Global solar radiation information is the basis for many solar energy utilizations as well as
for economic and environmental considerations. However, because solar-radiation …

Accurately predicting the power produced during solar power generation can greatly reduce
the impact of the randomness and volatility of power generation on the stability of the power …

Traffic flow data (TFD) prediction is a hot research area in intelligent transportation system.
TFD is non-stationary and nonlinear, so it has become a challenge to predict it accurately. In …

Distance measurement (also known as similarity measurement) is used to evaluate pairwise
similarities between data samples. It has been widely used in diverse building informatics …

This study elaborates on a novel Hidden Markov Model (HMM)-based fuzzy model for time
series prediction. Fuzzy rules (rule-based models) are employed to describe and quantify …

Genomic selection (GS) in plant breeding is explored as a promising tool to solve the
problems related to the biotic and abiotic threats. Polyploid plants like bananas (Musa spp.) …

In many developed countries, photovoltaic solar power, which is considered the most cost-
effective renewable energy source, accounts for a major portion of electricity production. The …

Building automatic fault detection and diagnosis (AFDD) technologies have shown great
potential for energy savings. To enable AFDD, a baseline depicting the normal operation …

Probabilistic graphical models (PGMs) can effectively deal with the problems of energy
consumption and occupancy prediction, fault detection and diagnosis, reliability analysis …

This study examines a new approach for short‐term wind speed and power forecasting
based on the mixture of Gaussian hidden Markov models (MoG‐HMMs). The proposed …