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Ansari Z.,Islamic Azad University at Shiraz | Gholami Y.,Zand institute of higher education
Advances in Environmental Biology | Year: 2014

In this paper we ensembles consisting of multiple classifiers used for member classifiers, and are rewarded based on their predictive performance. In the research were used 11 inputs that involve Cash' Short-Term Investments' Notes Receivable, Inventory, Spare Parts, Inventory Stock and Other Inventory, Advance Payment, Long- Term Assets, Notes Payable, Prepaid, Long-Term Liability that applied for prediction profit equity. © 2014 AENSI Publisher All rights reserved.


Ansari Z.,Islamic Azad University at Shiraz | Aslamloo S.A.,Islamic Azad University | Gholami Y.,Zand institute of higher education
Advances in Environmental Biology | Year: 2014

In machine learning, support vector machines (SVMs, also support vector networks) are supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis. An SVM model is a representation of the examples as points in space, mapped so that the examples of the separate categories are divided by a clear gap that is as wide as possible. In the research were used 11 inputs that involve Cash, Short-Term Investments, Notes Receivable, Inventory' Spare Parts, Inventory Stock and Other Inventory, Advance Payment, Long- Term Assets, Notes Payable, Prepaid, Long-Term Liability that applied for clustering of equity by SVM method. © 2014 AENSI Publisher All rights reserved.


Jamalnia A.,University of Manchester | Mahdiraji H.A.,Islamic Azad University at Kashan | Sadeghi M.R.,Allame Tabatabaee University | Hajiagha S.H.R.,Islamic Azad University at Kashan | Feili A.,Zand Institute of Higher Education
International Journal of Information Technology and Decision Making | Year: 2013

Companies pursuing extension of their activities and new companies in establishment phase are using various concepts and techniques to consider location decision, because location greatly affects both fixed and variable costs and on the overall profit of the company. This paper suggests a new use of quality function deployment (QFD) for facility location selection problem instead of applying it to traditional product quality promotion. Fuzzy sets concept is also incorporated to deal with imprecise nature of the linguistic judgments of decision makers. First, fuzzy QFD as a stand-alone approach is presented to address international facility location selection decision. To consider resource limitations and operational constraints, fuzzy goal programming is combined with fuzzy quality function deployment to present a developed approach to deal with global facility location-allocation decision. A demonstration of the applicability of proposed methodologies in a real-world problem is presented. © 2014 World Scientific Publishing Company.

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