• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.787-790
• /
• 1997

This paper proposes a method which selects essential elements in a human evaluation model using the Choquet integral based on fuzzy measures, and applies the model to the evaluation of human interface. Three kinds of concepts are defined to select essential elements. Increment Degree implies the increment degree from fuzzy measures of composed elements to the fuzzy measure of a combined element. Average of Increment Degree of an element means the relative possibility of superadditivity of the fuzzy measure of each combined element. Necessity Degree means the selection degree of each combined element as a result of the human evaluation. A task experiment, which consists of a static work and two dynamic works, is performed by the use of some human interfaces. In the experiment, (1) a warning sound which gives an attention to subjects, (2) a color vision which can be distinguished easily or not, (3) the size of working area and (4) a response of confirmation that is given from an interface, are considered as human interface elements. Subjects answer the questionnaire after the experiment. From the data of the questionnaire, fuzzy measures are identified and are applied to the proposed model. Effectiveness of the proposed model is confirmed by the comparison of human interface elements extracted from the proposed model and those from the questionnaire.

• Journal of Korean Port Research
• /
• v.12 no.1
• /
• pp.9-17
• /
• 1998

The evaluation structure of complex problems is composed of multi-attributes and hierarchy. A many studies were existed on this problems, but that based on the assumption that the evaluation elements were independent. The actual evaluation problems have the complexity, ambiguity and interlinkage among the elements. In this situation, the fuzzy evaluation process is very effective in settling the complex problems. For evaluation of large scale hierarchical MADM problem, the fuzzy evaluation algorithm is developed in this paper, and that is centering on the identification of fuzzy measures. In this study, we newly identified the weight and interaction among the evaluation attributes. The results of this study are as follows: we can identified the hierarchical structure of the evaluation problem which is composed of the evaluation structure, function and hierarchy; we improved the existed weighting method which could be accomplished by normalizing process, considering the uncertainty and new weight integrating method which come from Dempster-Shafer theory. And we take into account the interaction properties among more than 3 evaluation attributes, which can be compared with the existed studies in which only 2 evaluation attributes taked into account.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.8 no.2
• /
• pp.87-93
• /
• 2008

In this paper, we propose a hierarchical fuzzy based nutrition evaluation system that can analyze the individuals' nutrition status through the inference results generated by each layer. Moreover, a method to minimize the uncertainty of inference in the evaluated nutrition status is discussed. To show the effect of the uncertainty in fuzzy inference, we compared the results of nutrition evaluation with/without the certainty factor of rules on 132 people over the age of 65. From the experimental results, we can see that the evaluation method with the modified certainty factor provides better reliability than that of the general evaluation method without the certainty factor.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.21 no.45
• /
• pp.11-23
• /
• 1998

This paper presents a more efficient evaluation of alternatives by use of multi-criteria decision making methodlogy under fuzzy intersectional dependence relations. The performance evaluation of most systems such as weapons, enterprise systems etc. are multiple criteria decision making problems. The descriptions and judgements on these systems are usually linguistic and fuzzy. The traditional methods of Analytic Hierarchy Process(AHP) are mainly used in crisp(non-fuzzy) decision applications with a very unbalanced scale of judgements and rank reversal. To overcome these problems, we will propose a new, general decision making method for evaluation models using fuzzy AHP(FAHP) under fuzzy intersectional dependence relations. The T.M.S alternatives A, B and C will be evaluted by the Fuzzy Analytic Hierachy Process (FAHP) based on entropy weight in this study. We will use symmetric triangular fuzzy numbers to indicate the relative strength of the elements in the hierachy and degree of intersection between criteria. These problems are evaluated by five criteria : tactical criteria, technology criteria, maintenance criteria, economy criteria, advacement criteria.

