International Journal of Computational Intelligence Systems

Volume 9, Issue 1, January 2016

1. A Novel Role-based Access Control Model in Cloud Environments

Jun Luo, Hongjun Wang, Xun Gong, Tianrui Li
Pages: 1 - 9
In Cloud environments, the relationship between resources and users is more ad hoc and dynamic. The role-based access control (RBAC) model is an appropriate access control model for Cloud environments. When using the RBAC model in Cloud environments, some new elements should be considered. This pa- per...

2. Cardinal, Median Value, Variance and Covariance of Exponential Fuzzy Numbers with Shape Function and its Applications in Ranking Fuzzy Numbers

S. Rezvani
Pages: 10 - 24
In this paper, the researcher proposed a method to cardinal, median value, variance and covariance of exponential fuzzy numbers with shape function . The covariance used in this method is obtained from the exponential trapezoidal fuzzy number, first by finding mathematical expectation and then calculating...

3. A new integrated forward and reverse logistics model: A case study

Jasenka Djikanovic, Mirko Vujosević
Pages: 25 - 35
The increment of the number of activities related to recycling and recovery of products are determined mostly, by the legal regulations, but also, by the needs of users. As a result, there is a large quantites of materials and products that have been returned from the market for a specific reason. This...

4. Interval-Valued Intuitionistic Fuzzy Derivative and Differential Operations

Hua Zhao, Zeshui Xu, Zeqing Yao
Pages: 36 - 56
The interval-valued intuitionistic fuzzy set (IVIFS) generalizes Atanassov's intuitionistic fuzzy set (A-IFS) with the membership and non-membership degrees being intervals instead of real numbers, so it can contain more information. In this paper, we study the derivatives and differentials under interval-valued...

5. A Novel Mechanism for Efficient the Search Optimization of Genetic Algorithm

Chen-Fang Tsai, Shin-Li Lu
Pages: 57 - 64
This paper proposes a Social Genetic Algorithm (SGA) that includes a transformation function that has ability to improve search efficiency. The SGA is different from the Traditional Genetic Algorithm (TGA) approaches, as it allows refinement of the TGA parameters for the selections of operators in each...

6. Development of Emotional State Model using Electromagnetic Signal Information for Rehabilitation Robot

Aimi Shazwani Ghazali, Shahrul Naim Sidek, Sado Fatai
Pages: 65 - 79
The paper presents a development of emotion recognition system which can detect human emotion in real-time leveraging information captured from human body's electromagnetic (EM) signals. A new model of controller framework was designed to embed the emotion recognition module which was evaluated on a...

7. An improved fruit fly optimization algorithm based on selecting evolutionary direction intelligently

Lei Wu, Wensheng Xiao, Liang Zhang, Qi Liu, Jingli Wang
Pages: 80 - 90
As a novel global optimization algorithm, the fruit fly optimization algorithm FOA has been successfully applied in a variety of mathematic and engineering fields. For the purpose of accelerating the convergence speed and overcoming the shortcomings of FOA, an improved fruit fly optimization called SEDI-FOA...

8. Cross-docking Location Selection in Distribution Systems: A New Intuitionistic Fuzzy Hierarchical Decision Model

S. Meysam Mousavi, Behnam Vahdani
Pages: 91 - 109
This paper introduces a new intuitionistic fuzzy hierarchical group decision-making (IFHGDM) model for the cross-docking location selection problem. The model is based on intuitionistic fuzzy modified group complex proportional assessment and group order preference by similarity to ideal solution, structuring...

9. Hesitant Fuzzy Filters in -algebras

Akbar Rezaei, Arsham Borumand Saeid
Pages: 110 - 119
In this paper, we introduce the notion of hesitant fuzzy (implicative) filters and get some results on - algebras and show that every hesitant fuzzy implicative filter is a hesitant fuzzy filter but not the converse. Finally, we state and prove the relationship between hesitant fuzzy (implicative)...

10. Toward Automated Quality Classification via Statistical Modeling of Grain Images for Rice Processing Monitoring

Jinping Liu, Zhaohui Tang, Qing Chen, Pengfei Xu, Wenzhong Liu, Jianyong Zhu
Pages: 120 - 132
Computer vision-based rice quality inspection has recently attracted increasing interest in both academic and industrial communities because it is a low-cost tool for fast, non-contact, nondestructive, accurate and objective process monitoring. However, current computer-vision system is far from effective...

11. Multi-attribute group decision making based on Choquet integral under interval-valued intuitionistic fuzzy environment

Jindong Qin, Xinwang Liu, Witold Pedrycz
Pages: 133 - 152
In this paper, we propose new methods to represent interdependence among alternative attributes and experts’ opinions by constructing Choquet integral using interval-valued intuitionistic fuzzy numbers. In the sequel, we apply these methods to solve the multiple attribute group decision-making...

12. ELECTRE I Method Using Hesitant Linguistic Term Sets: An Application to Supplier Selection

Ali Fahmi, Cengiz Kahraman, Ümran Bilen
Pages: 153 - 167
Decision making is a common process in human activities. Every person or organization needs to make decisions besides dealing with uncertainty and vagueness associated with human cognition. The theory of fuzzy logic provides a mathematical base to model the uncertainities. Hesitant fuzzy linguistic term...

13. Intelligent Decision Support System for Real-Time Water Demand Management

Borja Ponte, David de la Fuente, José Parreño, Raúl Pino
Pages: 168 - 183
Environmental and demographic pressures have led to the current importance of Water Demand Management (WDM), where the concepts of efficiency and sustainability now play a key role. Water must be conveyed to where it is needed, in the right quantity, at the required pressure, and at the right time using...

14. Hyperrectangles Selection for Monotonic Classification by Using Evolutionary Algorithms

Javier García, Adnan M. AlBar, Naif R. Aljohani, José-Ramón Cano, Salvador García
Pages: 184 - 201
In supervised learning, some real problems require the response attribute to represent ordinal values that should increase with some of the explaining attributes. They are called classification problems with monotonicity constraints. Hyperrectangles can be viewed as storing objects in R which can be...