Abstract Monitoring various Fish Species and its distribution of the species obtains a primary significance in receiving insights to marine ecological-system. After this, visual classification those would aid tracing out movement yield patterns trends fish activities, which provides depth knowledge species. Unconstrained under-water images pose highly variations because orientation changes, Lig...

This thesis describes an attempt to predict the next value in a financial time series using various artificial techniques. The time series in question consists of daily values for commodities futures. First, an artificial neural network is used as a predictor. Then the neural network is augmented with a genetic algorithm. The genetic algorithm first is used to select the parameters for the neur...

objective: in this study, artificial neural network (ann) analysis of virotherapy in preclinical breast cancer was investigated. materials and methods: in this research article, a multilayer feed-forward neural network trained with an error back-propagation algorithm was incorporated in order to develop a predictive model. the input parameters of the model were virus dose, week and tamoxifen ci...

This study was conducted to rate the land characteristics of corn in hot areas based on artificial neural networks and regression models. For this purpose, 63 corn fields were selected in southern Iran. In each farm, a pedon was excavated, described and sampled. A questionnaire was completed for each farm. A stepwise regression model was used to study the relationship between land characteristi...

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 ...

This paper presents the implementation of multiple distributed generations planning in distribution system using computational intelligence technique. A pre-developed computational intelligence optimization technique named as Embedded Meta EP-Firefly Algorithm (EMEFA) was utilized to determine distribution loss and penetration level for the purpose of distributed generation (DG) installation. I...

Due to today’s advancement in technology and businesses, fraud detection has become a critical component of financial transactions. Considering vast amounts of data in large datasets, it becomes more difficult to detect fraud transactions manually. In this research, we propose a combined method using both data mining and statistical tasks, utilizing feature selection, resampling and cost-...

with the increase of the volume of information and the progress in technology, the deficiency of traditional algorithms for fast information retrieval becomes more clear. when large volumes of data are to be handled, the use of neural network as an artificial intelligent technique is a suitable method to increase the information retrieval speed. neural networks present a suitable representation...