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[HTML][HTML] Review of nitrogen compounds prediction in water bodies using artificial neural networks and other models
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 …
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
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 …
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
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 …
owing to the highly random characteristics of rainfall events. In this paper, a novel approach …
Application of artificial neural networks for water quality prediction
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 …
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)
Reservoir planning and management are critical to the development of the hydrological field
and necessary to Integrated Water Resources Management. The growth of forecasting …
and necessary to Integrated Water Resources Management. The growth of forecasting …
A review of impacts of climate change on slope stability
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 …
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 …
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
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 …
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 …
relates directly to water availability. It is crucial in managing and operating dams, which are …
Week-ahead rainfall forecasting using multilayer perceptron neural network
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 …
people about incoming natural disasters. This paper presents an implementation of week …