A review of the artificial neural network models for water quality prediction
Water quality prediction plays an important role in environmental monitoring, ecosystem
sustainability, and aquaculture. Traditional prediction methods cannot capture the nonlinear …
sustainability, and aquaculture. Traditional prediction methods cannot capture the nonlinear …
Protocol for developing ANN models and its application to the assessment of the quality of the ANN model development process in drinking water quality modelling
Abstract The application of Artificial Neural Networks (ANNs) in the field of environmental
and water resources modelling has become increasingly popular since early 1990s. Despite …
and water resources modelling has become increasingly popular since early 1990s. Despite …
Artificial neural network modeling of the water quality index for Kinta River (Malaysia) using water quality variables as predictors
This article describes design and application of feed-forward, fully-connected, three-layer
perceptron neural network model for computing the water quality index (WQI) 1 for Kinta …
perceptron neural network model for computing the water quality index (WQI) 1 for Kinta …
Artificial neural network modeling of dissolved oxygen in the Heihe River, Northwestern China
X Wen, J Fang, M Diao, C Zhang - Environmental monitoring and …, 2013 - Springer
Identification and quantification of dissolved oxygen (DO) profiles of river is one of the
primary concerns for water resources managers. In this research, an artificial neural network …
primary concerns for water resources managers. In this research, an artificial neural network …
Estimation of dissolved oxygen using data-driven techniques in the Tai Po River, Hong Kong
This study investigates the applicability of multilinear regression (MLR), adaptive neural-
based fuzzy inference system (ANFIS) and artificial neural networks (ANN) methods from …
based fuzzy inference system (ANFIS) and artificial neural networks (ANN) methods from …
杭州冬季塑料大棚内气温变化特征及日最低气温预报模型
范辽生， 朱兰娟， 柴伟国， 金志凤 - 中国农业气象, 2014 - zgnyqx.ieda.org.cn
利用2010-2012 年冬季塑料大棚内外气象资料, 分析晴天, 多云, 寡照3 种天气类型下的单,
双层棚内气温变化特征, 采用逐步回归方法构建适于杭州地区的棚内日最低气温预报模型 …
双层棚内气温变化特征, 采用逐步回归方法构建适于杭州地区的棚内日最低气温预报模型 …
[HTML][HTML] Artificial Neural Network (ANN)-Based Water Quality Index (WQI) for Assessing Spatiotemporal Trends in Surface Water Quality—A Case Study of South …
TD Banda, M Kumarasamy - Water, 2024 - mdpi.com
Artificial neural networks (ANNs) are powerful data-oriented “black-box” algorithms capable
of assessing and delineating linear and multifaceted non-linear correlations between the …
of assessing and delineating linear and multifaceted non-linear correlations between the …
[PDF][PDF] Artificial neural network modeling of the water quality index for the Euphrates river In Iraq
This study was aimed to investigate the development and evaluation of artificial intelligence
techniques by using multilayer neural network. Levenberg–Marquardt back propagation …
techniques by using multilayer neural network. Levenberg–Marquardt back propagation …
Development of software sensors for determining total phosphorus and total nitrogen in waters
E Lee, S Han, H Kim - International journal of environmental research and …, 2013 - mdpi.com
Total nitrogen (TN) and total phosphorus (TP) concentrations are important parameters to
assess the quality of water bodies and are used as criteria to regulate the water quality of the …
assess the quality of water bodies and are used as criteria to regulate the water quality of the …
A Chebyshev polynomial feedforward neural network trained by differential evolution and its application in environmental case studies
IA Troumbis, GE Tsekouras, J Tsimikas… - … Modelling & Software, 2020 - Elsevier
This paper introduces a polynomial feedforward neural network based on Chebyshev
polynomials able to effectively model non-linear and highly complex environmental data …
polynomials able to effectively model non-linear and highly complex environmental data …