Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
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ReserarchID
867GF
Crossref Journal DOI 10.17406/GJSFR
Print ISSN 0975-5896
e-ISSN 2249-4626
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Neural Networks and Rules-based Systems used to Find Rational and
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Analyses of runoff-sediment measurement and evaluation using automated and convectional runoff-meters was carried out at Meteorological and Hydrological Station of Auchi Polytechnic, Auchi using two runoff plots (ABCDa and EFGHm) of area 2m2 each, depth 0.26 m and driven into the soil to the depth of 0.13m. Runoff depths and intensities were measured from each of the positioned runoff plot. Automated runoff-meter has a measuring accuracy of ±0.001l/±0.025 mm and rainfall depth-intensity was measured using tipping-bucket rainguage during the period of 14-month of experimentation. Minimum and maximum rainfall depths of 1.2 and 190.3 mm correspond to measured runoff depths (MRo) of 0.0 mm for both measurement approaches and 60.4 mm and 48.9 mm respectively. Automated runoff-meter provides precise, accurate and instantaneous result over the convectional measurement of surface runoff. Runoff measuring accuracy for automated runoff-meter from the plot (ABCDa) produces R2 = 0.99; while R2 = 0.96 for manual evaluation in plot (EFGHm). WEPP and SWAT models were used to simulate the obtained hydrological variables from the applied measurement mechanisms. The outputs of sensitivity simulation analysis indicate that data from automated measuring systems gives a better modelling index and such could be used for running robust runoff-sediment predictive modelling technique under different reservoir sedimentation and water management scenarios.
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