• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.489-491
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• 1993

Many optimization problem or multiple attribute, multiple alternative decision making problem may have fuzzy evaluation factors. In this case, fuzzy number operation technique is needed to evaluate and compare object functions which become fuzzy sets. Generally, fuzzy number operations can be defined by extension principle of fuzzy set theory, but it is tedious to do fuzzy number operations by using extension principle when the membership functions are defined by complex functions. Many fast methods which approximate the membership functions such as triangle, trapezoidal, or L-R type functions are proposed. In this paper, a fast fuzzy number operation method is proposed which do not simplify the membership functions of fuzzy numbers.

• Journal of Korean Institute of Industrial Engineers
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• v.10 no.2
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• pp.17-27
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• 1984

This paper is concerned with a branched pipe network system which transports some fluids or gas from multiple sources to multiple demand nodes. A nonlinear programming model is proposed for determining junction locations simultaneously with selection of pipe sizes and pump capacities such that the capital and operating costs of the system are minimized over a given planning horizon. To solve the model, a hierarchical decomposition method is developed with the junction location being the primary variable. With some values fixed for the primary, the other decision variables are found by linear programming. Then, using the postoptimality analysis of LP, junction locations are adjusted. We repeat this process until an optimum is approached. A simple example of designing a water distribution network is solved to illustrate the optimization procedure developed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.119-124
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• 2004

Real data as web log file tend to be incomplete. But we have to find useful knowledge from these for optimal decision. In web log data, many useful things which are hyperlink information and web usages of connected users may be found. The size of web data is too huge to use for effective knowledge discovery. To make matters worse, they are very sparse. We overcome this sparse problem using Markov Chain Monte Carlo method as multiple imputations. This missing value imputation changes spare web data to complete. Our study may be a useful tool for discovering knowledge from data set with sparseness. The more sparseness of data in increased, the better performance of MCMC imputation is good. We verified our work by experiments using UCI machine learning repository data.

• Speech Sciences
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• v.12 no.3
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• pp.115-124
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• 2005

We investigated on the submission of multiple candidates in speaker-independent speech recognition by VQ/HMM. Submission of fixed number of multiple candidates has first been examined. As the number of candidates increases by two, three, and four, the recognition error rates were found to decrease by 41%, 58%, and 65%, respectively compared to that of a single candidate. We tried another approach that the candidates within a range of Viterbi scores are submitted. The number of candidates showed geometric increase as the admitted range becomes large. For a practical application, a combination of the above two methods was also studied. We chose the candidates within some range of Viterbi scores and limited the maximum number of candidates submitted to five. Experimental results showed that recognition error rates of less than 10% could be achieved with average number of candidates of 3.2 by this method.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.2
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• pp.163-174
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• 2011

Task assignments of multiple unmanned aerial vehicles (UAVs) are examined. The phrase "task assignment" comprises the decision making procedures of a UAV group. In this study, an on-line decentralized task assignment algorithm is proposed for an autonomous UAV group. The proposed method is divided into two stages: an order optimization stage and a communications and negotiation stage. A genetic algorithm and negotiation strategy based on one-to-one communication is adopted for each stage. Through the proposed algorithm, decentralized task assignments can be applied to dynamic environments in which sensing range and communication are limited. The performance of the proposed algorithm is verified by performing numerical simulations.

• Journal of the Korea Institute of Building Construction
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• v.16 no.4
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• pp.331-339
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• 2016

According to high-rise, complexation, and enlargement of buildings, various construction methods are being developed, and the significance of construction method selection about main work types has emerged as a major interest. However, it has been pointed out that hand-on workers cannot consider project characteristics carefully, and they lack an objective standard or reference for main construction method selection. Hence, the selection is being made depending on hand-on workers' experience and intuition. To solve this problem, various studies have proceeded for construction method selection of main work types using Artificial Intelligence like Fuzzy, AHP and Case-based reasoning. It is difficult to apply many different kinds of construction method selection to every main work type with consideration for characteristics of work types and condition of a construction site when selecting construction method in the field. Accordingly, this study proposed the decision-making model which can apply to fields easily. Using matrix analysis and liner transformation, this study verified consistency of study models applied in the process of soil retaining selection with a case study.

