• 전자공학회논문지B
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• 제32B권12호
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• pp.1552-1564
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• 1995

A fault detecting method of ternary logic is proposed by using the spectral coefficients of the Chrestenson function. Fault detecting conditions are derived for a stuck-at fault in case of single input, multiple inputs and internal lines in the ternary logic. The detecting conditions for min/max bridging faults are also considered. When using this fault analysis method, it is possible to detect faults without the test vector and minimize high volume memory for storing the vector and response data. Thus, the computational complexity for the test vector can be decreased.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권2호
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• pp.126-131
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• 2015

Studies on the control of inverted pendulum type systems have been widely reported. This is because this type of system is a typical complex nonlinear system and may be a good model to verify the performance of a proposed control system. In this paper, we propose the design of two fuzzy logic control systems for the control of a Segway mobile robot which is an inverted pendulum type system. We first introduce a dynamic model of the Segway mobile robot and then analyze the system. We then propose the design of the fuzzy logic control system, which shows good performance for the control of any nonlinear system. In this paper, we here design two fuzzy logic control systems for the position and balance control of the Segway mobile robot. We demonstrate their usefulness through simulation examples. We also note the possibility of simplifying the design process and reducing the computational complexity. This possibility is the result of the skew symmetric property of the fuzzy rule tables of the system.

• 산업경영시스템학회지
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• 제38권1호
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• pp.74-82
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• 2015

Two key challenges in statistical relational learning are uncertainty and complexity. Standard frameworks for handling uncertainty are probability and first-order logic respectively. A Markov logic network (MLN) is a first-order knowledge base with weights attached to each formula and is suitable for classification of dataset which have variables correlated with each other. But we need domain knowledge to construct first-order logics and a computational complexity problem arises when calculating weights of first-order logics. To overcome these problems we suggest a method to generate first-order logics and learn weights using association analysis in this study.

• Journal of Computational Design and Engineering
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• 제3권1호
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• pp.1-13
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• 2016

The increase of consumer needs for quality metal cutting related products with more precise tolerances and better product surface roughness has driven the metal cutting industry to continuously improve quality control of metal cutting processes. In this paper, two different approaches are discussed. First, design of experiments (DOE) is used to determine the significant factors and then fuzzy logic approach is presented for the prediction of surface roughness. The data used for the training and checking the fuzzy logic performance is derived from the experiments conducted on a CNC milling machine. In order to obtain better surface roughness, the proper sets of cutting parameters are determined before the process takes place. The factors considered for DOE in the experiment were the depth of cut, feed rate per tooth, cutting speed, tool nose radius, the use of cutting fluid and the three components of the cutting force. Finally the significant factors were used as input factors for fuzzy logic mechanism and surface roughness is predicted with empirical formula developed. Test results show good agreement between the actual process output and the predicted surface roughness.

• Advances in Computational Design
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• 제4권4호
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• pp.367-379
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• 2019

Multiple Inputs and Multiple Outputs (MIMO) Fuzzy logic model is developed to predict the engine performance and emission characteristics of pongamia pinnata biodiesel with hydrogen injection. Engine performance and emission characteristics such as brake thermal efficiency (BTE), brake specific energy consumption (BSEC), hydrocarbon (HC), carbon monoxide (CO), carbon dioxide ($CO_2$) and nitrous oxides ($NO_X$) were considered. Experimental investigations were carried out by using four stroke single cylinder constant speed compression ignition engine with the rated power of 5.2 kW at variable load conditions. The performance and emission characteristics are measured using an Exhaust gas analyzer, smoke meter, piezoelectric pressure transducer and crank angle encoder for different fuel blends (Diesel, B10, B20 and B30) and engine load conditions. Fuzzy logic model uses triangular and trapezoidal membership function because of its higher predictive accuracy to predict the engine performance and emission characteristics. Computational results clearly demonstrate that, the proposed fuzzy model has produced fewer deviations and has exhibited higher predictive accuracy with acceptable determination correlation coefficients of 0.99136 to 1 with experimental values. The developed fuzzy logic model has produced good correlation between the fuzzy predicted and experimental values. So it is found to be useful for predicting the engine performance and emission characteristics with limited number of available data.

