International Journal of Computational Intelligence Systems
Volume 6, Issue 2, March 2013
1. A Hybrid Approach Based on the Combination of Adaptive Neuro-Fuzzy Inference System and Imperialist Competitive Algorithm: Oil Flow Rate of the Wells Prediction Case Study
Shahram Mollaiy Berneti
Pages: 198 - 208
In this paper, a novel hybrid approach composed of adaptive neuro-fuzzy inference system (ANFIS) and imperialist competitive algorithm is proposed. The imperialist competitive algorithm (ICA) is used in this methodology to determine the most suitable initial membership functions of the ANFIS. The proposed...
2. Progressive CFM-Miner: An Algorithm to Mine CFM – Sequential Patterns from a Progressive Database
Bhawna Mallick, Deepak Garg, P. S. Grover
Pages: 209 - 222
Sequential pattern mining is a vital data mining task to discover the frequently occurring patterns in sequence databases. As databases develop, the problem of maintaining sequential patterns over an extensively long period of time turn into essential, since a large number of new records may be added...
3. REPAIR SHOP JOB SCHEDULING WITH PARALLEL OPERATORS AND MULTIPLE CONSTRAINTS USING SIMULATED ANNEALING
N. Shivasankaran, P. Senthil Kumar, G. Nallakumarasamy, K. Venkatesh Raja
Pages: 223 - 233
Scheduling problems are generally treated as NP – complete combinatorial optimization problems which is a multi-objective and multi constraint one. Repair shop Job sequencing and operator allocation is one such NP – complete problem. For such problems, an efficient technique is required that...
4. Using Pattern Position Distribution for Software Failure Detection
Chunping Li, Ziniu Chen, Hao Du, Hui Wang, George Wilkie, JuanC. Augusto, Jun Liu
Pages: 234 - 243
We present a novel approach for using the pattern position distribution as features to detect software failure. In this approach, we divide an execution sequence into several sections and compute the pattern distribution in each section. The distribution of all patterns is then used as features to train...
5. Gantry Crane Scheduling with Interference Constraints in Railway Container Terminals
Peng Guo, Wenming Cheng, Zeqiang Zhang, Min Zhang, Jian Liang
Pages: 244 - 260
Railway container terminals, where gantry cranes are responsible for loading and unloading containers between freight trains and yards, are important hubs of hinterland logistics transportation. Terminal managers confront the challenge in improving the efficiency of their service. As the most expensive...
6. A Discrete Constrained Optimization Using Genetic Algorithms for A Bookstore Layout
Tuncay Ozcan, Sakir Esnaf
Pages: 261 - 278
In retail industry, one of the most important decisions of shelf space management is the shelf location decision for products and product categories to be displayed in-store. The shelf location that products are displayed has a significant impact on product sales. At the same time, displaying complementary...
7. Developing a Smart Clothing System for Blinds Based on Information Axiom
Senem Kursun Bahadir, Selcuk Cebi, Cengiz Kahraman, Fatma Kalaoglu
Pages: 279 - 292
In this paper, a novel approach is proposed to determine the electronic system components of a smart clothing system design developed for blinds. The integration of diverse components which are developed and produced by different technologies and materials is a major challenge in a smart clothing system...
8. A Decision Making Model for the Evaluation of Supply Chain Execution and Management Systems
Sinan Apak, Özalp Vayvay, Orhan Feyzioğlu
Pages: 293 - 306
A Supply Chain Execution and Management (SCEM) system is an enterprise application that integrates all of the necessary supply chain functions into a single system. These functions range from common ones such as warehouse and transportation management to less known ones such as demand management. In...
9. Fast Fuzzy Inference in Octave
Piero Molino, Gianvito Pio, Corrado Mencar
Pages: 307 - 317
Fuzzy relations are simple mathematical structures that enable a very general representation of fuzzy knowledge, and fuzzy relational calculus offers a powerful machinery for approximate reasoning. However, one of the most relevant limitations of approximate reasoning is the efficiency bottleneck. In...
10. A new approach for testing fuzzy hypotheses based on fuzzy data
Mohsen Arefi, S. Mahmoud Taheri
Pages: 318 - 327
A new approach for testing fuzzy hypotheses based on fuzzy data is introduced. According to the proposed approach, a method is first developed based on the defined fuzzy point estimation, which are then used to make a procedure for testing fuzzy hypotheses. This approach has been used to test simple,...
11. An Efficient Binary Differential Evolution with Parameter Adaptation
Dongli Jia, Xintao Duan, Muhammad Khurram Khan
Pages: 328 - 336
Differential Evolution (DE) has been applied to many scientific and engineering problems for its simplicity and efficiency. However, the standard DE cannot be used in a binary search space directly. This paper proposes an adaptive binary Differential Evolution algorithm, or ABDE, that has a similar framework...
12. A decision support model for multi-attribute group decision making using a multi-objective optimization approach
Jian Xiong, Yingwu Chen, Kewei Yang, Jing Liu
Pages: 337 - 353
The multi-attribute group decision making (MAGDM) problem has received considerable attention in the decision analysis field and fruitful achievements have been reported in the literature. This paper focuses on the MAGDM in which the subjective absolute judgement on alternatives with respect to evaluating...
13. Genetic Algorithm with a Local Search Strategy for Discovering Communities in Complex Networks
Dayou Liu, Di Jin, Carlos Baquero, Dongxiao He, Bo Yang, Qiangyuan Yu
Pages: 354 - 369
In order to further improve the performance of current genetic algorithms aiming at discovering communities, a local search based genetic algorithm (GALS) is here proposed. The core of GALS is a local search based mutation technique. In order to overcome the drawbacks of traditional mutation methods,...
14. Combination of interval set and soft set
Keyun Qin, Dan Meng, Zheng Pei, Yang Xu
Pages: 370 - 380
Soft set theory and interval set theory are all mathematical tools for dealing with uncertainties. This paper is devoted to the discussion of soft interval set and its application. The notion of soft interval sets is introduced by combining soft set and interval set. Several operations on soft interval...
15. Linguistic interval 2-tuple power aggregation operators and their applications
Yanli Ruan, Zheng Pei, Zhisheng Gao
Pages: 381 - 395
In this paper, we present a linguistic interval 2-tuple representation model and new linguistic interval 2-tuple aggregation operators, i.e., linguistic interval 2-tuple power average (LI2TPA) operator, linguistic interval 2-tuple weighted power average (LI2TWPA) operator and linguistic interval 2-tuple...