• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.474-483
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• 2003

A number of studies for corporate bond rating classification problems have demonstrated that artificial intelligence approaches such as Case-based reasoning (CBR) can be alternative methodologies to statistical techniques. CBR is a problem solving technique in that the case specific knowledge of past experience is utilized to find a most similar solution to the new problems. To build a successful CBR system to deal with human information processing, the representation of knowledge of each attribute is an important key factor We propose a hybrid approach of using fuzzy sets that describe the approximate phenomena of the real world because it handles inexact knowledge represented by common linguistic terms in a similar way as human reasoning compared to the other existing techniques. Integration of fuzzy sets with CBR is important to develop effective methods for dealing with vague and incomplete knowledge to statistical represent using membership value of fuzzy sets in CBR.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1693-1705
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• 2013

To restore old aqueduct in Korea which is a irrigation bridge to supply water in paddy field area, it is needed to estimate approximate costs of restoration because the basic design for estimation of construction costs is often ruled out in current system. In this paper, estimating models of construction costs were developed on the basis of performance data for restoration of RC aqueduct bridges since 2003. The regression analysis (RA) model and case-based reasoning (CBR) model for the estimation of construction costs were developed respectively. Error rate of simple RA model was lower than that of multiple RA model. CBR model using genetic algorithm (GA) has been applied in the estimation of construction costs. In the model three factors like attribute weight, attribute deviation and rank of case similarity were optimized. Especially, error rate of estimated construction costs decreased since limit ranges of the attribute weights were applied. The results showed that error rates between RA model and CBR models were inconsiderable statistically. It is expected that the proposed estimating method of approximate costs of aqueduct restoration will be utilized to support quick decision making in phased rehabilitation project.

• The Transactions of the Korea Information Processing Society
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• v.5 no.4
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• pp.951-958
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• 1998

In this paper, we propose a backward reasoning algorithm which can be utilized in the fuzzy Petri-net representation representing fuzzy production rules. The fuzzy Petri-net representation can be used to model a approximate reasoning system and implement a fuzzy inference engine. The proposed algorithm, which uses the proper belief evaluation functions according to fuzzy concepts in antecedentes and consequents of fuzzy production rules, is more closer to human intuition and reasoning than other methods. This algorithm generates the backward reasoning path from the goal to the initial nodes and evaluates the belief value of the goal node using belief evaluation functions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.343-346
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• 1998

This paper deals with the decision in vague knowledge, One method is a classic theory. That is to say, constraints and goals in the vague knowledge. Another method is the fuzzy catastrophe. If there exist two fuzzy variables, there may be a discontinuity which plays an important role in decision.

• Journal of applied mathematics & informatics
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• v.37 no.3_4
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• pp.201-205
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• 2019

This note provides the solution equivalence of general minimum variance and minimax disparity problems for OWA operator. This result generalize a main theorem of Liu [International Journal of Approximate Reasoning, 48 (2008) 598-627.]

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1242-1247
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• 2009

The sudden changes in the construction market and the progressively intensifying price wars have amplified the importance of the construction cost estimation in the initial and planning phases of construction projects. However the methodologies and process of estimating construction cost in the planning and design phase are not standardized in the domestic market, in contrast to the markets of more developed countries. Therefore this paper proposes a new approximate estimation model to be used from the initial stages of construction projects. This methodology that extracts, modifies and synthesizes comparable elements of previous cases. This will introduce the foundation for the implementation of systems with improved usability and applicability.

• Computers and Concrete
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• v.15 no.1
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• pp.89-101
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• 2015

In this paper, Artificial Neural Networks (ANN) and Multiple Linear Regression (MLR) models were discussed to determine the compressive strength of clinker mortars cured for 1, 2, 7 and 28 days. In the experimental stage, 1288 mortar samples were produced from 322 different clinker specimens and compressive strength tests were performed on these samples. Chemical properties of the clinker samples were also determined. In the modeling stage, these experimental results were used to construct the models. In the models tricalcium silicate ($C_3S$), dicalcium silicate ($C_2S$), tricalcium aluminate ($C_3A$), tetracalcium alumina ferrite ($C_4AF$), blaine values, specific gravity and age of samples were used as inputs and the compressive strength of clinker samples was used as output. The approximate reasoning ability of the models compared using some statistical parameters. As a result, ANN has shown satisfying relation with experimental results and suggests an alternative approach to evaluate compressive strength estimation of clinker mortars using related inputs. Furthermore MLR model showed a poor ability to predict.

• The Journal of Information Systems
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• v.8 no.1
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• pp.27-44
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• 1999

Case-Based Reasoning(CBR) offers a new approach for developing knowledge based systems. CBR has several research issues which can be divided into two categories : (1) static issues and (2) dynamic issues. The static issues are related to case representation scheme and case data model, that is, focus on casebase which is a repository of cases. The dynamic issues, on the other hand, are related to case retrieval procedure and problem solving process, i.e. case adaptation phase. This research is forcused on retrieval procedure Traditional query processing accepts precisely specified queries and only provides exact answers, thus requiring users to fully understand the problem domain and the casebase schema, but returning limited or even null information if the exact answer is not available. To remedy such a restriction, extending the classical notion of query answering to approximate query answering(AQA) has been explored. AQA can be achieved by neighborhood query answering or associative query answering. In this paper, neighborhood query answering technique is used for AQA. To reinforce the CBR process, a new retrieval procedure(cooperative CBR) using neighborhood query answering is proposed. An neighborhood query answering relaxes a query scope to enlarge the search range, or relaxes an answer scope to include additional information. Computer Aided Process Planning(CAPP) is selected as cooperative CBR application domain for test. CAPP is an essential key for achieving CIM. It is the bridge between CAD and CAM and translates the design information into manufacturing instructions. As a result of the test, it is approved that the problem solving ability of cooperative CBR is improved by relaxation technique.

• Korean Journal of Construction Engineering and Management
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• v.14 no.6
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• pp.14-21
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• 2013

While a detailed cost estimation utilizes the comprehensive quantity information obtained from a complete drawing and specification, an approximate cost estimation heavily relies on the subjective decisions. This phenomenon is because the approximate estimation is usually conducted in early stage of the construction phase where the drawing and specification are not available. This study developed a roadway construction cost estimation system which enables users to estimate the approximated cost of the project in early stage. The system identifies the variation of the construction costs due to the road route change using a cased based reasoning(CBR) method. Overall the system is expected to improves the accuracy and effectiveness of the estimation process, because it would provide users with increased accessability and consistent results in early stage of the project which leaded to the increased work transparency.

• Journal of the Korean Society of Mechanical Technology
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• v.13 no.2
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• pp.9-19
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• 2011

Most real world design evaluation and risk-based decision support combine quantitative and qualitative (linguistic) variables. Decision making based on conventional mathematics that combines qualitative and quantitative concepts always exhibit difficulty in modelling actual problems. The successful selection process for choosing a design/procurement proposal is based on a high degree of technical integrity, safety levels and low costs in construction, corrective measures, maintenance, operation, inspection and preventive measures. In this paper, a design decision support framework using a composite structure methodology grounded in approximate reasoning approach and evidential reasoning method is suggested for design evaluation of machinery space of a ship engine room at the initial stages. An illustrative example is used to demonstrate the application of the proposed framework.