Fuzzy Logic Systems Institute FLSI

Iizuka, Japan

Fuzzy Logic Systems Institute FLSI

Iizuka, Japan

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Kashan A.H.,Tarbiat Modares University | Tavakkoli-Moghaddam R.,University of Tehran | Gen M.,Fuzzy Logic Systems Institute FLSI | Gen M.,Tokyo University of Science
Advances in Intelligent Systems and Computing | Year: 2017

This paper introduces a new evolutionary algorithm for continuous optimization which mimics the targeting process of selecting objects or installations to be destroyed in warfare. The algorithm performs main steps of Find, Fix, Finish, Exploit and Analyze (F3EA) in an iterative manner. For the Find step, a new selection operator is introduced which mimics the object detection process followed by the radar devices. It is justified that how the Fix step can be modeled as a single variable optimization problem to scan the path between the two individuals to determine the precise location of a local optimum. During the Finish step, which is a mutation stage, it is assumed that an artificial missile is launched from the current position toward the position selected via the Find step.We use from the motion equations of Physics which govern the path traveled by the missile to generate the new solutions within the search space. The Exploit step tries to take over opportunities presented by the generated solution during the Finish step. Finally in the Analyze step, if the resultant solution of the Exploit step produces a better function value, it enters into the population or updates the global best solution. Performance of the proposed algorithm is tested on a collection of classic functions. Results demonstrate that the algorithm is very efficient and effective. © Springer Science+Business Media Singapore 2017.


Uchino E.,Yamaguchi University | Uchino E.,Fuzzy Logic Systems Institute FLSI | Kubota R.,National Institute of Technology, Ube College | Koga T.,Tokuyama College of Technology | And 2 more authors.
IEICE Transactions on Information and Systems | Year: 2016

In this paper we propose a novel classification method for the multiple k-nearest neighbor (MkNN) classifier and show its practical application to medical image processing. The proposed method performs fine classification when a pair of the spatial coordinate of the observation data in the observation space and its corresponding feature vector in the feature space is provided. The proposed MkNN classifier uses the continuity of the distribution of features of the same class not only in the feature space but also in the observation space. In order to validate the performance of the present method, it is applied to the tissue characterization problem of coronary plaque. The quantitative and qualitative validity of the proposed MkNN classifier have been confirmed by actual experiments. © 2016 The Institute of Electronics, Information and Communication Engineers.


Uchino E.,Yamaguchi University | Uchino E.,Fuzzy Logic Systems Institute FLSI | Koga T.,Tokuyama College of Technology | Misawa H.,Hiroshima City University | Suetake N.,Yamaguchi University
Journal of Intelligent Manufacturing | Year: 2014

We propose a tissue characterization method for coronary plaques by using fractal analysis-based features. Those features are obtained from radiofrequency (RF) signals measured by the intravascular ultrasound (IVUS) method. The IVUS method is used for the diagnosis of the acute coronary syndrome. In the proposed method, the fact that the complexity of the tissue structures is reflected in the RF signals is used. The effectiveness of the proposed method is verified through some experiments by using IVUS RF signals obtained from rabbits and human patients. © 2013 Springer Science+Business Media New York.


Koga T.,Tokuyama College of Technology | Uchino E.,Yamaguchi University | Uchino E.,Fuzzy Logic Systems Institute FLSI | Suetake N.,Yamaguchi University
IEEE International Conference on Fuzzy Systems | Year: 2011

We propose a fully automatic plaque boundary extraction system for an intravascular ultrasound (IVUS) image aiming at practical use in clinic. The IVUS image, which is commonly used for a diagnosis of acute coronary syndromes (ACS) in the field of cardiology, has coarse-grained texture due to heavy speckle noise. A medical doctor's interpretation of the IVUS image is disturbed frequently by the heavy speckle noise. In the proposed system, the heavy speckle noise is reduced firstly by using an anisotropic diffusion filter. Secondarily, the plaque boundary is extracted by using the Takagi-Sugeno (T-S) type fuzzy inference with a weighted separability measure and some heuristic rules. Extraction of plaque boundary is achieved fully automatically. The proposed system substantially reduces the workload of medical doctors. The effectiveness of the proposed system has been verified by the experiments using the real IVUS images. © 2011 IEEE.


Tasan A.S.,Dokuz Eylül University | Gen M.,Fuzzy Logic Systems Institute FLSI
40th International Conference on Computers and Industrial Engineering: Soft Computing Techniques for Advanced Manufacturing and Service Systems, CIE40 2010 | Year: 2010

The vehicle routing problem with simultaneous pick-up and deliveries, which considers simultaneous distribution and collection of goods to/from customers, is an extension of the capacitated vehicle routing problem. There are numerous real cases, that fleet of vehicles originated in a depot serves customers with pick-up and deliveries from/to their locations. Increasing importance of reverse logistics activities make it necessary to determine efficient and effective vehicle routes for simultaneous pick-up and delivery activities. The vehicle routing problem with simultaneous pick-up and deliveries is also NP-hard as capacitated vehicle routing problem and this study proposes a genetic algorithm based approach to this problem. Computational example is given for an illustrative in order to illustrate the performance of the proposed approach.


