Pulp properties are key factors to assessing the performance of a refining process, evaluating operational conditions, and optimizing the process of stock preparation. This paper presents a data-driven approach to estimate the beating degree and wet weight of pulp after refining using case-based reasoning (CBR). Historical data generated in a refining process at a paper mill was used to evaluat...

The target of this research is to estimate the distribution global solar radiation (GSR) and reanalysis datasets (ERA-5) for development PV cost reduction predict level energy over five countries in North Africa during period time from 2011 2020. effectiveness African was evaluated against high-quality surfaces measured using statistical analysis. average values mean bias error (MBE), root squa...

Rainfall is considered as one of the major components of the hydrological process; it takes significant part in evaluating drought and flooding events. Therefore, it is important to have an accurate model for rainfall prediction. Recently, several data-driven modeling approaches have been investigated to perform such forecasting tasks as multilayer perceptron neural networks (MLP-NN). In fact, ...

This paper aims at evaluating volatility forecasts for the US Dollar/Mauritian Rupee exchange rate obtained via a GARCH (1,1) model under two distributional assumptions: the Generalized Error Distribution (GED) and the Student’s-t distribution. We make use of daily data to evaluate the parameters of each model and produce volatility estimates. The forecasting ability is subsequently assessed us...

The Root Mean Square-Deviation (RMSD) or Root Mean Square Error (RMSE) is the frequently used measure of the difference between values predicted by a model or an estimator and the values actually observed from that which is being modelled or estimated. In this paper, we show that the magnification of the RMSE, when used with the classifier Hopfield Neural Network (HNN), may help the network to ...

This paper puts forward a prediction model based on membrane computing optimization algorithm for chaos time series; the model optimizes simultaneously the parameters of phase space reconstruction (τ, m) and least squares support vector machine (LS-SVM) (γ, σ) by using membrane computing optimization algorithm. It is an important basis for spectrum management to predict accurately the change tr...

The error in a designed experiment, σ2, is the natural variation in the response when one of the experimental combinations is replicated. One important challenge in a designed experiment is obtaining an unbiased estimate of σ2. Too often, experimenters do not realize the impact that data collection and analysis assumptions have on the estimate of σ2. If the estimate is biased, tests of the effe...

Horizontal directional drilling (HDD) is widely used in soil and rock engineering. In a variety of conditions, it is necessary to estimate the torque required for performing the reaming operation. Nevertheless, there is not presently a convenient method to accomplish this task. In this paper, to overcome this difficulty based on the basic concepts of rock engineering systems (RES), a model for ...

The refrigeration cycle of an air source heat pump system is important information that reveals critical operating data, such as the cooling capacity, power consumption, and performance a during operation. Operating refrigerant pressure enthalpy in situ, can be difficult to measure. Therefore, this study developed situ measurement method using airside data pump. A for measuring proposed charact...