scholarly journals Hierarchical Fuzzy Case Based Reasoning with Multi-criteria Decision Making for Financial Applications

Author(s):  
Shanu Sushmita ◽  
Santanu Chaudhury
Author(s):  
Aleksander F Berman ◽  
Galina S Maltugueva ◽  
Aleksander Y Yurin

This paper describes a decision support approach for selecting construction materials in the field of petrochemistry. The correct selection of construction materials is the basis for the provision of durability, long lifetime, and the safety of the designed and upgraded equipment. The proposed hybrid approach is based on the joint application of case-based reasoning and multi-criteria decision-making methods, particularly the aggregation and ranking alternatives nearby the multi-attribute ideal situation (ARAMIS) and aggregation of individual ranking/ complex of aggregation of individual ranking (AIR/CAIR) methods are used. In turn, ARAMIS enables the processing of individual preferences, which are represented in the form of numeric and verbal estimates, and AIR/CAIR is used for processing rankings (strictly or partially ordered sets of alternatives). The primary advantage of this approach is that it considers the experience of previous successful solutions of the materials selection problem, demonstrates the validity of the obtained results using the mathematical theory of multi-criteria decision making and explains the decision making process. The approach is implemented in the form of the expert system. The case model, algorithms, and an illustrative example of application of the proposed approach are also presented.


2019 ◽  
Vol 25 (2) ◽  
pp. 213-235 ◽  
Author(s):  
Soumava Boral ◽  
Sanjay Kumar Chaturvedi ◽  
V.N.A. Naikan

Purpose Usually, the machinery in process plants is exposed to harsh and uncontrolled environmental conditions. Even after taking different types of preventive measures to detect and isolate the faults at the earliest possible opportunity becomes a complex decision-making process that often requires experts’ opinions and judicious decisions. The purpose of this paper is to propose a framework to detect, isolate and to suggest appropriate maintenance tasks for large-scale complex machinery (i.e. gearboxes of steel processing plant) in a simplified and structured manner by utilizing the prior fault histories available with the organization in conjunction with case-based reasoning (CBR) approach. It is also demonstrated that the proposed framework can easily be implemented by using today’s graphical user interface enabled tools such as Microsoft Visual Basic and similar. Design/methodology/approach CBR, an amalgamated domain of artificial intelligence and human cognitive process, has been applied to carry out the task of fault detection and isolation (FDI). Findings The equipment failure history and actions taken along with the pertinent health indicators are sufficient to detect and isolate the existing fault(s) and to suggest proper maintenance actions to minimize associated losses. The complex decision-making process of maintaining such equipment can exploit the principle of CBR and overcome the limitations of the techniques such as artificial neural networks and expert systems. The proposed CBR-based framework is able to provide inference with minimum or even with some missing information to take appropriate actions. This proposed framework would alleviate from the frequent requirement of expert’s interventions and in-depth knowledge of various analysis techniques expected to be known to process engineers. Originality/value The CBR approach has demonstrated its usefulness in many areas of practical applications. The authors perceive its application potentiality to FDI with suggested maintenance actions to alleviate an end-user from the frequent requirement of an expert for diagnosis or inference. The proposed framework can serve as a useful tool/aid to the process engineers to detect and isolate the fault of large-scale complex machinery with suggested actions in a simplified way.


Author(s):  
Yikun Su ◽  
Shijing Yang ◽  
Kangning Liu ◽  
Kaicheng Hua ◽  
Qi Yao

Case-based reasoning (CBR) has been extensively employed in various construction management areas, involving construction cost prediction, duration estimation, risk management, tendering, bidding and procurement. However, there has been a dearth of research integrating CBR with construction safety management for preventing safety accidents. This paper proposes a CBR model which focuses on case retrieval and reuse to provide safety solutions for new problems. It begins with the identification of case problem attribute and solution attribute, the state of hazard is used to describe the problem attribute based on principles of people’s unsafe behavior and objective’s unsafe state. Frame-based knowledge representation method is adopted to establish the case database from dimensions of slot, facet and facet’s value. Besides, cloud graph method is introduced to determine the attribute weight through analyzing the numerical characteristics of expectation value, entropy value and hyper entropy value. Next, thesaurus method is employed to calculate the similarity between cases including word level similarity and sentence level similarity. Principles and procedures have been provided on case revise and case retain. Finally, a real-world case is conducted to illustrate the applicability and effectiveness of the proposed model. Considering the high potential for pre-control and decision-making of construction safety accident, the proposed model is expected to contribute safety managers to take decisions on prevention measures more efficiently.


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