Quantum computational devices currently under development have the potential to accelerate data analysis techniques beyond ability of any classical algorithm. We propose application a quantum algorithm for detection unknown signals in noisy data. apply Grover's matched filtering, signal processing technique that compares number candidate templates. In comparison method, this provides speedup pr...

Presently, the introduction of intelligent models to optimize structural problems has become an important issue in civil engineering and almost all other fields of engineering. Optimization models in artificial intelligence have enabled us to provide powerful and practical solutions to structural optimization problems. In this study, a novel method for optimizing structures as well as solving s...

Gravitational edge detection is one of the new edge detection algorithms that is based on the law of gravity. This algorithm assumes that each image pixel is a celestial body with a mass represented by its grayscale intensity and their interactions are based on the Newtonian laws of gravity. In this article, a multispectral version of the algorithm is introduced. The method uses gravitational t...

This paper introduces an improved clustering algorithm GCA(Gravitational Clustering Algorithm ), it is extended in such a way that the Gravitational Law is not the only law that can be applied. This algorithm can decide automatically the number of clusters in the target data set, and find any clusters with arbitrary forms and filter the noisy data. The experimental results show that GCA algorit...

In this paper we briefly review the importance of LP (linear programming), and Dantzig’s main contributions to OR (Operations Research), mathematics, and computer science. In [11, 3] gravitational methods for LP have been introduced. Several versions exist. The three main versions discussed there use a ball of (a): 0 radius, (b): small positive radius, and (c): the ball of largest possible radi...

Gravitational search algorithm (GSA) is a new member of swarm intelligence algorithms. It stems from Newtonian law of gravity and motion. The performance of synchronous GSA (S-GSA) and asynchronous GSA (A-GSA) is studied here using statistical analysis. The agents in S-GSA are updated synchronously, where the whole population is updated after each member’s performance is evaluated. On the other...