Hossein Nezamabadi-pour

Learn More
In recent years, various heuristic optimization methods have been developed. Many of these methods are inspired by swarm behaviors in nature. In this paper, a new optimization algorithm based on the law of gravity and mass interactions is introduced. In the proposed algorithm, the searcher agents are a collection of masses which interact with each other(More)
Gravitational search algorithm is one of the new optimization algorithms that is based on the law of gravity and mass interactions. In this algorithm, the searcher agents are a collection of masses, and their interactions are based on the Newtonian laws of gravity and motion. In this article, a binary version of the algorithm is introduced. To evaluate the(More)
In this paper a new algorithm for edge detection using ant colony search is proposed. The problem is represented by a directed graph in which nodes are the pixels of an image. To adapt the problem, some modifications on original ant colony search algorithm (ACSA) are applied. A large number of experiments are employed to determine suitable algorithm(More)
In this paper, a new thresholding function is proposed for image denoising in the wavelet domain. The proposed function is further used in a new subband-adaptive thresholding neural network to improve the efficiency of the denoising procedure. Some new adaptive learning types are also proposed. In these learning methods, the threshold and the thresholding(More)
In this paper, we present a new and effective image indexing technique that extracts features directly from DCT domain. Our proposed approach is an object-based image indexing. For each block of size 8*8 in DCT domain a feature vector is extracted. Then, feature vectors of all blocks of image using a kmeans algorithm is clustered into groups. Each cluster(More)
Gravitational search algorithm (GSA) has been recently presented as a new heuristic search algorithm with good results in real-valued and binary encoded optimization problems which is categorized in swarm intelligence optimization techniques. The aim of this article is to show that GSA is able to find multiple solutions in multimodal problems. Therefore, in(More)
This paper presents a new approach to economic dispatch (ED) problems with nonsmooth cost functions using a particle swarm optimization (PSO) technique. The practical ED problems have nonsmooth cost functions with equality and inequality constraints, which makes the problem of finding the global optimum difficult when using any mathematical approaches. In(More)