In this paper, two types of Artificial Neural Network (ANNs), Generalized Regression Neural Network (GRNN) and Radial Basis Function (RBF) have been used for heart disease to prescribe the medicine. Diagnosing the heart disease and prescribing the medicine on the basis of symptoms is a very challenging task to improve the ability of the physicians. The training capacity and medicines provided b...

The society is fully aware of the needs of impaired people. One such impairment resulting due to articulatory or congenital conditions in human speech production mechanism produces a disordered speech. This disordered speech is difficult to interpret and leads to miscommunication. Thus, the speech enabled helping aid is a good alternative to existing devices designed to assist the impaired spea...

In order to control the power plant accurately, exact models of the reheater and attemperator are needed. But sometimes due to a lack of needful information and complex internal structure of the system, it is unadvisable to establish the dynamics model based on energy mass balance, physical rules and thermodynamics principles. In this paper, a generalized regression neural network(GRNN) is deve...

Proposing a new precise price forecasting method is still challenging task as electricity signals generally exhibit various complex features. In this paper, approach for called hybrid local general regression neural network, and harmony search algorithm (LGRNN-HSA) proposed. The proposed LGRNN-HSA developed by combining the coordinate delay (CD) method, paradigm, network (GRNN) (HSA). CD employ...

Water vapor plays an important role in climate change and water cycling, but there are few products with both high spatial resolution accuracy that effectively monitor the of vapor. The precision Global Navigation Satellite System (GNSS) Precipitable Vapor (PWV) is often used to calibrate Moderate-resolution Imaging Spectroradiometer (MODIS) PWV produce new product resolution. In addition, mach...

Recently, neural network models for natural language processing tasks have been increasingly focused on for their ability of alleviating the burden of manual feature engineering. However, the previous neural models cannot extract the complicated feature compositions as the traditional methods with discrete features. In this paper, we propose a gated recursive neural network (GRNN) for Chinese w...

This study compares and evaluates the prediction of hepatitis in Guangxi Province, China by using back propagation neural networks based genetic algorithm (BPNN-GA), generalized regression neural networks (GRNN), and wavelet neural networks (WNN). In order to compare the results of forecasting, the data obtained from 2004 to 2013 and 2014 were used as modeling and forecasting samples, respectiv...

This paper deals with the problem of robust and perceptual logo watermarking for colour images. In particular, we investigate trade-off factors in designing efficient watermarking techniques to maximize the quality of watermarked images and the robustness of watermark. With the fixed size of a logo watermark, there is a conflict between these two objectives, thus a multiobjective optimization p...

Artificial neural network (ANN) based prediction of the response of a microbend fiber optic sensor is presented. To the best of our knowledge no similar work has been previously reported in the literature. Parallel corrugated plates with three deformation cycles, 6 mm thickness of the spacer material and 16 mm mechanical periodicity between deformations were used in the microbend sensor. Multil...

The aim of this study is to predict breast cancer and to construct a supportive model that will stimulate a more reliable prediction as a factor that is fundamental for public health. In this study, we utilize general regression neural networks (GRNN) to replace the normal predictions with prediction periods to achieve a reasonable percentage of confidence. The mechanism employed here utilises ...