Case-Based Reasoning Module for Intelligent Decision Support Systems

In this paper, actual issues of improving the efficiency of solution search systems based on precedents -Case-Based Reasoning Systems (CBR systems) are considered. To improve the efficiency of CBR systems and accelerate the search for solutions, it is proposed to use a modified CBR cycle, which allows to create a base of successful and unsuccessful precedents and reducing the number of precedents in the database of successful and unsuccessful precedents through the use of classification and clustering methods.

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“…It is proposed to retrieve and determine the similarity of the case and the current situation in two stages [9]:…”

Section: Methods Of Case Retrievalmentioning

confidence: 99%

Improving the Efficiency of Solution Search Systems Based on Precedents

Eremeev

Varshavskiy

Alekhin

2018

Advances in Intelligent Systems and Computing

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“…Artificial intelligence has already been proposed for the assistance in fault diagnosis for industry [7,8] and specifically in the nuclear field [9,10]. Cases of success such as that shown by Yang and Mou [11] extend the interest of research in this field and manifests the promising derivations of their applications to new fields like tritium and fusion.…”

Section: Introductionmentioning

confidence: 99%