Predicting water quality with artificial intelligence: a review of methods and applications
D Irwan, M Ali, AN Ahmed, G Jacky, A Nurhakim… - … Methods in Engineering, 2023 - Springer
The water is the main pivotal sources of irrigation in agricultural activities and affects human
daily activities such as drinking. The water quality has a significant impact on various …
daily activities such as drinking. The water quality has a significant impact on various …
[HTML][HTML] Application of ANN and HEC-RAS model for flood inundation mapping in lower Baro Akobo River Basin, Ethiopia
Abstract Study region Lower Baro River, Ethiopia. Study focus This paper presents the
novelty of ANN and HEC-RAS model for flood inundation mapping in lower Baro Akobo …
novelty of ANN and HEC-RAS model for flood inundation mapping in lower Baro Akobo …
Proposed formulation of surface water quality and modelling using gene expression, machine learning, and regression techniques
The rising water pollution from anthropogenic factors motivates further research in
developing water quality predicting models. The available models have certain limitations …
developing water quality predicting models. The available models have certain limitations …
Simulating the relationship between land use/cover change and urban thermal environment using machine learning algorithms in Wuhan City, China
The changes of land use/land cover (LULC) are important factor affecting the intensity of the
urban heat island (UHI) effect. Based on Landsat image data of Wuhan, this paper uses …
urban heat island (UHI) effect. Based on Landsat image data of Wuhan, this paper uses …
Rainfall and runoff time-series trend analysis using LSTM recurrent neural network and wavelet neural network with satellite-based meteorological data: case study of …
YO Ouma, R Cheruyot, AN Wachera - Complex & Intelligent Systems, 2021 - Springer
This study compares LSTM neural network and wavelet neural network (WNN) for spatio-
temporal prediction of rainfall and runoff time-series trends in scarcely gauged hydrologic …
temporal prediction of rainfall and runoff time-series trends in scarcely gauged hydrologic …
Combining data-intelligent algorithms for the assessment and predictive modeling of groundwater resources quality in parts of southeastern Nigeria
JC Egbueri, JC Agbasi - Environmental Science and Pollution Research, 2022 - Springer
Abstract Machine learning algorithms have proven useful in the estimation, classification,
and prediction of water quality parameters. Similarly, indexical modeling has enhanced the …
and prediction of water quality parameters. Similarly, indexical modeling has enhanced the …
Modelling Reservoir Chlorophyll‐a, TSS, and Turbidity Using Sentinel‐2A MSI and Landsat‐8 OLI Satellite Sensors with Empirical Multivariate Regression
YO Ouma, K Noor, K Herbert - Journal of Sensors, 2020 - Wiley Online Library
Sentinel‐2A/MSI (S2A) and Landsat‐8/OLI (L8) data products present a new frontier for the
assessment and retrieval of optically active water quality parameters including chlorophyll‐a …
assessment and retrieval of optically active water quality parameters including chlorophyll‐a …
Predicting and analysing the quality of water resources for industrial purposes using integrated data-intelligent algorithms
JC Egbueri - Groundwater for Sustainable Development, 2022 - Elsevier
The continuous increase in the rate of industrialization in developing countries, in recent
times, calls for continuous industrial water quality assessment and prediction. This is to …
times, calls for continuous industrial water quality assessment and prediction. This is to …
Incorporation of information entropy theory, artificial neural network, and soft computing models in the development of integrated industrial water quality index
JC Egbueri - Environmental Monitoring and Assessment, 2022 - Springer
Keeping purpose and targeted end-users in perspective, several water quality indices have
been developed over the past decades to summarily convey water quality information to …
been developed over the past decades to summarily convey water quality information to …
Predicting the degree of dissolved oxygen using three types of multi-layer perceptron-based artificial neural networks
Predicting the level of dissolved oxygen (DO) is an important issue ensuring the
sustainability of the inhabitants of a river. A prediction model can predict the DO level using …
sustainability of the inhabitants of a river. A prediction model can predict the DO level using …