• Journal of Korean Society of Water and Wastewater
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• v.19 no.4
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• pp.395-403
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• 2005

It is very important to forecast water supply for reasonal operation and management of water utilities. In this paper, water supply forecasting models using artificial intelligence are developed. Artificial intelligence models shows better results by using Temperature(t), water supply discharge (t-1) and water supply discharge (t-2), which are expressed by neural network(LMNNWS; Levenberg-Marquardt Neural Network for Water Supply, MDNNWS; MoDular Neural Network for Water Supply) and neuro fuzzy(ANASWS; Adaptive Neuro-Fuzzy Inference Systems for Water Supply). ANFISWS model which is applied for water supply forecasting shows stable application to the variable water supply data. As results, MDNNWS model shows the highest overall accuracy among proposed water supply forecasting models and the lowest estimation error with the order of ANFISWS, LMNNWS model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.3A
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• pp.172-178
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• 2012

This paper studies the application of a fuzzy-ARTMAP (FAM) neural network to multi-user detector (MUD) for direct sequence (DS)-code division multiple access (CDMA) system. This method shows new solution for solving the problems, such as complexity and long training, which is found when implementing the previously developed neural-basis MUDs. The proposed FAM based MUD is fast and easy to train and includes capabilities not found in other neural network approaches; a small number of parameters, no requirements for the choice of initial weights, automatic increase of hidden units, no risk of getting trapped in local minima, and the capabilities of adding new data without retraining previously trained data. In simulation studies, binary signals were generated at random in a linear channel with Gaussian noise. The performance of FAM based MUD is compared with other neural net based MUDs in terms of the bit error rate.

• Architectural research
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• v.12 no.2
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• pp.85-92
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• 2010

In recent years, construction projects have been forced to cope with lack of skilled labor and increasing hazard circumstance of human operations. A construction robotic system has been frequently accomplished as one alterative for overcoming these difficulties in increasing construction quality, enhancing productivity, and improving safety. However, while the complexity of such a system increases, there are few ways to carry out an assessment of the system. This paper introduces a knowledge-based multi-criteria decision-making process to assist decision makers in systematically evaluating an automated system for a given project and quantifying its system performance index. The model employs linguistic terms and fuzzy numbers in attempts to deal with the vagueness inherent in experts' or decision makers' subjective opinions, considering the contribution resulted from their knowledge on a decision problem. As an illustrative case, the system, called Robotic-based Construction Automation, for constructing steel erection of high-rise buildings was applied into this model. The results show the model's capacities and imply the application to other extended types of construction robotic systems.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.448-451
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• 2000

Fuzzy control has been researched for application of industrial processes which have no accurate mathematical model and could not controlled by conventional methods because of a lack of quantitative input-output data. Intelligent control approach based on fuzzy logic could directly reflex human thinking and natural language to controller comparing with conventional methods. In this paper, the tested system is constructed for sending a ball to the goal position using wind from two DC motors in the path. This system contains non-linearity and uncertainty because of the characteristic of aerodynamics inside the path. The system used in this experiment could be hardly modeled by mathematic methods and could not be easily controlled by linear control manners. The controller, in this paper could control the system containing non-linearity and uncertainty because it is designed based on the input-output data and experimental knowledge obtained by trials.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.296-301
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• 1998

The Rough Set theory suggested by Pawlak in 1982 has been useful in AI, machine learning, knowledge acquisition, knowledge discovery from databases, expert system, inductive reasoning. etc. The main advantages of rough set are that it does not need any preliminary or additional information about data and reduce the superfluous informations. but it is a significant disadvantage in the real application that the inference result form is not the real control value but the divided disjoint interval attribute. In order to overcome this difficulty, we will propose approach in which Rough set theory and Neuro-fuzzy fusion are combined to obtain the optimal rule base from lots of input/output datum. These results are applied to the rule construction for infering the temperatures of refrigerator's specified points.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.352-357
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• 1998

