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 ...

A precise short-term load forecasting technique is required for the economic and reliable operation of power system. Modern load forecasting techniques especially ANN methods are attractive as they have the ability to handle the non-linear relationships between load, weather temperature and the factors affecting it directly. In this paper, an investigation on the use of ANN for short term load ...

This paper proposes a data-driven graphical framework for the real-time search of risky cascading fault chains (FCs). While identifying FCs is pivotal to alleviating failures, complex spatio-temporal dependencies among components power system render challenges modeling and analyzing FCs. Furthermore, faces an inherent combinatorial complexity that grows exponentially with size system. The propo...

The research on the sustainability evaluation of innovation and entrepreneurship education for clean energy majors in colleges universities can not only cultivate more better innovative entrepreneurial talents development sustainable but also provide a reference other majors. To achieve systematic comprehensive scientific evaluation, this paper proposes an model based SPA-VFS Chaos bat algorith...

In vitro rooting as one of the most critical steps micropropagation is affected by various extrinsic (e.g., medium composition, auxins) and intrinsic factors species, explant). Passiflora in adventitious a difficult, complex, non-linear process. Since multivariable complex biological process, efficient reliable computational approaches such machine learning (ML) are required to model, predict, ...

this paper presents the application of three main artificial neural networks (anns) in damage detection of steel bridges. this method has the ability to indicate damage in structural elements due to a localized change of stiffness called damage zone. the changes in structural response is used to identify the states of structural damage. to circumvent the difficulty arising from the non-linear n...

in the present study, sodium alginate microparticle for oral delivery of furosemide was designed whether the encapsulation into microparticles might improve the oral absorption of this potent loop diuretic. we described preparation of microspheres based on ionotropic gelation method and characterized its physicochemical properties. to acquire an optimum formulation, a generalized regression neu...