International Journal of Computational Intelligence Systems

Volume 9, Issue 3, June 2016

1. Interval-valued Evidence Updating with Reliability and Sensitivity Analysis for Fault Diagnosis

Xiaobin Xu, Zhen Zhang, Dongling Xu, Yuwang Chen
Pages: 396 - 415
Information fusion methods based on Dempster-Shafer evidence theory (DST) have been widely used in fault diagnosis. In DST-based methods, the monitoring information collected from sensors is modeled as multiple pieces of diagnosis evidence in the form of basic belief assignment (BBA), and Dempster’s...

2. SONFIS: Structure Identification and Modeling with a Self-Organizing Neuro-Fuzzy Inference System

Héctor Allende-Cid, Rodrigo Salas, Alejandro Veloz, Claudio Moraga, Héctor Allende
Pages: 416 - 432
This paper presents a new adaptive learning algorithm to automatically design a neural fuzzy model. This constructive learning algorithm attempts to identify the structure of the model based on an architectural self-organization mechanism with a data-driven approach. The proposed training algorithm self-organizes...

3. Selecting appropriate ERP software using integrated fuzzy linguistic preference relations – fuzzy TOPSIS method

Süleyman Çakır
Pages: 433 - 449
Due to the high uncertainty of business environment, the complexity and diversity of enterprise resource planning (ERP) projects and conflicting assessment criteria, appropriate ERP software selection can be viewed as a multi-criteria decision-making (MCDM) problem. Among the MCDM methods, extent analysis...

4. Descriptive and Comparative Analysis of Human Perceptions expressed through Fuzzy Rating Scale-based Questionnaires

Pelayo Quirós, Jose M. Alonso, David P. Pancho
Pages: 450 - 467
Opinion surveys are widely admitted as a valuable source of information which becomes complementary to the information extracted from data by machine learning techniques. This paper focuses on a challenging and still open problem which is related to how to handle properly the inherent uncertainty of...

5. Multi-Groups Decision Making using Intuitionistic-valued Hesitant Fuzzy Information

Hai Wang, Zeshui Xu
Pages: 468 - 482
Multi-groups decision making (MGDM) problems, which contain multiple groups of experts acting collectively to evaluate a set of alternatives with respect to several criteria, are focused on in this study. The existing solutions for MGDM are to aggregate the evaluations three times at different levels,...

6. A Decision Support System Based on a Genetic Algorithm for the Utilization of Leftovers

Hsin-Pin Fu, Cheng-Yuan Ku, Tsung-Sheng Chang
Pages: 483 - 496
There are usually some leftovers (usable pieces of raw material) and scraps (unusable pieces of raw material).generated after the completion of a manufacturing process. These leftovers consist of many different types, materials, styles and sizes so the use of such materials is difficult to manage, resulting...

7. A Definition for Hesitant fuzzy Partitions

Laya Aliahmadipour, Vicenç Torra, Esfandiar Eslami, Mahdi Eftekhari
Pages: 497 - 505
In this paper, we define hesitant fuzzy partitions (H-fuzzy partitions) to consider the results of standard fuzzy clustering family (e.g. fuzzy c-means and intuitionistic fuzzy c-means). We define a method to construct H-fuzzy partitions from a set of fuzzy clusters obtained from several executions of...

8. An autonomous teaching-learning based optimization algorithm for single objective global optimization

Fangzhen Ge, Liurong Hong, Li Shi
Pages: 506 - 524
Teaching-learning based optimization is a newly developed intelligent optimization algorithm. It imitates the process of teaching and learning simply and has better global searching capability. However, some studies have shown that TLBO is good at exploration but poor at exploitation and often falls...

9. Hybridizing a fuzzy multi-response Taguchi optimization algorithm with artificial neural networks to solve standard ready-mixed concrete optimization problems

Barış Şimşek, Yusuf Tansel İç, Emir Hüseyin Şimşek
Pages: 525 - 543
In this study, a fuzzy multi-response standard ready-mixed concrete (SRMC) optimization problem is addressed. This problem includes two conflicting quality optimization objectives. One of these objectives is to minimize the production cost. The other objective is to assign the optimal parameter set of...

10. Migration Ratio Model Analysis of Biogeography-Based Optimization Algorithm and Performance Comparison

Jie-sheng Wang, Jiang-di Song
Pages: 544 - 558
Biogeography-based optimization (BBO) algorithm is based on species migration between habitats to complete information circulation and sharing, which achieves the global optimization by improving the adaptability of habitats. In this paper, the basic migration balance model of biogeography theory is...

11. Improvement of the Aircraft Traffic Management Advisor Optimization Using a Hybrid Genetic Algorithm

Adel Soheili, Habib Rajabi Mashhadi
Pages: 559 - 571
During the last decade, problems regarding the Traffic Management Advisor(TMA) has become a concerning matter. A novel hybrid Genetic Algorithm(GA) for the goal of seeking best possible alignment has been presented in this paper. This simple and yet very thorough method benefits from low computational...

12. Adopting Relational Reinforcement Learning in Covering Algorithms for Numeric and Noisy Environments

Hebah ElGibreen, Mehmet Sabih Aksoy
Pages: 572 - 594
Covering algorithms (CAs) constitute a type of inductive learning for the discovery of simple rules to predict future activities. Although this approach produces powerful models for datasets with discrete features, its applicability to problems involving noisy or numeric (continuous) features has been...