Fuzzy clustering is a popular unsupervised learning method used in cluster analysis which allows a point in large data sets belongs to two or more clusters. Prior work suggests that Particle Swarm Optimization based approach could be a powerful tool for solving clustering problems. In this paper, we propose a data clustering algorithm based on modified adaptive particle swarm optimization. We c...

Particle swarm optimization is a popular method for solving difficult optimization problems. There have been attempts to formulate the method in formal probabilistic or stochastic terms (e.g. bare bones particle swarm) with the aim to achieve more generality and explain the practical behavior of the method. Here we present a Bayesian interpretation of the particle swarm optimization. This inter...

It is well known that solutions of k-means algorithm depend on the initialization of cluster centers and the final solution converges to local minima. In this paper, we introduce a clustering approach that combines ideas from modified particle swarm optimization (PSO) and k-means. The potential benefits of this technique are investigated by incorporating the multidimensional asynchronism and st...

Clustering is an unsupervised process that divides a given set of objects into groups so that objects within a cluster are highly similar with one another and dissimilar with the objects in other clusters. In this article, a new clustering method based on cat swarm optimization was proposed to find the proper clustering of data sets called K-means improvement and Simulated Annealing selection b...

In optimizing the particle swarm optimization (PSO) that inevitable existence problem of prematurity and the local convergence, this paper base on this aspects is put forward a kind of modified particle swarm optimization algorithm, take the gradient descent method (BP algorithm) as a particle swarm operator embedded in particle swarm algorithm, and at the same time use to attenuation wall (Dam...

High performance concrete is designed to meets special requirements such as high strength, high flowability, and high durability in large scale concrete construction. To obtain such performance many trial mixes are required to find desired combination of materials and there is no conventional way to achieve proper mix proportioning. Genetic algorithm is a global optimization technique based ...

Pattern recognition has as its objective to classify objects into different categories and classes. It is a fundamental component of artificial intelligence and computer vision. This thesis investigates the application of an efficient optimization method, known as Particle Swarm Optimization (PSO), to the field of pattern recognition and image processing. First a clustering method that is based...

in recent years, wavelet packet modulation ofdm (wpm-ofdm) signals have been introduced for radar applications. these signals have important properties such as inherent high range resolution and high resistance of radar system against jamming reception. this paper investigates the problem of designing these family of signals according to the following criteria: constrained maximization of the d...