The triple-frequency linear combination method can provide combinations with different characteristics and is one of the important methods to improve performance navigation services. Due large number performances, combinatorial clustering optimization very important, efficiency manual screening low. Firstly, based on basic model, objective equations are derived. Secondly, fuzzy c-means (FCM) al...

This paper, presents a new image segmentation method based on Wavelets, Particle Swarm Optimization (PSO) and outlier rejection caused by the membership function of the kernel fuzzy local information c-means (KFLICM) algorithm combined with level set is proposed. The segmentation of Magnetic Resonance (MR) images plays an important role in the computer-aided diagnosis and clinical research, but...

A mobile ad-hoc network (MANET) faces various challenges including limited energy, limited communication bandwidth, computation constraint and cost. Therefore, clustering of sensor nodes is adopted which involves selection of cluster-heads for each cluster. This enhances system performance by enabling bandwidth reuse, better resource allocation and improved power control. The various existing c...

Automatic detection systems in medical sciences improve the accuracy of the diagnosis and reduce the time of analysis. This field in lung disease referred to computer aided diagnosis (CAD) system. Lung nodule detection is the most important task of these systems. CAD systems used the combination of image processing techniques in order to detect the lung nodules. Lung CT image clustering is one ...

In order to overcome the premature convergence in the particle swarm optimization algorithm, dynamically chaotic perturbation is introduced to form a dynamically chaotic PSO, briefly denoted as DCPSO. To get rid of the drawbacks of simply finding the convex cluster and being sensitive to the initial partitions in k -means algorithm, a novel hybrid clustering algorithm combined with the DCPSO is...

In the field of economics and business, the ever increasing amount of text documents written in different languages and the ever increasing dependence of people and organisations on such information require effective document retrieval, searching and classification mechanisms. Searching for groups of related documents has an important role in text mining and Document Management Systems. Swarm i...

This paper presents a new stochastic nature inspired methodology, which is based on the concepts of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), for optimally clustering N objects into K clusters. Due to the nature of stochastic and population-based search, the proposed algorithm can overcome the drawbacks of traditional clustering methods. Its performance is compared wi...

For multi-objective optimal reactive power dispatch (MORPD), a new approach is proposed where simultaneous minimization of the active power transmission loss, the bus voltage deviation and the voltage stability index of a power system are achieved. Optimal settings of continuous and discrete control variables (e.g. generator voltages, tap positions of tap changing transformers and the number of...