Remote patient tracking has recently gained increased attention, due to its lower cost and non-invasive nature. In this paper, the performance of Support Vector Machines (SVM), Least Square Support Vector Machines (LS-SVM), Multilayer Perceptron Neural Network (MLPNN), and General Regression Neural Network (GRNN) regression methods is studied in application to remote tracking of Parkinson’s dis...

Diabetes has become a major threat to the life and it is getting common day by day and is having a fast increasing trend .Unhealthy practices in consumption of food have on a major side contributed to the rise of type 2 diabetes. In this paper we have tried to develop a method for the prediction of type 2 diabetes using adaptive neuro-fuzzy interface system (ANFIS) with genetic algorithms (GA)....

This paper presents the application of neural networks in software maintainability estimation using objectoriented metrics. Maintenance effort can be measured as the number of lines changed per class. In this paper, the number of lines changed per class (modification volume) is predicted using Ward neural network and General Regression neural network (GRNN). Object-oriented design metrics conce...

In the research of heat transfer, exchanger plays an important role in highly integrated and high-precision thermal management to ensure balance. previous studies, traditional experiments CFD simulations consume lots time computational resources, while transfer correlations have large errors. Hence, this aims establish a reliable method predict Heat Transfer Coefficient (HTC) exchange channels ...

The growth in electricity consumption the world forces countries to have a well-structured planning relation forecasting demand for their most diverse sectors. Several techniques are used predict electrical loads, such as artificial intelligence models, statistical models and hybrid models. This work aims present model based on combination of method, SARIMA, an neural network, GRNN, improve acc...

The basic aim of the present paper is to present a practical solution of an intelligent Business Class system of aiding decisionmaking in activity management processes of small energy sources functioning on the electricity market. The solution has been worked out by the authors of the paper. A hybrid approach combining SHELL applications and neural networks has been applied. This hybrid, togeth...

Several time delay estimates have been reported for the quasar Q0957+561. They come from distinct data sets and published separately. This paper presents a methodology to estimate a single time delay given several data sets by using multi-objective optimisation. We use General Regression Neural Networks (GRNN) to estimate the time delay, which is one of the most accurate time delay estimators –...

The analysis of pathological voice is a challenging and an important area of research in speech processing. Acoustic voice analysis can be used to characterize the pathological voices with the aid of the speech signals recorded from the patients. This paper presents a method for the identification and classification of pathological voice using Artificial Neural Network. Multilayer Perceptron Ne...

In this article, seven filter algorithms were compared. The Lee sigma method was more suitable for estimating soil moisture (SM) than the other filtering methods under different land cover types. First, we used a combination of roughness and dual-polarized Sentinel-1A backscattering coefficients (VV VH) to estimate SM in bare areas. Second, employed water cloud model (WCM) remove influence vege...