Since the middle of the twentieth century, artificial intelligence (AI) models have been used
widely in engineering and science problems. Water resource variable modeling and …

Reliable and precise prediction of the rivers flow is a major concern in hydrologic and water
resources analysis. In this study, multi-linear regression (MLR) as a statistical method …

Ensemble machine learning models have been widely used in hydro-systems modeling as
robust prediction tools that combine multiple decision trees. In this study, three newly …

Eight data-driven models and five data pre-processing methods were summarized; the
multiple linear regression (MLR), artificial neural network (ANN) and wavelet decomposition …

Smart systems can be appropriately coordinated in industries to monitor and control the
performance of wastewater treatment plants to regulate their pollutant discharge levels …

Rainfall prediction is a very challenging task due to its dependence on many meteorological
parameters. Because of the complex nature of rainfall, the uncertainty associated with its …

In this paper, an integrated model based on efficient extreme learning machine (EELM) and
differential evolution (DE) is proposed to predict chaotic time series. In the proposed model …

Accurate streamflow forecasting is of great importance for the effective management of water
resources systems. In this study, an improved streamflow forecasting approach using the …

Grinding is a critical machining process because it produces parts of high precision and high
surface quality. Due to the semi-artisan production of the wheel, it is not possible to know in …

Modeling of mean monthly flow is of particular importance for long-term planning of
processes relying on water abstraction, such as reservoir operations. Advantage of data …