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Shimonoseki, Japan

Shimonoseki City University is a municipal university in Japan. Its campus is located in Daigaku-cho, Shimonoseki City, Yamaguchi Prefecture, Japan. Wikipedia.


Yabuuchi Y.,Shimonoseki City University | Watada J.,Waseda University
ICIC Express Letters | Year: 2010

The objective of a fuzzy regression model is to illustrate the potentialpossibilities of the target system. In the interval fuzzy regression model,system possibilities are measured by the width of the interval indicated by themodel. If the center of the model coincides with the center of the possibilitydistribution, more information could be obtained about the possibilities of thetarget system. As the model should be intuitive, this would make the proposedmodel more user-friendly and broadly applicable. In this paper, we use thepopulation of a district and its number of households as a numerical example,and we use a basin area and a drift distance in Japan as an application of ourmodel to check its features. ICIC International © 2010. Source


Yabuuchi Y.,Shimonoseki City University | Watada J.,Waseda University
Journal of Advanced Computational Intelligence and Intelligent Informatics | Year: 2011

Since management and economic systems are complex, it is hard to handle data obtained in management and economic areas. Hitherto, in the fields, much research has focused on the structure and analysis of such data. H. Tanaka et al. proposed a fuzzy regression model to illustrate the potential possibilities inherent in the target system. J. C. Bezdek proposed a switching regression model based on a fuzzy clustering model to separate mixed samples coming from plural latent systems and apply regression models to the groups of samples coming from each system. It is hard to illustrate a rough and moderate possibility of the target system. In this paper, to deal with the possibility of a social system, we propose a new fuzzy robust regression model. Source


Yabuuchi Y.,Shimonoseki City University | Watada J.,Waseda University
6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012 | Year: 2012

Economic analyses are typical methods based on time-series data or cross-section data. Economic systems are complex because they involve human behaviors and are affected by many factors. When a system includes such uncertainty, as those concerning human behaviors, a fuzzy system approach plays a pivotal role in such analysis. In this paper, we propose a fuzzy autocorrelation model with confidence intervals of fuzzy random time-series data. This confidence intervals has an essential role in dealing with fuzzy random data on our fuzzy autocorrelation model which we have presented. We analyze tick-by-tick data of stock dealing and compare two time-series models, a fuzzy autocorrelation model proposed by us, and a new fuzzy time-series model which we propose in this paper. © 2012 IEEE. Source


Matsumoto Y.,Shimonoseki City University | Watada J.,Waseda University
Smart Innovation, Systems and Technologies | Year: 2016

Rough set theory was proposed by Z. Pawlak in 1982. This theory has high capability to mine knowledge based on decision rules from a database, a web base, a set and so on. The decision rule is widely used for data analysis as well. In this paper the decision rule is employed to reason for an unknown object. That is, the rough set theory is applied to analysis of economic time series data. An example shown in the paper indicates how to acquire knowledge from time series data. At the end we suggest its application to predictions. © Springer International Publishing Switzerland 2016. Source


Yabuuchi Y.,Shimonoseki City University | Watada J.,Waseda University
Journal of Advanced Computational Intelligence and Intelligent Informatics | Year: 2012

A possibilistic regression model illustrates the potential possibilities inherent in the target system by including all data in the model. Tanaka and Guo employ exponential possibility distribution to build a model, while Inuiguchi et al. and Tajima are independently working on coinciding between the center of a possibility distribution and the center of a possibilistic regression model. Typically, samples influence and distort the shape of the model if they are far from the center of data. Yabuuchi and Watada have developed a model for describing the system possibility using the center of a possibilistic fuzzy regression model and an approach that mends the distortion of the model. The objective of this paper is to analyze the Japanese economy using our model, and to show the usefulness of our model by analysis results. Source

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