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Hierarchical fuzzy case based reasoning with multi-criteria decision making for financial applications

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This paper presents a framework for using a case-based reasoning system for stock analysis in financial market using a hierarchical structure for case representation and incorporates a multi-criteria decision-making algorithm which furnishes the most suitable solution with respect to the current market scenario.
Abstract
This paper presents a framework for using a case-based reasoning system for stock analysis in financial market. The unique aspect of this paper is the use of a hierarchical structure for case representation. The system further incorporates a multi-criteria decision-making algorithm which furnishes the most suitable solution with respect to the current market scenario. Two important aspects of financial market are addressed in this paper: stock evaluation and investment planning. CBR and multi-criteria when used in conjunction offer an effective tool for evaluating goodness of a particular stock based on certain factors. The system also suggests a suitable investment plan based on the current assets of a particular investor. Stock evaluation maps to a flat case structure, but investment planning offers a scenario more suited for structuring the case into successive detailed layers of information related to different facets. This naturally leads to a hierarchical case structure.

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Journal ArticleDOI

A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis

TL;DR: This paper proposes a fuzzy ontology-based CBR framework that combines a fuzzy case-base OWL2 ontology, and a fuzzy semantic retrieval algorithm that handles many feature types and achieves an accuracy of 97.67%.
Journal ArticleDOI

Selection and impact of different topologies in multi-layered hierarchical fuzzy systems

TL;DR: An evolutionary algorithm based approach for selection of topologies in hierarchical fuzzy systems (HFS) is presented and Coupling fuzzy system with evolutionary algorithm provides a solution to the automated acquisition of the fuzzy rule base.
Journal ArticleDOI

A hybrid algorithm of improved case-based reasoning and multi-attribute decision making in fuzzy environment for investment loan evaluation

TL;DR: A model to support the banking managerial decisions in the evaluation of investment plans, especially on rejecting inappropriate plans that can be done in short time (less than hour) and with minimal cost is presented.
Journal ArticleDOI

A case-base fuzzification process: diabetes diagnosis case study

TL;DR: A case-base preparation framework for CBR systems, which converts the electronic health record medical data into fuzzy CBR knowledge, which enhances the representation of case- base knowledge, the performance of retrieval algorithms, and the querying capabilities ofCBR systems.
Journal ArticleDOI

Using mutually validated memories of experts for case-based knowledge systems

TL;DR: The proposed framework, integrating fuzzy linguistic GDM and CBR, thus enhances the efficiency and effectiveness of a CBR system and provides a powerful methodology for performance ranking.
References
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Proceedings Article

Time series extrapolation using hierarchical case-based reasoning

TL;DR: It is shown how the idea of hierarchical case-based reasoning is involved within the context of time series similarity assessment, and several key issues in CBR are discussed.
Book ChapterDOI

Case-Based Reasoning: An Intelligent Approach Applied for Financial Crises Warning

TL;DR: Three critical techniques of CBR are studied intensively, namely: knowledge representation, re-trieval of similar cases and case learning, and an implementation of the Case-based Financial Crises Warning Prototype System is described in summary.
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