International Journal of Computational Intelligence Systems

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...

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...

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...

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...

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....

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...

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,...

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...

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...

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...

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...

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....

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...

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...

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...