A case‐based reasoning approach for building a decision model

Lee, Jae Kwang; Kim, Jae Kyeong

doi:10.1111/1468-0394.00198

Cited by 18 publications

(8 citation statements)

References 9 publications

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“…For this purpose, the numbers of retrieval results must be as minimum as possible, and the cases searched out will have the highest similarity to target issues. So, the retrieval tactic is very important [3].…”

Section: Algorithm Model For Case Matchingmentioning

confidence: 99%

Study on Transportation Planning System: Based on Case-Based Reasoning

Nie¹,

Pi²,

Zhengwei³

et al. 2015

TOCSJ

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Section: Algorithm Model For Case Matchingmentioning

confidence: 99%

Study on Transportation Planning System: Based on Case-Based Reasoning

Nie¹,

Pi²,

Zhengwei³

et al. 2015

TOCSJ

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“…Based on past mistakes made by some decision makers in an organization, CBR can alert decision makers to avoid repeating past mistakes (Lee & Kim, 2002).…”

Section: Case Based Reasoning (Cbr)mentioning

confidence: 99%

Decision Making for Predictive Maintenance in Asset Information Management

Faiz¹,

Edirisinghe²

2009

IJIKM

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Asset management is a process of identification, design, construction, operation, and maintenance of physical assets (Wenzler, 2005). An asset-centric approach is vital for the success of an asset intensive organisation as the effective management of assets is a major determinant of organisational success. One key issue in asset information management is the availability of information at the right time, in the right format, before the right person, against the right query, and at the right level. This paper provides a comprehensive and in-depth critical analysis from literature which fulfils an identified need of fusing asset information for predictive maintenance so that decision making can be improved. The critical literature review included also highlights the need for an expert system which integrates reliable information with effective decision-support, under the umbrella of Asset Management. Various elements of asset management were critically reviewed, highlighting the need for more robust Predictive maintenance management for assets. We argue that this is best achieved by a system that, in particular, incorporates Expert System to enhance the quality of predictive maintenance through accurate decision analysis. In addition, it should have fuzzy logic reasoning ability that assists in the decision-making process. Our analysis leads us to propose that Expert System when combined with fuzzy logic provides a better way of decision making in predictive maintenance management of assets.

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“…For managing decision knowledge, we adopt the case-based reasoning (CBR) approach (Lee and Kim, 2002). CBR is concerned with supporting new problem solving by using knowledge derived from solving previous problems.…”

Section: Introductionmentioning

confidence: 99%

“…Modern CBR focuses on computerized case-based reasoning using algorithms for case indexing, case retrieval, and case adaptation (Lee and Kim, 2002). In this article we emphasize human case-based reasoning and do not provide details of automation.…”

Section: Introductionmentioning

confidence: 99%

Knowledge management of interconnected decisions with application to project management

Karni

Kaner

2008

Knowl Process Manag

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In this paper we describe a methodology to support decisionmaking in a multiple decision environment using previous experience regarding decisions and their interrelationships. This methodology comprises: (a) new kinds of knowledge which help to better understand the interrelationships between decisions; (b) a human reasoning process incorporating the reuse of past experience in making interrelated decisions; (c) lessons that can be learned or formulated, on the basis of past experience, when current interconnected decisions are to be made. Casebased reasoning (CBR) is used to manage decision knowledge using cases-experience gained from previous decisions. This is complemented by dyad-based reasoning (DBR) to manage the interrelationships between decisions. A dyad is a pair of linked decisions reflecting past experience in making successive decisions. DBR provides a new type of knowledge: the nature and composition of an interconnected set of decisions involving several aspects of a decisionmaking situation. We demonstrate the application of the proposed methodology to a typical example of a multiple decision environment-project management. When a project manager has to make a number of interrelated decisions while carrying out several project management processes, a dyad knowledge base and DBR provide guidance as to the complementary considerations needed to make a multi-faceted set of decisions.

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A case‐based reasoning approach for building a decision model

Cited by 18 publications

References 9 publications

Study on Transportation Planning System: Based on Case-Based Reasoning

Study on Transportation Planning System: Based on Case-Based Reasoning

Decision Making for Predictive Maintenance in Asset Information Management

Knowledge management of interconnected decisions with application to project management

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