In its simplest form, the traffic flow prediction problem is restricted to predicting a single time-step into the future. Multi-step traffic flow prediction extends this set-up to the case where predicting multiple time-steps into the future based on some finite history is of interest. This problem is significantly more difficult than its single-step variant and is known to suffer from degradat...

This paper presents a comprehensive error analysis of the day-ahead photovoltaic (PV) production multi-step forecasting model that uses chained support vector regression (SVR). A principal component (PCA) is also implemented to investigate possible improvements SVR prediction accuracy. Special attention was given hyper-parameter tuning and PCA+SVR models; specifically, dispersion errors when fi...

Abstract Water security and urban flooding have become major sustainability issues. This paper presents a novel method to introduce rates of change as the state-of-the-art approach in artificial intelligence model development for agenda. Multi-layer perceptron (MLP) deep learning long short-term memory (LSTM) models were considered flood forecasting. Historical rainfall data from 2008 2021 at 1...