Machine learning (ML) has been utilized to predict climatic parameters, and many successes have reported in the literature. In this paper, we scrutinize effectiveness of five widely used ML algorithms monthly prediction seasonal parameters using image data. Specifically, quantify predictive performance these applied various combinations features. We compare accuracy resulting trained models tha...

Precise streamflow forecasting is crucial when designing water resource planning and management, predicting flooding, reducing flood threats. This study invented a novel approach for the monthly of Tigris River in Amarah City, Iraq, by integrating an artificial neural network (ANN) with particle swarm optimisation algorithm (PSO), depending on data preprocessing. Historical were utilised from (...

introduction rainfall is considered as one of the most important factures in water cycle. prediction of monthly rainfall is important for many purposes such as estimating torrent, drought, run-off, sediment, irrigation programming and also management of drainage basins. rainfall prediction in each area is mediated by punctual data measured as humidity, temperature, wind speed and etc. as iran i...