Hybrid ANN optimized artificial fish swarm algorithm based classifier for classification of suspicious lesions in breast DCE-MRI

A Hybrid Clustering Algorithm Based on Improved Artificial Fish Swarm

K-medoids clustering algorithm is used to classify data, but the approach is sensitive to the initial selection of the centers and the divided cluster quality is not high. Basic Artificial Fish Swarm Algorithm is a new type of heuristic swarm intelligence algorithm, but optimization is difficult to get a very high precision due to the randomness of the artificial fish behavior. A novel clusteri...

A Multiple Classifier System for Classification of Breast Lesions Using Dynamic and Morphological Features in DCE-MRI

AN IMPROVED INTELLIGENT ALGORITHM BASED ON THE GROUP SEARCH ALGORITHM AND THE ARTIFICIAL FISH SWARM ALGORITHM

This article introduces two swarm intelligent algorithms, a group search optimizer (GSO) and an artificial fish swarm algorithm (AFSA). A single intelligent algorithm always has both merits in its specific formulation and deficiencies due to its inherent limitations. Therefore, we propose a mixture of these algorithms to create a new hybrid optimization algorithm known as the group search-artif...

An Artificial Fish Swarm Optimized Fuzzy Mri Image Segmentation Approach for Improving Identification of Brain Tumour

In image processing, it is difficult to detect the abnormalities in brain especially in MRI brain images. Also the tumor segmentation from MRI image data is an important; however it is time consuming while carried out by medical specialists. A lot of methods have been proposed to solve MR images problems, quite difficult to develop an automated recognition system which could process on a large ...

A Short-Term Prediction Model Based on Support Vector Regression Optimized by Artificial Fish-Swarm Algorithm

In urban management, it is important to precisely forecast the short-term demand for necessary resources, including water, electric power, and gas. Although a variety of prediction models have been proposed in literature, the underlying defects and limitations confine the effectiveness and forecasting precision of these models. In this paper, the shortterm prediction problem is modeled as a non...