• The Journal of Society for e-Business Studies
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• v.15 no.4
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• pp.165-179
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• 2010

Recently, the processing of data streams such as stock quotes, buy-sell orders, and billing records becomes more important in e-Business environments. Especially, the use of skyline queries over data streams is rapidly increasing to support multiple criteria decision making. Given a set of multi-dimensional tuples, a skyline query retrieves a set of tuples which are not dominated by other tuples. Although there has been much work on processing skyline queries over static datasets, there has been relatively less work on processing multiple skyline queries over data streams. In this paper, we propose an efficient method for processing multiple continuous skyline queries over data streams. The proposed method efficiently identifies which tuple is a skyline tuple of which query, resulting in a lower cost of processing multiple skyline queries. Through performance evaluation, we show the performance advantage of the proposed method.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.26-32
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• 2023

Hajj is a fundamental pillar of Islam that all Muslims must perform at least once in their lives. However, Umrah can be performed several times yearly, depending on people's abilities. Every year, Muslims from all over the world travel to Saudi Arabia to perform Hajj. Hajj and Umrah pilgrims face multiple issues due to the large volume of people at the same time and place during the event. Therefore, a system is needed to facilitate the people's smooth execution of Hajj and Umrah procedures. Multiple devices are already installed in Makkah, but it would be better to suggest the data architectures with the help of machine learning approaches. The proposed system analyzes the services provided to the pilgrims regarding gender, location, and foreign pilgrims. The proposed system addressed the research problem of analyzing the Hajj pilgrim dataset most effectively. In addition, Visualizations of the proposed method showed the system's performance using data architectures. Machine learning algorithms classify whether male pilgrims are more significant than female pilgrims. Several algorithms were proposed to classify the data, including logistic regression, Naive Bayes, K-nearest neighbors, decision trees, random forests, and XGBoost. The decision tree accuracy value was 62.83%, whereas K-nearest Neighbors had 62.86%; other classifiers have lower accuracy than these. The open-source dataset was analyzed using different data architectures to store the data, and then machine learning approaches were used to classify the dataset.

• Journal of Korean Medical classics
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• v.25 no.4
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• pp.39-55
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• 2012

Objective : In order to find the decision system in differentiation of syndromes and treatments, I paid attention to divination by Achillea sibireca. Method : I pulled out the elements of differentiation of syndromes and treatments in Zh$\bar{o}$ng y$\bar{i}$n$\grave{e}$i k$\bar{e}$ xu$\acute{e}$(中醫內科學), Uihagipmun Sanghan(醫學入門 傷寒), Donguibogam Japbyeong(東醫寶鑑 雜病) and compared them with the horoscope in The Book of Changes(周易) from the relativity of both eight principles(八綱) etc and subdivision in the entity of the cosmos (太極內 分化). Result : From this viewpoint, the decision system that has relative references in differentiation of syndromes & treatments on cold diseases(傷寒病) and complexed diseases(雜病) by eight principles etc can be compared with the decision system in divination by Achillea sibireca that the entity of the cosmos(太極) gradually can be breakdown into the positive and negative(陰陽), the positive and negative can be breakdown into four phases(四象), four phases can be breakdown into eight signs of divination(八卦), eight signs of divination can be breakdown into 64 divination signs(64卦). Conclusion : I had found that differentiation of syndromes and treatments and divination by Achillea sibireca have similarity to each other in side of decision system. Those decision systems for clinical use and telling the future has many relative references and are made of multiple structures. Clinician can easily, exactly distinguish similar syndromes of many another diseases through this way.

• Journal of Engineering Education Research
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• v.13 no.4
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• pp.51-59
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• 2010

In order to manage the lectures efficiently in the university and improve the educational outcome, the process is needed that make diagnosis of the present educational outcome of each classes on a lecture and find factors of educational outcome. In most studies for finding the factors of the efficient lecture, statistical methods such as association analysis, regression analysis are used usually, and recently decision tree analysis is employed, too. The decision tree analysis have the merits that is easy to understand a result model, and to be easy to apply for the decision making, but have the weaknesses that is not strong for characteristic of input data such as multicollinearity. This paper indicates the weaknesses of decision tree analysis, and suggests the experimental solution using multiple decision tree algorithm to supplement these problems. The experimental result shows that the suggested method is more effective in finding the reliable factors of the educational outcome.