• 한국컴퓨터정보학회논문지
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• 제12권5호
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• pp.49-56
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• 2007

계산 그리드 컴퓨팅은 수많은 컴퓨팅 자원들을 이용하여, 슈퍼 컴퓨팅이나 이전의 분산 컴퓨팅으로 해결 할 수 없는 대용량의 연산 문제를 해결한다. 계산 그리드 컴퓨팅 환경에서의 자원은 이 기종으로 구성되어, 효율적인 작업 처리를 위해서는 스케줄링 기법이 필요하다. 본 논문에서는 계산 그리드에서 효율적인 작업 스케줄링을 위하여 퍼지로직 기반의 그리드 작업 스케줄링 모델을 제안한다. 퍼지로직 기반의 그리드 작업 스케줄링 모델은 퍼지로직을 이용하여 자원의 효율성을 평가하며, 평가된 기반으로 그룹을 구성하여 작업을 할당하는 모델이다. 우리는 DEVS 모델링 & 시뮬레이션 환경에서 시뮬레이션 모델을 구성하고 Random 스케줄링과 MCT 스케줄링 모델과의 비교 실험을 통하여 제안된 퍼지로직 기반의 그리드 작업 스케줄링 모델이 작업완료시간, 작업손실, 통신량을 개선함으로써 더욱 더 안정적이고 빠른 작업 처리 서비스를 그리드 사용자에게 제공할 수 있다는 사실을 증명하였다.

• 제어로봇시스템학회논문지
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• 제15권1호
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• pp.8-14
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• 2009

A formation flight guidance logic that enables the leader-follower station keeping between two UAVs is presented in this paper. The logic is motivated by the investigation of the relation between the proportional navigation and the nonlinear trajectory tracking guidance law, The simplicity of the presented method provides computational efficiency and allows easy implementation. An excellent performance of the proposed logic is demonstrated via various numerical simulations for multiple UAVs environment.

• 한국경영과학회지
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• 제27권4호
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• pp.87-109
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• 2002

A satisfiability problem in propositional logic is the problem of checking for the existence of a set of truth values of atomic prepositions that renders an input propositional formula true. This paper describes an empirical investigation of a particular integer programming approach, using the set covering model, to solve satisfiability problems. Our satisfiability engine, SETSAT, is a fully integrated, linear programming based, branch and bound method using various symbolic routines for the reduction of the logic formulas. SETSAT has been implemented in the integer programming shell MINTO which, in turn, uses the CPLEX linear programming system. The logic processing routines were written in C and integrated into the MINTO functions. The experiments were conducted on a benchmark set of satisfiability problems that were compiled at the University of Ulm in Germany. The computational results indicate that our approach is competitive with the state of the art.

• Journal of Applied and Pure Mathematics
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• 제6권1_2호
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• pp.97-103
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• 2024

This study is about digits of numbers in system logic B₃. Any real number is written as digits in the binary system, in the ternary system. The numbers in base two and base three are also written in the B₃ system ternary logic. These two writing methods are transferred into the third method. The real numbers 0,1 and 0, 1, 2 are written as digits. The same real numbers are written as digits of elements of the set -1, 0, 1 in base B₃. The periods here are investigated. The relationship between these digits is analysed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권4호
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• pp.256-267
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• 2014

An automatic switch among ensembles of clustering algorithms is proposed as a part of the bibliographic big data retrieval system by utilizing a fuzzy inference engine as a decision support tool to select the fastest performing clustering algorithm between fuzzy C-means (FCM) clustering, Newman-Girvan clustering, and the combination of both. It aims to realize the best clustering performance with the reduction of computational complexity from O($n^3$) to O(n). The automatic switch is developed by using fuzzy logic controller written in Java and accepts 3 inputs from each clustering result, i.e., number of clusters, number of vertices, and time taken to complete the clustering process. The experimental results on PC (Intel Core i5-3210M at 2.50 GHz) demonstrates that the combination of both clustering algorithms is selected as the best performing algorithm in 20 out of 27 cases with the highest percentage of 83.99%, completed in 161 seconds. The self-adapted FCM is selected as the best performing algorithm in 4 cases and the Newman-Girvan is selected in 3 cases.The automatic switch is to be incorporated into the bibliographic big data retrieval system that focuses on visualization of fuzzy relationship using hybrid approach combining FCM and Newman-Girvan algorithm, and is planning to be released to the public through the Internet.