1:p:41-57
    DOI: 10.1002/(SICI)1099-1174(199703)6:13.0.CO;2-J
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    Cited by:

    1. Glykas, Michael, 2012. "Performance measurement scenarios with fuzzy cognitive strategic maps," International Journal of Information Management, Elsevier, vol. 32(2), pages 182-195.

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