• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.231-240
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• 2001

Conventional expert systems has been criticized due to its lack of capability to adapt to the changing decision-making environments. In literature, many methods have been proposed to make expert systems more environment-adaptive by incorporating fuzzy logic and neural networks. The objective of this paper is to propose a new approach to building a self-evolving expert system inference mechanism by integrating fuzzy neural network and fuzzy rule extraction technique. The main recipe of our proposed approach is to fuzzify the training data, train them by a fuzzy neural network, extract a set of fuzzy rules from the trained network, organize a knowledge base, and refine the fuzzy rules by applying a pruning algorithm when the decision-making environments are detected to be changed significantly. To prove the validity, we tested our proposed self-evolving expert systems inference mechanism by using the bankruptcy data, and compared its results with the conventional neural network. Non-parametric statistical analysis of the experimental results showed that our proposed approach is valid significantly.

• International Journal of Railway
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• v.5 no.4
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• pp.144-147
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• 2012

New transport technologies have been rapidly developed and various transport systems are ready to introduce. However, there no exists effective decision making tools for pre-feasibility studies on transport systems. The pre-feasibility studies should provide reliable solutions about whether a certain transport system is feasible or not by cost-benefit analysis and effectiveness test of enhancing regional economy. This study introduces the smart transport investment/information system (SMARTIS) for supporting decision making with ease, fast and reliable methods. The SMARTIS incorporates travel demand estimates into the process of feasibility studies with automatic data processing methods to give reliable solutions quickly. The SMARTIS is expected to be informative for transit agencies, planners, and operators.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.212-216
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• 2011

Fault detection technique for photovoltaic power systems is significant to dramatically reduce economic damage in industrial fields. This paper presents a novel fault detection approach using Fourier neural networks and stochastic decision making strategy for photovoltaic systems. We achieve neural modeling to represent its nonlinear dynamic behaviors through a gradient descent based learning algorithm. Next, a general likelihood ratio test (GLRT) is derived for constructing a decision malling mechanism in stochastic fault detection. A testbed of photovoltaic power systems is established to conduct real-time experiments in which the DC power line communication (DPLC) technique is employed to transfer data sets measured from the photovoltaic panels to PC systems. We demonstrate our proposed fault detection methodology is reliable and practicable over this real-time experiment.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.1
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• pp.65-72
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• 2016

Curling is compared to the Chess because of variety and importance of strategies. For winning the Curling game, selecting optimal strategies at decision making points are important. However, there is lack of research on optimal strategies for Curling. 'Aggressive' and 'Conservative' strategies are common strategies of Curling; nevertheless, even those two strategies have never been studied before. In this study, Markov Decision Process would be applied for Curling strategy analysis. Those two strategies are defined as actions of Markov Decision Process. By solving the model, the optimal strategy could be found at any in-game states.

• Journal of Ecology and Environment
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• v.35 no.4
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• pp.251-258
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• 2012

Many aquatic ecosystems suffer from anthropogenic disturbances, including the introduction of damaging levels of toxic substances. The effects of disturbances include complex relations with various components involved in the systems, and can include physical, chemical, and hydrological disruption depending of the contaminant. Decision Support Systems (DSSs) are developed to help decision makers to deal with complex management crises, through the systematic structuring and evaluation of decisions, and through providing easy-to-use and integrated tools for information elaboration and display. We reviewed various DSSs developed for toxic substances in aquatic ecosystems, and suggested a conceptual framework which is best suited to the management of such issues within Korea. It may assist stakeholders with their decision making process, and in the achievement of a consensus on water management solutions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.112-119
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• 2017

Selecting suppliers in the global supply chain is the very difficult and complicated decision making problem particularly due to the various types of supply risk in addition to the uncertain performance of the potential suppliers. This paper proposes a multi-phase decision making model for supplier selection under supply risks in global supply chains. In the first phase, the model suggests supplier selection solutions suitable to a given condition of decision making using a rule-based expert system. The expert system consists of a knowledge base of supplier selection solutions and an "if-then" rule-based inference engine. The knowledge base contains information about options and their consistency for seven characteristics of 20 supplier selection solutions chosen from articles published in SCIE journals since 2010. In the second phase, the model computes the potential suppliers' general performance indices using a technique for order preference by similarity to ideal solution (TOPSIS) based on their scores obtained by applying the suggested solutions. In the third phase, the model computes their risk indices using a TOPSIS based on their historical and predicted scores obtained by applying a risk evaluation algorithm. The evaluation algorithm deals with seven types of supply risk that significantly affect supplier's performance and eventually influence buyer's production plan. In the fourth phase, the model selects Pareto optimal suppliers based on their general performance and risk indices. An example demonstrates the implementation of the proposed model. The proposed model provides supply chain managers with a practical tool to effectively select best suppliers while considering supply risks as well as the general performance.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.155-164
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• 2022

