International Journal of Computational Intelligence Systems

Volume 8, Issue 6, December 2015
Research Article

1. Polynomial Based Functional Link Artificial Recurrent Neural Network adaptive System for predicting Indian Stocks

D.K. Bebarta, Birendra Biswal, P.K. Dash
Pages: 1004 - 1016
A low complexity Polynomial Functional link Artificial Recurrent Neural Network (PFLARNN) has been proposed for the prediction of financial time series data. Although different types of polynomial functions have been used for low complexity neural network architectures earlier for stock market prediction,...
Research Article

2. A group selection approach to supplier collaborative configuration problems with correlation of experts and attributes

Haihan Chen
Pages: 1017 - 1026
Enterprises nowadays are often confronted with selecting supplier collaborative configuration problems in supply chain management. The aim of this paper is to develop a group selection methodology with the correlation of experts and attributes for solving supplier collaborative configuration problems....
Research Article

3. An Improved Weighted Correlation Coefficient Based on Integrated Weight for Interval Neutrosophic Sets and its Application in Multi-criteria Decision-making Problems

Hong-yu Zhang, Pu Ji, Jian-qiang Wang, Xiao-hong Chen
Pages: 1027 - 1043
This paper presents a new correlation coefficient measure, which satisfies the requirement of this measure equaling one if and only if two interval neutrosophic sets (INSs) are the same. And an objective weight of INSs is presented to unearth and utilize deeper information that is uncertain. Using the...
Research Article

4. A New Adaptive Genetic Algorithm and Its Application in the Layout problem

Lei Wu, Wensheng Xiao, Jingli Wang, Houqiang Zhou, Xue Tian
Pages: 1044 - 1052
Genetic algorithm (GA) is a search algorithm based on the theory of Darwin. For the purpose of improving the convergent rate and maintaining the population diversity in GA, this paper presents a new genetic operator called trisecting group and directional selection mechanism (TDGA), in which the worst...
Research Article

5. An adaptive local search with prioritized tracking for Dynamic Environments

A.D. Masegosa, E. Onieva, P. Lopez-Garcia, E. Osaba, A. Perallos
Pages: 1053 - 1075
Dynamic Optimization Problems (DOPs) have attracted a growing interest in recent years. This interest is mainly due to two reasons: their closeness to practical real conditions and their high complexity. The majority of the approaches proposed so far to solve DOPs are population-based methods, because...
Research Article

6. Context-Based Method Using Bayesian Network in Multimodal Fission System

Atef Zaguia, Chakib Tadj, Amar Ramdane-Cherif
Pages: 1076 - 1090
The current technological advancement has created the need to produce machines more powerful, easy to use and to meet the needs of users. To achieve this goal, multimodal systems have been developed to combine multiple modalities depending on the task, preferences and communicative intentions of the...
Research Article

7. Materialized View Selection Based on Adaptive Genetic Algorithm and Its Implementation with Apache Hive

Dongjin Yu, Wensheng Dou, Zhixiang Zhu, Jiaojiao Wang
Pages: 1091 - 1102
Frequently accessed views in data warehouses are usually materialized in order to accelerate the speed of querying big data. However, the view materialization itself incurs huge costs. Moreover, some latest products of non-traditional data warehouse software, such as Apache Hive, still lack the support...
Research Article

8. Birkhoff's aesthetics, Arnheim's entropy. Some remarks on complexity and fuzzy entropy in arts

Marco Elio Tabacchi, Settimo Termini
Pages: 1103 - 1115
A judgement of aesthetic in arts is, by sheer consensus, a daunting task that requires evaluation of a whole host of endogenous and exogenous cultural factors. A few of them can actually provide very useful hints in tackling foundational problems in Information Science in a more natural setting than...
Research Article

9. Secure and Efficient Biometric-Data Binarization using Multi-Objective Optimization

Eslam Hamouda, Xiaohui Yuan, Osama Ouda, Taher Hamza
Pages: 1116 - 1127
Biometric system databases are vulnerable to many types of attacks. To address this issue, several biometric template protection systems have been proposed to protect biometric data against unauthorized use. Many of biometric protection systems require the biometric templates to be represented in a binary...
Research Article

10. Computational Intelligence-based Entertaining Level Generation for Platform Games

Zahid Halim, Abdul Rauf Baig, Ghulam Abbas
Pages: 1128 - 1143
With computers becoming ubiquitous and high resolution graphics reaching the next level, computer games have become a major source of entertainment. It has been a tedious task for game developers to measure the entertainment value of the computer games. The entertainment value of a game does depend upon...
Research Article

11. Improving Meta-learning for Algorithm Selection by Using Multi-label Classification: A Case of Study with Educational Data Sets

Juan Luis Olmo, Cristóbal Romero, Eva Gibaja, Sebastián Ventura
Pages: 1144 - 1164
Recommending classification algorithms is an open research problem the solution to which is of tremendous value for practitioners and non-experts data mining users such as educators. This paper proposes a new meta-learning framework for educational domains based on the use of multi-label learning for...
Research Article

12. A Cognitive Method for Musicology Based Melody Transcription

Jiayin Sun, Hongyan Wang
Pages: 1165 - 1177
This paper describes a method for transcribing the main structure of polyphonic music audio automatically by analyzing musical tonality related musicological information. Music transcription is a difficult topic in Music Information Retrieval (MIR) which contains many tasks to recognize all the elements...
Research Article

13. DisCoSet: Discovery of Contrast Sets to Reduce Dimensionality and Improve Classification

Zaher Al Aghbari, Imran N. Junejo
Pages: 1178 - 1191
Traditionally, contrast set mining aims at finding a set of rules that best distinguish the instances of different user-defined groups. Contrast sets are conjunctions of attribute-value pairs that are significantly more frequent in one group than in other groups. Typically, these contrast sets are extracted...
Research Article

14. Some Advantages of the RDM-arithmetic of Intervally-Precisiated Values

Andrzej Piegat, Marcin Plucinski
Pages: 1192 - 1209
Moore's interval arithmetic always provides the same results of arithmetic operations, e.g. [1, 3]+ [5, 9]= [6, 12]. But in real life problems, the operation result can be different, e.g. equal to [4, 7]. Therefore, real problems require more advanced arithmetic. The paper presents (on example of the...