This paper proposes artificial neural network (ANN) and regression models for photovoltaic
modules power output predictions and investigates the effects of climatic conditions and …

The ability to predict solid particle erosion is a vital task for the integrity management of
pipelines carrying solid particles in many industries. Usually, the accuracy of predicted …

Validation is an essential procedure in the development of a predictive model in several
engineering fields. In addition, recent data analysis techniques and the increasing …

Purpose Experiments are the backbone of the development process of data-driven
predictive models for scientific applications. The quality of the experiments directly impacts …

Confidence in erosion model predictions is crucial for their effective use in design and
operation of pipelines in upstream oil and gas industry. Accurate and precise estimates of …

Uncertainties are part of any scientific measurements and calculations. As a complex
phenomenon, erosion is affected by many independent parameters and consequently the …

Predictive models have a pervasive role in many daily applications. The increasing amount
of generated and shared data has recently boosted their development, shifting the model …

Surrogate models are used to map input data to output data when the actual relationship
between the two is unknown or computationally expensive to evaluate (Han & Zhang, 2012) …