• Coupled systems mechanics
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• v.2 no.3
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• pp.255-269
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• 2013

This paper targets to investigate the solution of fuzzy quadratic Riccati differential equations with various types of fuzzy environment using Homotopy Perturbation Method (HPM). Fuzzy convex normalized sets are used for the fuzzy parameter and variables. Obtained results are depicted in term of plots to show the efficiency of the proposed method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.9
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• pp.4183-4191
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• 2011

Considering the characteristics of a data stream whose data elements are continuously generated and may change over time, there have been many techniques to differentiate the importance of data elements in a data stream by their generation time. The conventional techniques are efficient to get an analysis result focusing on the recent information in a data stream, but they have a limitation to differentiate the importance of information in various ways more flexible. An information differentiation technique based on the term of a fuzzy set can be an alternative way to compensate the limitation. A term of a fuzzy set has been widely used in various data mining fields, which can overcome the sharp boundary problem and give an analysis result reflecting the requirements in real world applications more. In this paper, a fuzzy window mechanism is proposed, which is adapting a term of a fuzzy set and is efficiently used to differentiate the importance of information in mining data streams. Basic concepts including fuzzy calendars are described first, and subsequently details on data stream mining of weighted patterns using a fuzzy window technique are described.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1172-1174
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• 2002

An adaptive fuzzy P + ID controller for variable speed operation of BLDC motor drives is presented in this paper. Generally, a conventional PID controller is most widely used in industry due to its simple control structure and ease of design. However, the PID controller suffers from the electrical machine parameter variations and disturbances. To improve the tracking performance for parameter and load variations, the controller proposed in this paper is constructed by using an adaptive fuzzy logic controller in place of the proportional term in a conventional PID controller. For implementing this controller, only one additional parameter has to be adjusted in comparison with the PID controller. An adaptive fuzzy controller applied to proportional term to achieve robustness against parameter variations has simple structure and computational simplicity. The controller based on optimal fuzzy logic controller has an self-tuning characteristics with clustering. Computer simulation results show the usefulness of the proposed controller.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.1
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• pp.25-32
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• 2011

In this paper, we study the existence and uniqueness of solutions for the impulsive semilinear fuzzy integrodifferential equations with nonlocal conditions and forcing term with memory in n-dimensional fuzzy vector space ($E^n_N$, $d_{\varepsilon}$) by using Banach fixed point theorem. That is an extension of the result of Kwun et al. [9] to impulsive system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.327-332
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• 2009

This paper proposes a method to improve the accuracy of a short-term electrical load forecasting (STLF) system based on neuro-fuzzy models. The proposed method compensates load forecasts based on the error obtained during the previous prediction. The basic idea behind this approach is that the error of the current prediction is highly correlated with that of the previous prediction. This simple compensation scheme using error information drastically improves the performance of the STLF based on neuro-fuzzy models. The viability of the proposed method is demonstrated through the simulation studies performed on the load data collected by Korea Electric Power Corporation (KEPCO) in 1996 and 1997.

• Journal of the Korean Society of Safety
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• v.21 no.2 s.74
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• pp.22-28
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• 2006

This paper presents assessment of possibility on the human risk for the electromagnetic field of unbalanced two coupled three-phase transmission line using fuzzy theory. Three phase load flow program was developed which employed a Newton-Raphson method as a tool to analyze system unbalanced. This research presents a method of handling two coupled three phase transmission system unbalance analysis and unbalanced power demand as a function of voltages. As the results of case study, in case of 345[kV] T/L, the electric field intensity was 10.9540[kV/m], magnetic field intensity was 0.2567[G] in severest case. The results showed that the membership of a proposition fuzzy '10.9540 [kV/m] is hazardous' is 0.6349. As the analytic results using the fuzzy qualifier term, the membership in case of very false is 0.1379 and fairly false is 0.6124, respectively. In assessment of fuzzy measure possibility for the electromagnetic field, this paper used probability of fuzzy arid measure of fuzziness technique.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.261-265
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• 2004

This paper proposes a fuzzy dual method for analyzing long-term transmission system expansion planning problem considering ambiguities of the power system using fuzzy lineal programming. Transmission expansion planning problem can be formulated integer programming or linear programming with minimization total cost subject to reliability (load balance). A long-term expansion planning problem of a grid is very complex, which have uncertainties fur budget, reliability criteria and construction time. Too much computation time is asked for actual system. Fuzzy set theory can be used efficiently in order to consider ambiguity of the investment budget (economics) for constructing the new transmission lines and the delivery marginal rate (reliability criteria) of the system in this paper. This paper presents formulation of fuzzy dual method as first step for developing a fuzzy Ford-Fulkerson algorithm in future and demonstrates sample study. In application study, firstly, a case study using fuzzy integer programming with branch and bound method is presented for practical system. Secondly, the other case study with crisp Ford Fulkerson is presented.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.230-236
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• 2011

This paper proposes the possibility which the fuzzy theory can be used to improve the performance of the parabolic SAR(Stop-And-Reverse) indicator in the trading systems for stock market. The simulation results with data of the KOSPI 200 future show that the occurred number of trading signals and the false signals in the proposed fuzzy SAR indicator is less than that in the conventional SAR indicator. In the conventional SAR system, the incremental value of the acceleration factor is usually setted as 0.02 and the maximum value of the acceleration factor is usually limited as 0.2. But in the proposed fuzzy SAR system, the incremental value and the maximum value of the acceleration factor are automatically adjusted by using the fuzzy rules, which are designed based-on the difference between short-term moving average and medium-term moving average and also based-on the slope of short-term moving average.

• Journal of KIISE:Software and Applications
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• v.31 no.11
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• pp.1519-1533
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• 2004

When Web-based special retrieval systems for scientific field extremely restrict the expression of user's information request, the process of the information content analysis and that of the information acquisition become inconsistent. In this paper, we apply the fuzzy retrieval model to solve the high time complexity of the retrieval system by constructing a reduced term set for the term's relatively importance degree. Furthermore, we perform a cluster retrieval to reflect the user's Query exactly through the similarity relation matrix satisfying the characteristics of the fuzzy compatibility relation. We have proven the performance of a proposed re-ranking model based on the similarity union of the fuzzy retrieval model and the document cluster retrieval model.

• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.147-155
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• 2012

We propose some properties for a fuzzy correlation test by reduced-spread fuzzy variance for sample fuzzy data. First, we define the condition of fuzzy data for repeatedly observed data or that which includes error term data. By using the average of spreads for fuzzy numbers, we reduce the spread of fuzzy variance and define the agreement index for the degree of acceptance and rejection. Given a non-normal random fuzzy sample, we have bivariate normal distribution by apply Box-Cox power fuzzy transformation and test the fuzzy correlation for independence between the variables provided by the agreement index.