Tutorial Review Neural networks in multivariate calibration
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"Technical Report" Performance Comparison of IHACRES Model and Artificial Neural Network to Predict the Flow of Sivand River
The accurate determination of river flow in watersheds without sufficient data is one of the major challenges in hydrology. In this regard, given the diversity of existing hydrological models, selection of an appropriate model requires evaluation of the performance of the hydrological models in each region. The objective of this study was to compare the performance of artificial neural network ...
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In some statistical process control applications, the quality of the product is characterized by thecombination of both correlated variable and attributes quality characteristics. In this paper, we propose anovel control scheme based on the combination of two multi-layer perceptron neural networks forsimultaneous monitoring of mean vector as well as the covariance matrix in multivariate-attribu...
متن کاملQuantitative analysis of multivariate data using artificial neural networks: a tutorial review and applications to the deconvolution of pyrolysis mass spectra.
The implementation of artificial neural networks (ANNs) to the analysis of multivariate data is reviewed, with particular reference to the analysis of pyrolysis mass spectra. The need for and benefits of multivariate data analysis are explained followed by a discussion of ANNs and their optimisation. Finally, an example of the use of ANNs for the quantitative deconvolution of the pyrolysis mass...
متن کاملOnline Monitoring and Fault Diagnosis of Multivariate-attribute Process Mean Using Neural Networks and Discriminant Analysis Technique
In some statistical process control applications, the process data are not Normally distributed and characterized by the combination of both variable and attributes quality characteristics. Despite different methods which are proposed separately for monitoring multivariate and multi-attribute processes, only few methods are available in the literature for monitoring multivariate-attribute proce...
متن کاملPredicting peak particle velocity by artificial neural networks and multivariate regression analysis - Sarcheshmeh copper mine, Kerman, Iran
Ground vibrations caused by blasting are undesirable results in the mining industry and can cause serious damage to the nearby buildings and facilities; therefore, controlling such vibrations has an important role in reducing the environmental damaging effects. Controlling vibration caused by blasting can be achieved once peak particle velocity (PPV) is predicted. In this paper, the values of P...
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تاریخ انتشار 1996