International Journal of Computational Intelligence Systems

Volume 7, Issue 2, April 2014

1. Fast Support Vector Machine Classification for Large Data Sets

Xiaoou Li, Wen Yu
Pages: 197 - 212
Normal support vector machine (SVM) algorithms are not suitable for classification of large data sets because of high training complexity. This paper introduces a novel two-stage SVM classification approach for large data sets. Fast clustering techniques are introduced to select the training data from...

2. Curve-Fitting on Graphics Processors Using Particle Swarm Optimization

R. T. Kneusel
Pages: 213 - 224
Curve fitting is a fundamental task in many research fields. In this paper we present results demonstrating the fitting of 2D images using CUDA (compute unified device architecture) on NVIDIA graphics processors via particle swarm optimization (PSO). Particle swarm optimization is particularly well-suited...

3. Ensemble of Kernel Regression Models for Assessing the Health State of Choke Valves in Offshore Oil Platforms

Piero Baraldi, Enrico Zio, Francesca Mangili, Giulio Gola, Bent H. Nystad
Pages: 225 - 241
This paper considers the problem of erosion in choke valves used on offshore oil platforms. A parameter commonly used to assess the valve erosion state is the flow coefficient, which can be analytically calculated as a function of both measured and allocated parameters. Since the allocated parameter...

4. A Content Based Video Retrieval Analysis System with Extensive Features by Using Kullback-Leibler

R. Priya, T.N. Shanmugam, R. Baskaran
Pages: 242 - 263
Content-based video retrieval systems have shown great potential in supporting decision making in clinical activities, teaching, and biological research. In content-based video retrieval, feature combination plays a key role. As a result content-based retrieval of all different type video data turns...

5. The fuzzy mapping aggregation operator based on rimer and its application

Xiaoping Qiu, Ming Jian, Jun Liu, Yi Wang, Yang Xu
Pages: 264 - 271
A fuzzy mapping aggregation operator based on RIMER and its application in Chinese word semantic proofing system for special domain are discussed deeply in this paper. Firstly, the fuzzy mapping aggregation operator based on RIMER are introduced and followed by the corresponding fuzzy inference method....

6. Ensemble ANNs-PSO-GA Approach for Day-ahead Stock E-exchange Prices Forecasting

Yi Xiao, Jin Xiao, Fengbin Lu, Shouyang Wang
Pages: 272 - 290
Stock e-exchange prices forecasting is an important financial problem that is receiving increasing attention. This study proposes a novel three-stage nonlinear ensemble model. In the proposed model, three different types of neural-network based models, i.e. Elman network, generalized regression neural...

7. An Approach to Multiple Attribute Group Decision Making Based on Intuitionistic Trapezoidal Fuzzy Power Generalized Aggregation Operator

Peide Liu, Ying Liu
Pages: 291 - 304
With respect to multiple attribute decision making (MADM) problems in which the attribute value takes the form of intuitionistic trapezoidal fuzzy number, a new decision making analysis method is developed. Firstly, some operational laws and expected values of intuitionistic trapezoidal fuzzy numbers,...

8. Approximate cycles count in undirected graphs

Maytham Safar, Khaled Mahdi, Hisham Farahat, Saud Albehairy, Ali Kassem, Khalid Alenzi
Pages: 305 - 311
In social networks, counting the number of different cycle sizes can be used to measure the entropy of the network that represents its robustness. The exact algorithms to compute cycles in a graph can generate exact results but they are not guaranteed to run in a polynomial time. We present an approximation...

9. A multi-affinity model for logistics network inspired by bio-system

Zhi-Hua Hu, Zhao-Han Sheng
Pages: 312 - 326
How can we deal with the increasing scale of large logistics network for the booming economy? The structure, mechanisms and principles upon the logistics network show an evolutionary tendency which is complex, and interesting for designing and optimizing logistics network. The adaptability, stability...

10. An Integrated Intuitionistic Fuzzy Similarity Measures for Medical Problems

Kuo-Chen Hung, Pei-Kuang Wang
Pages: 327 - 343
The purpose of this paper is to develop an integrated similarity measures model based on intuitionistic fuzzy sets. This integrated model has improved two similarity measures methods: (1) Ye (, 53, 91-97 (2011)) presented a novel cosine similarity measures method for handling pattern recognition problems...

11. Ischemia classification via ECG using MLP neural networks

J.I. Peláez, J.M. Doña, J.F. Fornari, G Serra
Pages: 344 - 352
This paper proposes a two stage system based in neural network models to classify ischemia via ECG analysis. Two systems based on artificial neural network (ANN) models have been developed in order to discriminate inferolateral and anteroposterior ischemia from normal electrocardiogram (ECG) and other...

12. Seeker Optimization Algorithm for Several Practical Applications

Yunfang Zhu, Chaohua Dai, Weirong Chen
Pages: 353 - 359
Optimization problems can often be simplified to the search for an optimal solution in the feasible search space. Based on the concept of simulating the act of human randomized search, a novel algorithm called seeker optimization algorithm (SOA) for real-parameter optimization is proposed in this paper....

13. An Atanassov's intuitionistic Fuzzy Kernel Clustering for Medical Image segmentation

Tamalika Chaira, Anupam Panwar
Pages: 360 - 370
This paper suggests a novel method for medical image segmentation using kernel based Atanassov's intuitionistic fuzzy clustering. The widely used fuzzy c means clustering that uses Euclidean distance has many limitations in clustering the regions accurately. To overcome these difficulties, we introduce...

14. An Emotion-oriented Music Recommendation Algorithm Fusing Rating and Trust

Jiwei Qin, Qinghua Zheng, Feng Tian, Deli Zheng
Pages: 371 - 381
With the overwhelming increase of music, it has become difficult to find music which suits the taste of a listener who is in a certain state of emotion. Focusing on the listener's emotional state, this paper presents an emotion-oriented music recommendation algorithm. First, the listener's similarity...

15. Filtration of Non-Monotonic Rules for Fuzzy Rule Base Compression

Alexander Gegov, Neelamugilan Gobalakrishnan, David Sanders
Pages: 382 - 400
This paper proposes a rule base compression method for fuzzy systems. The method is based on filtration of rules with identical linguistic values for the output that are known as non-monotonic rules. The filtration removes the redundant computations in the fuzzy inference with respect to the crisp values...