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
10I50
Crossref Journal DOI 10.17406/GJSFR
Print ISSN 0975-5896
e-ISSN 2249-4626
The methods for personal identification and authentication are no exception.
Neural Networks and Rules-based Systems used to Find Rational and
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This study was undertaken to assess the physicochemical quality of the surface water of the Sagbama Creek, Bayelsa State, Nigeria. Samples of water were collected and preserved using trioxonitrate v acid and placed in a cooler of ice for transfer to the laboratory except for insitu measurements for temperature, turbidity, conductivity, TDS, pH, DO and Salinity using Hanna H19828 multi-parameter water quality checker. Five stations were employed correspondingly with control stations. Results were compared with both control and standard permissible limits for the following parameters for both River water samples and the control respectively; temperature (28.56±1.99 and 27.52±0.93), turbidity (225±274 and 359±318), TDS (39±29.60 and 20.80±14.81), conductivity (94±47 and 40.80±29), pH (5.55±0.6 and 5.61±0.24), Salinity (0.04±0.02 and 0.016±0.015), alkalinity (27±31 and 8.80±12.5), Hardness (20.82±22 and 6.66±7.52). Similarly the gross organic pollutants of DO, COD, and BOD recorded 2.22±0.065 and 2.26±0.15; 1.07±0.41 and 0.58±0.41; 0.72±0.49 and 0.39±0.27) respectively. All values were either below or within the permissible limits for either surface water, DPR or FMENV. This means that the Sagbama creek water is not polluted except for the high level of turbidity recorded which were above permissible limits. There is, therefore, the urgent need to de-silt the River by dredging to reduce the turbidity which could lead to migration of aquatic animals.
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