In time series predictor evaluation, we observe that with respect to the model selection
procedure there is a gap between evaluation of traditional forecasting procedures, on the …

The primary purpose of the paper is to enable deeper insight into the measurement of
economic forecast accuracy. The paper employs the systematic literature review as its …

An increase in renewable energy injected into the power system will directly cause a
fluctuation in the overall voltage and frequency of the power system. Thus, renewable …

While a wealth of resources is available for teaching research writing of traditional IMRD
research papers, instructors have little to draw on when working with graduate students in …

Solar photovoltaic (PV) power generation is prone to drastic changes due to cloud cover.
The power is easily affected within a very short period of time. Thus, the accuracy of …

The present work explores the potential of an artificial neural network platform to emulate the
performance, emissions and stability indices of an existing single cylinder diesel engine …

This paper evaluates k-fold and Monte Carlo cross-validation and aggregation (crogging) for
combining neural network autoregressive forecasts. We introduce Monte Carlo crogging …

A new multiple parallel input and parallel output architecture-based models are developed
for forecasting electric load power consumption. Attention was paid toward the improvement …

Management of water resources under climate change is one of the most challenging tasks
in many arid and semiarid regions. A major challenge in countries, such as Yemen, is the …

Dynamic Trees are a tree-based machine learning technique specially designed for online
environments where data are to be analyzed sequentially as they arrive. Our purpose is to …