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Clustering, a well-known technique, is used to divide a data set into number of groups, called clusters. Differential evolution and particle swarm optimization are robust, fast and very effective search techniques. To increase computational capability, two different quantum inspired meta-heuristics for automatic clustering, have been proposed here. An application of quantum inspired techniques has...
Millions of users harvest their personal information (photo, video, status) on different online social networks (OSNs). Hence, these rich repositories of sensitive information attract the eyes of adversary to launch variety of cyber attacks on OSN. Here we have identified all crucial threats on social network that may lead to severe risks. In this paper, we have formalized possible social network...
Clustering is a simple technique to make partition of given data set into number of clusters. This paper presents an quantum inspired algorithm using GA to automatically find the number of clusters for image data set. The advantage lies in this technique is that no previous information about the data set used for classification is required before hand. The method decides the optimum cluster number...
In this paper, two quantum behaved multi-objective optimization techniques, based on Binary Particle Swarm Optimization and Ant Colony Optimization, have been introduced. The proposed approaches are used to search optimal threshold values of gray scale images, by optimizing the non-dominated solutions using Li's method as objective function. These approaches coalesce the meta-heuristic algorithms...
In this article, a Quantum Inspired Tabu Search for Multi-level thresholding for Colour Image has been developed to boost the possible effectiveness than that of its classical counterpart. The proposed algorithm has been applied to two true colour images to determine optimal threshold values at different levels using Otsu's method as an objective function. The features of quantum mechanics are coupled...
In this article, the particle swarm optimization and differential evolution algorithms inspired by the intrinsic principles of quantum mechanics are presented. These quantum versions of meta-heuristic algorithms, namely quantum inspired particle swarm optimization and quantum inspired differential evolution for multi-level thresholding have been designed to find optimal thresholds of colour images...
Thresholding is a simple, effective and popular method for image segmentation. It can be bi-level or multi-level depending on number of segments in an image. Multi-level thresholding computationally takes more time than the bi-level thresholding. To reduce the computational complexity, here we propose two quantum inspired meta-heuristic methods, namely Quantum Inspired Ant Colony Optimization and...
A genetic algorithm inspired by the inherent features of parallelism and time discreteness exhibited by quantum mechanical systems, is presented in this article. The predominant interference operator in the proposed quantum inspired genetic algorithm (QIGA) is influenced by time averages of different random chaotic map models derived from the randomness of quantum mechanical systems. Subsequently,...
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