Artificial Neural NetworksAvailable Parameter PickingPattern BuildingPattern CheckingThis chapter is dedicated to the scope of which facts should be considered when deciding whether a Neural Network (NN) solution is suitable to solve a given problem. This is followed by a detailed example of a ...
Artificial neural networks show potential for modeling the behavior of complex nonlinear processes, such as those involved in the occurrence of breakup ice jams. Because breakup ice jams and related flooding occur suddenly, ice jam prediction methods are desirable to provide early warning and to allow...
Application of neural networks to adaptive control of nonlinear systems G.W. Ng (UMIST Control Systems Centre series, 4) Research Studies Press , J. Wiley... R Ballini,FJV Zuben - Research Studies press LTD ; John Wiley & Sons INC 被引量: 1发表: 2000年 Application Of Neural Networks To...
This paper presents the application of neural networks in software quality estimation using object-oriented metrics. In this paper, two kinds of investigation are performed. The first on predicting the number of defects in a class and the second on predicting the number of lines changed per class...
The purpose of this paper is to investigate the use of neural networks and fuzzy logic in the modelling and control of an industrial fed-batch fermentation process. The reason why we choose neural networks and fuzzy logic for this application is because of the nature of the fermentation process...
Herein the use of Convolutional Neural Networks (CNNs) is investigated to interpret fluorescence spectra and predict the formation of disinfection by-products during drinking water treatment. Using deep CNNs, mean absolute prediction error on a test set of data for total trihalomethanes, total ...
The results of this study suggested that the CNN model, the Grad-CAM, and the dimension reductions are useful for evaluating frictional features of tribofilms formed from multiple lubricant additives.Similar content being viewed by others Investigation of multi-input convolutional neural networks for ...
of large models on large datasets, the ability to perform speaker adaptation and the development of discriminative techniques to train the GMM/HMM models. The performance of neural networks based approaches could theoretically have been improved further by using neural networks with more parameters. It...
1Vol.:(0123456789)Scientif i c Reports | (2022) 12:612 | https://doi.org/10.1038/s41598-021-03881-wwww.nature.com/scientificreportsApplication of convolutional neural networks for prediction of disinfection by‑productsNicolás M. PeleatoFluorescence spectroscopy can provide high‑level chemical ...
A neural network is used to generate control parameters for a parallel formant speech synthesizer, corresponding to a sequence of allophonic tokens. Training is to be accomplished using formant data obtained from both natural and synthetic speech. It is intended that theories of cognitive phonetics, ...