Conventional marketing research generally focuses on a single layer's benefit. A notable example is the consumer layer providing managers with partial market information to evaluate relevant strategies. As generally known, marketing management encounters complex supply and demand behaviors, thereby necessitation that a successful marketing strategy adopt multi-layer considerations, such as the consumer layer, channel-retailer layer, and marketing planner layer. In light of above situation, this study applies fuzzy theory and the analytic hierarchy process(AHP) technique to analyze the performances of marketing strategies under multi-layer benefits, In addition, conventional marketing research has difficulty in efficiently allocating the limited budget so that each desired criterion can be significantly enhanced by a group of events. Therefore, a weighting structure among the goal, layers, criteria, and strategies(i.e. a group of events) is also developed herein to trace the influential process and assist marketing managers in efficiently allocating resources(i.e.budget).

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.1
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• pp.197-211
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• 2017

In recent years, it is natural that the development and the maintenance of information systems are strongly dependent on outside service providers for economic reasons, especially in public sector. There has been an unexpected growth in the number of selection activities for outsourcing related works. At this time, selection of the contractor generally considers the proposals received based on the RFP(requested for proposal) and determines the ranking by experts committee. However, it is difficult even for expert giving a specific numeric score in weighting criteria or rating alternatives. In this context, an extended fuzzy TOPSIS method is applied for selection problem of IT proposals. A numerical illustration is also provided to demonstrate the applicability of the approach. This approach is very practical to help decision makers in assessing proposals during the selection phase under uncertainties.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.83-88
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• 2002

In order to predict the moldability of a injection molded part, a simulation of filling is needed. Short shot is one of the most frequent troubles encountered during injection molding process. The adjustment of process conditions is the most economic way to troubleshoot the problematic short shot in cost and time since the mold doesn't need to be modified at all. But it is difficult to adjust the process conditions appropriately in no times since it requires an empirical knowledge of injection molding. In this paper, the intelligent CAE system synergistically combines fuzzy-neural network (FNN) for heuristic knowledge with CAE programs for analytical knowledge. To evaluate the intelligent algorithms, a cellular phone flip has been chosen as a finite element model and filling analyses have been performed with a commercial CAE software. As the results, the intelligent CAE system drastically reduces the troubleshooting time of short shot in comparison with the experts' conventional methodology which is similar to the golden section search algorithm.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.590-594
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• 2004

본 연구는 통합의사결정지원시스템을 위한 3-단계 모델과 이를 사용자가 쉽게 활용할 수 있도록 웹 기반의 전산 프로그램을 개발하고 응용 사례를 들어 보았다. 의사결정문제의 대안 선정, 대안을 평가시스템 및 여러 평가 위원들의 평가 결과를 종합하는 문제들을 포함하였으며 AHP(Analytic Hierarchy Process) 방법과 Fuzzy AHP방법을 활용하여 평가구조 평가인자 구성 및 각 가중치 등 개관적인 방법을 사용하였다. 이러한 3단계의 통합의사 결정방법은 1) Brain storming 단계서 대안 및 평가구조를 도출하고, 2) AHP 및 Fuzzy-AHP 방법으로 각 대안을 평가하여 의사 결정의 기반을 삼으며, 3) 여러 평가자들의 평가 결과를 합리적으로 통합하여 최선의 대안을 도출하는 방법이다.

• Journal of Power Electronics
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• v.8 no.3
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• pp.210-216
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• 2008

This paper presents a classical speed controller (CSC) for vector controlled induction motors. The controller explores the use of a Fuzzy Logic controller in a classical form. The controller combines the advantages of the classical controller and the properties of intelligent controllers. The Fuzzy Logic controller idea is used to obtain the CSC output equation, whereby the CSC equation is based on the speed error and its change. The CSC parameters are calculated based on the motor mechanical equation and a predefined system performance. Once the CSC parameters are obtained, the defined speed performance can be achieved at all operating conditions. The application of the CSC to control the speed of a vector controlled induction motor is presented. Different induction motor ratings are used. Simulation results in all possible olperating conditions are presented. Results show that the CSC behaves as an expert controller to provide the predefined speed performance in all possible operating conditions. Based on the results obtained in this paper, the CSC is expected to become the ultimate solution for high-performance drives of the next generation.