The review of known decisions showed that currently there are no systems and technologies for supporting the decision about the possibility of concluding the civil law agreements for medical, therapeutic and dental services. The paper models the decision-making support process on the possibility of concluding the civil law agreements for medical, therapeutic and dental services, which is the theoretical basis for the development of rules, methods and system for supporting the decision about the possibility of concluding the civil law agreements for medical, therapeutic and dental services. The paper also developed the system for supporting the decision about the possibility of concluding the civil law agreements for medical, therapeutic and dental services, which automatically and free determines the possibility or impossibility of concluding the corresponding civil law agreement for the provision of a corresponding medical service. In the case of formation of a conclusion about the possibility of concluding the agreement, further conclusion and signing of the corresponding agreement takes place. In the case of forming a conclusion about the impossibility of concluding the agreement, a request is made for finalizing the relevant agreement for the provision of the relevant medical service, indicating the reasons for the impossibility of concluding the agreement - missing essential conditions in the agreement. After finalization, the agreement can be analyzed again by the developed system for supporting the decision.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.47-55
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• 2016

As one of recent issues in the information and communication industry, internet of things has attracted attention to provide intelligent infrastructure services which connect and share data and information between real and virtual world. According to the development of these internet of things technologies, types of machines, telecommunication devices, and terminals are increasing tremendously. In this situation, connectivity and interoperability between internet of things components are important issues to build a hyper connected society. To visualize this society, it is important to set up and develop information and communication technology (ICT) standards among stakeholders. However, under limited budget and human resources, it is essential to rank standardization work items for setting standards with respect to efficiency. The purpose of this study is to provide a method for setting standardization strategies within group decision making. As a multi-criteria group decision making tool, analytic hierarchy process (AHP) is adopted and applied to determine the priorities of setting work items. The proposed method first defines decision making problem with objective, criteria, and alternatives which produces a hierarchy consisting of upper and lower criteria. Then, pairwise comparisons of academy and public sector experts are performed with respect to their relative meaning and importance. Individual surveys of expert groups are collected and summarized to determine relative criteria importance measures. Furthermore, to deliver reliable importance criteria measures, differences between academy and public sector expert groups are compared and tested using Mann-Whitney non-parametric test. The results are illustrated for useful guidelines to practical group decision making in standardization strategy establishments.

• Journal of the Korean Society of Food Culture
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• v.35 no.2
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• pp.173-180
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• 2020

This study evaluated methods of improving sustained learning participation by examining the structural relationship of school support consisting of professor support, friend-senior support and educational environment support, career decisionmaking self-efficacy, school satisfaction, and learning persistence depending on the characteristics of college students majoring in culinary art and food service. The study findings were as follows. First, the general characteristics of college students majoring in culinary art and food service were perceived significantly more by female students than by male students. Second, school support directly influenced the career decision-making self-efficacy and school satisfaction, but did not directly influence the learning persistence. Instead, school support influenced school satisfaction and learning persistence indirectly by the medium of career decision-making self-efficacy. Third, career decision-making self-efficacy directly influenced school satisfaction and learning persistence and indirectly influenced learning persistence by the medium of school satisfaction. Lastly, school satisfaction directly influenced the learning persistence, implying that school satisfaction is an important factor for the learning persistence of college students majoring in culinary art and food service. These results show that, because school members and environmental support cannot exclusively make learning persistence, diverse systems and programs must be developed and applied to improve the career decision-making self-efficacy and school satisfaction of college students majoring in culinary art and food service.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.90-113
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• 2021

Electronic Records Management System (ERMS) is a computer program or set of applications that is utilized for keeping up to date records along with their storage. ERMS has been extensively utilized for enhancing the performance of academic institutions. The system assists in the planning and decision-making processes, which in turn enhances the competencies. However, although ERMS is significant in supporting the process of decision-making, the majority of organizations have failed to take an initiative to implement it, taking into account that are some implementing it without an appropriate framework, and thus resulted in the practice which does not meet the accepted standard. Therefore, this study identifies the factors influencing the adoption of ERMS among employees of HLI in Yemen and the role of such adoption in the decision-making process, using the Unified Theory of Acceptance and Use of Technology (UTAUT) along with Technology, Organization and Environment (TOE) as the underpinning theories. The study conducts a cross-sectional survey with a questionnaire as the technique for data collection, distributed to 364 participants in various Yemeni public Higher Learning Institutions (HLI). Using AMOS as a statistical method, the findings revealed there are significant and positive relationships between technology factors (effort expectancy, performance expectancy, IT infrastructure and security), organizational factors (top management support, financial support, training, and policy),environmental factors (competitiveness pressure, facilitating conditions and trust) and behavioral intention to adopt ERMS, which in return has a significant relationship with the process of decision-making in HLI. The study also presents a variety of theoretical and empirical contributions that enrich the body of knowledge in the field of technology adoption and the electronic record's domain.