Annalen der PhysikVolume 535, Issue 9 2370017 Cover PictureFree Access (Ann. Phys. 9/2023) First published: 08 September 2023 https://doi.org/10.1002/andp.202370017AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text full-text accessPlease review our Terms and Conditions of Use check box below share version article.I have read accep...

This paper presents artificial neural network (ANN)-based models for forecasting precipitation, in which the training parameters are adjusted using a parameter automatic calibration (PAC) approach. A classical ANN-based model, the multilayer perceptron (MLP) neural network, was used to verify the utility of the proposed ANN–PAC approach. The MLP-based ANN used the learning rate, momentum, and n...

soil hydraulic properties such as saturated and unsaturated hydraulic conductivity play an important role in environmental research. since direct measurement of these soil hydraulic properties is time-consuming and costly, indirect methods such as pedotransfer functions and artificial neural networks (ann) were developed based on readily available parameters. in this study, the use of ann to pr...

This paper presents overview of applications of artificial neural networks (ANN) in the field of engine development. Various approaches using ANN are highlighted that resulted in better modeling of engine operations. Using ANN we can reduce engine development time. The paper discusses ANN approach, algorithms and importance of architecture. This will also help in advancing ANN research.