• IE interfaces
• /
• v.17 no.2
• /
• pp.169-179
• /
• 2004

In supply chain management, supplier capacity is very important to meet the customer demand quickly. This paper studies a supplier evaluation structure and then suggests a methodology using fuzzy theory for selecting an effective supplier. Several quantitative and qualitative evaluation factors should be analyzed in the evaluation structure. The qualitative factors includes not only product and service qualities but financial condition. The methodology deals with both the quantitative and qualitative factors together through fuzzy inference. A case study is also presented to show how to choose the best one among potential suppliers.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.14 no.2
• /
• pp.113-121
• /
• 2004

In a result that the types of intrusion detection are getting diverse in accordance with rapid internet sprawl, many intrusion detection systems have been developed. In this paper, we will propose a novel evaluation on the evaluation criteria for the intrusion detection systems using Fuzzy integrals

• Journal of Korean Port Research
• /
• v.7 no.1
• /
• pp.13-24
• /
• 1993

The rapid progress of the intermodal freight transportation in recent years has induced fierce competition among the adjacent hub ports for container transport. This brings increased attention to the evaluation of the port competitive ability. But it is not easy to evaluate the port competitive ability because this belongs to ill-defined system which is composed of ambiguous interacting attributes. Paying attention to this point, this paper deals the competitive ability of container port in Far-East Asia by fuzzy integral evaluation which is adequate to interacting ambiguous attribute problem. For this, the proposed fuzzy evaluation algorithm is applied to the real problem, based on the factors such as cargo volumes, costs, services, infrastructure and geographical sites These are extracted from the precedent study of port competitive ability, etc. The results show that the port evaluation factors come in following order ; services, costs, infrastructure, geographical sites and cargo volumes. There are some interactions(interaction coefficient, ${\lambda}=-0.664$ between evaluation attributes. The port competitive ability comes in following order : Singapore, Hongkong, Kobe, Kaoshiung and Busan. According to the sensitivity analysis, the rank between Busan and Kaoshiung changes when ${\lambda}=0.7$. From the analysis of the results, we confirmed that the proposed fuzzy evaluation algorithm is very effective in the complex-fuzzy problem which is composed of hierarchical structure with interacting attributes.

• Journal of Korea Society of Industrial Information Systems
• /
• v.4 no.2
• /
• pp.7-13
• /
• 1999

This paper propose a fuzzy regression method using fuzzy neural networks when a membership value is attached to each input -output pair. First, an architecture of fuzzy neural networks with fuzzy weights and fuzzy biases is shown. Next, a cost function is defined using the fuzzy output from the fuzzy neural network and the corresponding target output with a membership value. A learning algorithm is derived from the cost function. The derived learning algorithm trains the fuzzy neural network so that the level set of the fuzzy output includes the target output. Last, the proposed method is applied to the quality evaluation problem of injection molding

• Journal of Biomedical Engineering Research
• /
• v.18 no.4
• /
• pp.491-498
• /
• 1997

This paper describes the arousal measurement and control system using fuzzy logic to prevent drowsy driving. Sugeno's method was used for fuzzy inference in this study. Arousal evaluation and control criteria were modified from result of Nz-IRI analysis depending on arousal sate. Membership function and rule base of fuzzy inference were determined from the modified arousal level criteria When lRl (Inter-SIR Interval) was shorter than 60sec, outputs of both methods were changed from small to big, but output of three step warning method was same level until the next warning range. Since output of fuzzy inference tracked well the change of subject's arousal level, problems of three step warning method could be overcome by fuzzy inference method Furthermore, the output of the fuzzy inference was highly correlated with Nz(r = 0.99). Therefore, the fuzzy inference method for evaluation and the control of arousal will be more effective at real driving situation than three step warning method.

• IE interfaces
• /
• v.22 no.1
• /
• pp.26-37
• /
• 2009

BPM(Business Process Management) secures the agility of an enterprise through automation, integration, and optimization of business process. For the successful BPM introduction, the evaluation and selection of suitable processes for BPM are very important. But as to process evaluation and selection standards, in fact, various selection elements exist and they have to be considered. Therefore, it is very difficult to evaluate systematically and reasonably business processes for enterprises or concerned persons that plan to introduce BPM. This paper describes a Web-based business process evaluation model for BPM using BSC(Balanced Scorecard) and fuzzy AHP(Analytic Hierarchy Process). A Web-based business process evaluation system was implemented based on this and it provides many useful business process evaluation results to enterprises or concerned persons that have insufficient experience and knowledge about BPM, and initially plan to implement BPMS(Business Process Management System). Thus, this paper demonstrates the applicability of fuzzy AHP concept in business process evaluation and selection for BPM, and provides a systemic guidance in the decision-making process.