Hao X.-C.,Waseda University | Wu J.-Z.,Soochow University of Taiwan | Chien C.-F.,National Tsing Hua University | Gen M.,Fuzzy Logic Systems Institute FLSI
Journal of Intelligent Manufacturing | Year: 2014

A large number of studies have been conducted in the area of semiconductor final test scheduling (SFTS) problems. As a specific example of the simultaneous multiple resources scheduling problem, intelligent manufacturing planning and scheduling based on meta-heuristic methods, such as the genetic algorithm (GA), simulated annealing, and particle swarm optimization, have become common tools for finding satisfactory solutions within reasonable computational times in real settings. However, only a few studies have analyzed the effects of interdependent relations during group decision-making activities. Moreover, for complex and large problems, local constraints and objectives from each managerial entity and their contributions toward global objectives cannot be effectively represented in a single model. This paper proposes a novel cooperative estimation of distribution algorithm (CEDA) to overcome these challenges. The CEDA extends a co-evolutionary framework incorporating a divide-and-conquer strategy. Numerous experiments have been conducted, and the results confirmed that CEDA outperforms hybrid GAs for several SFTS problems. © 2013 Springer Science+Business Media New York.


Zhang W.,Henan University of Technology | Gen M.,Fuzzy Logic Systems Institute FLSI | Gen M.,National Tsing Hua University | Jo J.,Dongseo University
Journal of Intelligent Manufacturing | Year: 2014

Process planning and scheduling (PPS) is an important and practical topic but very intractable problem in manufacturing systems. Many research studies used multiobjective evolutionary algorithm (MOEA) to solve such problems; however, they cannot achieve satisfactory results in both quality and computational speed. This paper proposes a hybrid sampling strategy-based multiobjective evolutionary algorithm (HSS-MOEA) to deal with the PPS problem. HSS-MOEA tactfully combines the advantages of vector evaluated genetic algorithm (VEGA) and a sampling strategy according to a new Pareto dominating and dominated relationship-based fitness function (PDDR-FF). The sampling strategy of VEGA prefers the edge region of the Pareto front and PDDR-FF-based sampling strategy has the tendency converging toward the central area of the Pareto front. These two mechanisms preserve both the convergence rate and the distribution performance. The numerical comparisons state that the HSS-MOEA is better than a generalized Pareto-based scale-independent fitness function based genetic algorithm combing with VEGA in efficacy (convergence and distribution) performance, while the efficiency is closely equivalent. Moreover, the efficacy performance of HSS-MOEA is also better than NSGA-II and SPEA2, and the efficiency is obviously better than their performance. © 2013 Springer Science+Business Media New York.


Vachkov G.,Yamaguchi University | Uchino E.,Fuzzy Logic Systems Institute FLSI
Smart Innovation, Systems and Technologies | Year: 2012

This paper is dealing with the problem of tissue characterization of the plaque in the coronary arteries by processing the data from the intravascular ultrasound catheter. The similarity analysis method in the paper is applied in the frame of the moving window approach, which scans all cells in the matrix data from one cross section of the artery. The center-of-gravity model is used for evaluating the dissimilarity between any given pairs of data sets, belonging to pairs of windows. As a computational strategy, the use of weighted values of dissimilarity within the cells belonging to one window is proposed in the paper, rather than simply using an equal mean value for all cells in the window. The similarity results from each cross section of the artery are displayed as gray scale image, where the darker areas denote the more similar areas to a predefined region of interest. The simulation results from the tissue characterization of a real data set show that the weighted moving window approach gives a sharper resolution of the similarity results that are closer to the real results, compared to the simple mean value approach. This suggests that the weighted moving window approach can be applied to real medical diagnosis. © Springer-Verlag Berlin Heidelberg 2012.


Tasan A.S.,Dokuz Eylül University | Gen M.,Fuzzy Logic Systems Institute FLSI | Gen M.,Hanyang University
Computers and Industrial Engineering | Year: 2012

The vehicle routing problem with simultaneous pick-up and deliveries, which considers simultaneous distribution and collection of goods to/from customers, is an extension of the capacitated vehicle routing problem. There are various real cases, where fleet of vehicles originated in a depot serves customers with pick-up and deliveries from/to their locations. Increasing importance of reverse logistics activities make it necessary to determine efficient and effective vehicle routes for simultaneous pick-up and delivery activities. The vehicle routing problem with simultaneous pick-up and deliveries is also NP-hard as a capacitated vehicle routing problem and this study proposes a genetic algorithm based approach to this problem. Computational example is presented with parameter settings in order to illustrate the proposed approach. Moreover, performance of the proposed approach is evaluated by solving several test problems. © 2011 Elsevier Ltd. All rights reserved.


Yamakawa T.,Fuzzy Logic Systems Institute FLSI | Miki T.,Kyushu Institute of Technology
Studies in Fuzziness and Soft Computing | Year: 2015

Nine basic fuzzy logic functions can be represented by the Bounded- Difference(s) and theAlgebraic Sum(s). In current mode electronic circuits, the Algebraic Sum is implemented only by connecting wires (wired sum), and the Bounded Difference done by current difference and prevention of negative current. These fuzzy logic functions are implemented in the form of CMOS integrated circuits. The design criteria are also presented. © 2015 Springer International Publishing Switzerland

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