Esmat Rashedi

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)
Parameter tuning has critical influences on the performance of evolutionary algorithms. Deliberate parameter investigation and changing the value of them is very expensive and time consuming. This paper has applied Design of Experiment (DOE) method to tune the parameters of Gravitational Search Algorithms (GSA) systematically. Also, to reduce its complexity(More)
Content based image retrieval (CBIR) systems could provide more precise results by taking the user’s feedbacks into account. Two types of the relevance feedback learning paradigms are short term learning (STL) and long term learning (LTL). By using both STL and LTL, a collaborative CBIR system is proposed in this paper. The proposed system introduced three(More)