International Journal of Computational Intelligence Systems

Volume 3, Issue 6, December 2010

1. Uncertainty and Preference Modelling for Multiple Criteria Vehicle Evaluation

Qiuping Yang, Xinlian Xie, Dong-ling Xu, Jian-bo Yang, Anil Kumar Maddulapalli
Pages: 688 - 708
A general framework for vehicle assessment is proposed based on both mass survey information and the evidential reasoning (ER) approach. Several methods for uncertainty and preference modeling are developed within the framework, including the measurement of uncertainty caused by missing information,...

2. Performance Based Clustering for Benchmarking of Container Ports: an Application of Dea and Cluster Analysis Technique

Jie Wu, Liang Liang, Malin Song
Pages: 709 - 722
The operational performance of container ports has received more and more attentions in both academic and practitioner circles, the performance evaluation and process improvement of container ports have also been the focus of several studies. In this paper, Data Envelopment Analysis (DEA), an effective...

3. Performance Enhancement of Data Classification using Selectively Cloned Genetic Algorithm for Neural Network

Devinder Kaur, Praneeth Nelapati
Pages: 723 - 732
The paper demonstrates performance enhancement using selective cloning on evolutionary neural network over the conventional genetic algorithm and neural back propagation algorithm for data classification. Introduction of selective cloning improves the convergence rate of the genetic algorithm without...

4. A New Fast Vertical Method for Mining Frequent Patterns

Zhihong Deng, Zhonghui Wang
Pages: 733 - 744
Vertical mining methods are very effective for mining frequent patterns and usually outperform horizontal mining methods. However, the vertical methods become ineffective since the intersection time starts to be costly when the cardinality of tidset (tid-list or diffset) is very large or there are a...

5. Remote Sensing Image Enhancement Based on Orthogonal Wavelet Transformation Analysis and Pseudo-color Processing

Zhiwen Wang, Shaozi Li, Yanping Lv, Kaitao Yang
Pages: 745 - 753
Wavelet analysis based on image enhancement technique is only applicable to black-and-white image, and pseudo-color image processing technology cannot adequately deal with some of the details information of the image. In this paper, an enhanced approach of remote sensing image based on orthogonal wavelet...

6. Simultaneous feature selection and classification via Minimax Probability Machine

Liming Yang, Laisheng Wang, Yuhua Sun, Ruiyan Zhang
Pages: 754 - 760
This paper presents a novel method for simultaneous feature selection and classification by incorporating a robust L1-norm into the objective function of Minimax Probability Machine (MPM). A fractional programming framework is derived by using a bound on the misclassification error involving the mean...

7. Uncertain Bonferroni Mean Operators

Zeshui Xu
Pages: 761 - 769
The Bonferroni mean is a traditional mean type aggregation operator bounded by the max and min operators, which is suitable to aggregate the crisp data. In this paper, we consider situations where the input data are interval numbers. We develop some uncertain Bonferroni mean operators, and then combine...

8. Clustering with Instance and Attribute Level Side Information

Jinlong Wang, Shunyao Wu, Gang Li
Pages: 770 - 785
Selecting a suitable proximity measure is one of the fundamental tasks in clustering. How to effectively utilize all available side information, including the instance level information in the form of pair-wise constraints, and the attribute level information in the form of attribute order preferences,...

9. Duopoly Market Analysis within One-Shot Decision Framework with Asymmetric Possibilistic Information

Peijun Guo, Ruiliang Yan, John Wang
Pages: 786 - 796
In this paper, a newly emerging duopoly market with a short life cycle is analyzed. The partially known information of market is characterized by the possibility distribution of the parameter in the demand function. Since the life cycle of the new product is short, how many products should be produced...

10. A Modified Support Vector Machine model for Credit Scoring

Xiaoyong Liu, Hui Fu, Weiwei Lin
Pages: 797 - 804
This paper presents a novel quantitative credit scoring model based on support vector machine (SVM) with adaptive genetic algorithm, gr-GA-SVM. In this study, two real world credit datasets in the University of California Irvine Machine Learning Repository are selected for the numerical experiments....

11. Developing a Mobile Service-Based Customer Relationship Management System Using Fuzzy Logic

Xiaobei Liang, Jianghua Zhang, Binyong Tang
Pages: 805 - 814
Customer relationship management (CRM) has gained lately widespread popularity in many industries. With the development of economy and society, customers are unsatisfied with the stereotyped products. As customers usually describe their demands in nature language, the demands are often conflicting with...

12. A Multi-Criteria Decision Model for Architecturing Competence in Human Performance Technology

Yasemin C. Erensal, Tuncay Gürbüz, Y. Esra Albayrak
Pages: 815 - 831
In a continuously changing environment, like globalization, technological innovation, restructuring and outsourcing, organizations can no longer cope without continually developing their competencies and human resources. As a result academic research and company practices have actively started to develop...

13. Comprehensive Learning Particle Swarm Optimizer for Constrained Mixed-Variable Optimization Problems

Lei Gao, Atekelty Hailu
Pages: 832 - 842
This paper presents an improved particle swarm optimizer (PSO) for solving multimodal optimization problems with problem-specific constraints and mixed variables. The standard PSO is extended by employing a comprehensive learning strategy, different particle updating approaches, and a feasibility-based...

14. Tunnel Surrounding Rock Displacement Prediction Using Support Vector Machine

Bao-zhen Yao, Jian Sun, Cheng-yong Yang, Jin-bao Yao
Pages: 843 - 852
Multi-step-ahead prediction of tunnel surrounding rock displacement is an effective way to ensure the safe and economical construction of tunnels. This paper presents a multi-step-ahead prediction model, which is based on support vector machine (SVM), for tunnel surrounding rock displacement prediction....

15. A hybrid algorithm to minimize makespan for the permutation flow shop scheduling problem

Fardin Ahmadizar, Farnaz Barzinpour
Pages: 853 - 861
This paper deals with the permutation flow shop scheduling problem. The objective is to minimize the maximum completion time, or makespan. To solve this problem which has been proved to be strongly NP-hard, a combination between an ant colony algorithm, a heuristic algorithm and a local search procedure...