[HTML][HTML] Review of nitrogen compounds prediction in water bodies using artificial neural networks and other models

P Kumar, SH Lai, JK Wong, NS Mohd, MR Kamal… - Sustainability, 2020 - mdpi.com
The prediction of nitrogen not only assists in monitoring the nitrogen concentration in
streams but also helps in optimizing the usage of fertilizers in agricultural fields. A precise …

Prediction of hydropower generation using grey wolf optimization adaptive neuro-fuzzy inference system

M Dehghani, H Riahi-Madvar, F Hooshyaripor… - Energies, 2019 - mdpi.com
Hydropower is among the cleanest sources of energy. However, the rate of hydropower
generation is profoundly affected by the inflow to the dam reservoirs. In this study, the Grey …

A hybrid support vector regression–firefly model for monthly rainfall forecasting

A Danandeh Mehr, V Nourani… - International Journal of …, 2019 - Springer
Long-term prediction of rainfalls is one of the most challenging tasks in stochastic hydrology
owing to the highly random characteristics of rainfall events. In this paper, a novel approach …

Application of artificial neural networks for water quality prediction

A Najah, A El-Shafie, OA Karim… - Neural Computing and …, 2013 - Springer
The term “water quality” is used to describe the condition of water, including its chemical,
physical, and biological characteristics. Modeling water quality parameters is a very …

Daily forecasting of dam water levels: comparing a support vector machine (SVM) model with adaptive neuro fuzzy inference system (ANFIS)

A Hipni, A El-shafie, A Najah, OA Karim… - Water resources …, 2013 - Springer
Reservoir planning and management are critical to the development of the hydrological field
and necessary to Integrated Water Resources Management. The growth of forecasting …

A review of impacts of climate change on slope stability

JL Wong, ML Lee, FY Teo, KW Liew - Climate Change and Water Security …, 2021 - Springer
Climate change has become an increasingly pressing issue that needs to be tackled by
scientists and researchers around the globe in recent years. However, huge uncertainties …

[HTML][HTML] Modeling of monthly rainfall and runoff of Urmia lake basin using “feed-forward neural network” and “time series analysis” model

J Farajzadeh, AF Fard, S Lotfi - Water Resources and Industry, 2014 - Elsevier
Urmia lake basin located in northwestern Iran is the second largest saline lake in the world.
Due to many reasons ie climate changes, several dam constructions, building a bridge …

Feasibility of rainwater harvesting for sustainable water management in urban areas of Egypt

TA Gado, DE El-Agha - Environmental Science and Pollution Research, 2020 - Springer
Egypt's limited water resources, rapid population growth, and climate change are increasing
the gap between water demand and supply. Meanwhile, significant amounts of rain fall in …

Monthly and seasonal hydrological drought forecasting using multiple extreme learning machine models

GC Wang, Q Zhang, SS Band, M Dehghani… - Engineering …, 2022 - Taylor & Francis
Hydrological drought forecasting is a key component in water resources modeling as it
relates directly to water availability. It is crucial in managing and operating dams, which are …

Week-ahead rainfall forecasting using multilayer perceptron neural network

LCP Velasco, RP Serquiña, MSAA Zamad… - Procedia Computer …, 2019 - Elsevier
Accurate rainfall forecasting plays a significant role for weather stations as it serves to warn
people about incoming natural disasters. This paper presents an implementation of week …