# A Review of the Artificial Neural Network Models for Water Quality Prediction
## 5 Result
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Categories** & **Authors (Year)** & **Methods** & **Scenario (s)** & **Time Step** & **Dataset (Samples)** \\ \hline  & [39] & GRNN, BPNN, & lake & weekly & 28 (6 months) \\  & [40] & ANN(MLP), GRNN & coastal waters & No details & 32 (5 months) \\  & [59] & BPNN & river & No details & 39 (3 days) \\  & [158] & ANN & mine water & No details & 73 \\  & [97] & ANN & groundwater & No details & 97 \\  & [106] & ANN(MLP) & surface water & No details & 110 \\  & [159] & MLP & river & No details & 110 (8 hours) \\  & [130] & ANN(MLP) & plain & No details & 122 \\  & [128] & ANN & groundwater & monthly & 124 (1 year) \\  & [80] & ANN(MLP) & stream & No details & 132 (11 months) \\  & [79] & ANN(MLP) & basin & fortnightly & 144 (1 year) \\  & [131] & ANN(MLP) & river & monthly & 144 (12 years) \\  & [121] & RBFNN & river & weekly & 144 \\  & [24] & GRNN, ANN(MLP), & river & monthly & More than 151 \\  & [130] & ANN(MLP) & plain & No details & samples (6 years) \\  & [128] & ANN & groundwater & Monthly & 124 (1 year) \\  & [80] & ANN(MLP) & stream & No details & 132 (11 months) \\  & [79] & ANN(MLP) & basin & fortnightly & 144 (1 year) \\  & [131] & ANN(MLP) & river & monthly & 144 (12 years) \\  & [121] & RBFNN & river & weekly & 144 \\  & [24] & GRNN, ANN(MLP), & river & monthly & More than 151 \\  & [130] & ANN(MLP) & river & monthly & 147 (1 year) \\  & [142] & GRNN, MLR & river & monthly & 159 (9 years) \\  & [160] & ANN(MLP) & river & monthly & 164 (over 6 years) \\  & [107] & ANN & reservoir & No details & 180 (3 years) \\  & [22] & ANN & system & No details & 195 (4 years) \\  & [161] & ANN(MLP), RBFNN & river & monthly & 200 (17 years) \\  & [139] & ANN & river & No details & 200 (16 years) \\  & [93] & ANN & river & No details & 232 (3 years) \\ Feedforward & [63] & CCNN, MLP & river & half a month & 232 (12 years) \\  & [122] & ANN & river & No details & 252 (21 years) \\  & [113] & ANN(MLP) & river & No details & 255 (7 months) \\  & [43] & ANN(MLP), RBFNN, & WWTP & daily & 265 (3 years) \\  & [119] & ELM & WWTP & daily & 360 \\  & [75] & ANN & WWTP & daily & 364 (1 year) \\  & [118] & BPNN & reservoir & No details & 400 (20 years) \\  & [94] & BPNN & NA & No details & 500 \\  & [95] & ANN & river & monthly & 500 (10 years) \\  & [10] & ANN & groundwater & 30 minutes & 818 (nearly 17 days) \\  & [162] & BPNN & river & No details & 969 \\  & [77] & MLP, RBF, GRNN & Well & No details & 975 (16 years) \\  & [163] & ANN(MLP) & stream & daily & 982 (6 months) \\  & [88] & MLP & lake & No details & 1087 (6 years) \\  & [133] & ANN & lake & No details & 1217 \\  & RBFNN, GRNN, & river & No details & More than 1300 \\  & MLR & river & No details & samples (6 years) \\  & [36] & RBFNN, TDNN & river & monthly & 1320 (10 years) \\  & [117] & GRNN & river & No details & 1512 (9 years) \\  & [50] & MNN & WWTP & No details & 1900 \\  & [83] & ANN(MLP), RBFNN & river & daily & 2063 (6 years) \\  & [137] & ANN & river & No details & 3001 \\  & [112] & RBFNN, ANN(MLP), & upstream and & daily & 2063 and 4765 \\  & MLR & downstream & daily & samples (18 years) \\  & [115] & ANN & river & daily & more than 3000 \\  & [116] & ANN & lake & 15 minutes & 6674 (86 days) \\  & [164] & ANN & river & No details & 13,800 (5 years) \\  & [25] & GRNN & river & No details & more than 32,000 \\  & [47] & ELM, ANN(MLP) & Open-source & & samples \\  & [78] & ANN(MLP) & power station & 10 minutes & 45,594 (2 years) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Datasets of feedforward and recurrent neural networks. The artificial neural network has been widely used in water quality prediction. If researchers only look at the modeling process, various studies follow some of the steps of the modeling framework below (see Figure 10).