Journal of Electrical and Computer Engineering / 2022 / Article / Tab 5 / Research Article
Analysis of Artificial Neural Network: Architecture, Types, and Forecasting Applications Table 5 The proposed five inputs based on improved backpropagation neural network statistical performance analysis with various hidden neurons for rainfall forecasting.
Number of hidden neurons Error qualifier R MAPE MSE MAE RMSE MRE Time (min) 1 0.98949 8.9725 657.7246 18.1105 25.6461 0.0897 1.21 2 0.1638 100 7.4967e +04 201.8431 273.8012 1.000 0.01 3 0.99991 0.7373 5.4600 1.4882 2.3367 0.0074 0.57 4 1 0.2696 0.6398 0.5441 0.7999 0.0027 1.59 5 1 0.0945 0.0864 0.1906 0.2939 9.4451e -04 4.15 6 1 0.0344 0.0143 0.0695 0.1194 3.4418e -04 1.54 7 1 0.0158 0.0042 0.0320 0.0645 1.5841e -04 1.24 8 1 0.0203 0.0077 0.0409 0.0880 2.0264e -04 1.36 9 1 0.0199 0.0079 0.0401 0.0869 1.9879e -04 1.49 10 1 0.0170 0.0066 0.0344 0.0815 1.7022e -04 1.52 11 1 0.0357 0.1512 0.0721 0.3889 3.5704e -04 1.13 12 1 0.0283 0.0842 0.0572 0.2902 2.8320e -04 3.47 13 1 0.0231 0.2452 0.0466 0.4956 2.3092e -04 3.10 14 1 0.0191 0.3369 0.0385 0.5804 1.9076e -04 5.40 15 1 0.0255 0.6127 0.0515 0.7828 2.5517e -04 8.31
Bold implies the best results.