Increasing risks of energy security and greenhouse gas emission due to the growing
urbanization trend have prompted the need for urban energy demand prediction and …

With the significant increase in WQI applications worldwide and lack of specific application
guidelines, accuracy and reliability of WQI models is a major issue. It has been reported that …

In this synthesis, we assess present research and anticipate future development needs in
modeling water quality in watersheds. We first discuss areas of potential improvement in the …

This paper presents a flexible structure Radial Basis Function (RBF) neural network (FS-
RBFNN) and its application to water quality prediction. The FS-RBFNN can vary its structure …

Many efforts are used to eliminate the gaps between physical measurements and simulation
results. The Bayesian calibration technique is one of the popular automatic calibration …

A novel growing-and-pruning (GP) approach is proposed, which optimizes the structure of a
fuzzy neural network (FNN). This GP-FNN is based on radial basis function neurons, which …

China is confronting the challenge of accelerated lake eutrophication, where Lake Dianchi is
considered as the most serious one. Eutrophication control for Lake Dianchi began in the …

Nowadays, freshwater resources are facing numerous crises and pressures, resulting from
both artificial and natural process, so it is crucial to predict the water quality for the …

Water quality prediction is an important means for scientific water environment management
and early warning measures. However, its reliability is often restricted by the uncertainties of …

Sediment plays a pivotal role in determining the physical, chemical and biological integrity of
aquatic ecosystems. A range of factors influences the impacts of sediment pressures on …