Water Pollution and Its Prevention Through Development of Low Cost Wastewater Treatment System

Gawande, Sagar M.; Sarode, Dilip D.

doi:10.1007/978-3-030-51485-3_35

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…TDS comprises dissolved organic matters and a variety of inorganic salts e.g., sodium )Na + (, magnesium (Mg 2+ ), calcium (Ca 2+ ), and potassium (K + ) as cations, as well as chloride (Cl -), sulfate (SO4 2 ), nitrates (NO -), and bicarbonates (HCO 3-), as anions (Sun et al, 2021). Based on the World Health Organization WHO standards, the acceptable TDS range for agricultural uses is 450-2000 mg/l (Gawande & Sarode, 2021). As high concentrations of this parameter can overshadow human health and the environment, it is important to focus on it in the evaluation of water resources, especially surface waters (Chellaiah et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of total dissolved solids in rivers by improved neuro fuzzy approaches using metaheuristic algorithms

Jannatkhah,

Davarpanah,

Fakouri

et al. 2024

Earth Sci Inform

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Substantial deterioration of surface water quality, mainly caused by human activities and climate change, makes the assessment of water quality a global priority. Thus, in this study, four metaheuristic algorithms, namely the particle swarm optimization (PSO), differential evolution (DE), ant colony optimization algorithm (ACOR), and genetic algorithm (GA), were employed to improve the performance of the adaptive neuro-fuzzy inference system (ANFIS) in the evaluation of surface water total dissolved solids (TDS). Monthly and annual TDS were considered as target variables in the analysis. In order to evaluate and compare the authenticity of the models, an economic factor (execution time) and statistical indices of the coefficient of determination (R2), Kling Gupta efficiency (KGE), root mean squared error (RMSE), mean absolute error (MAE), and Nash-Sutcliff efficiency (NSE) were utilized. The results revealed that the hybrid methods used in this study could enhance the classical ANFIS performance in the analysis of monthly and annual TDS of both stations. For more clarification, the models were ranked using the TOPSIS approach by simultaneously applying the effects of statistical parameters, temporal and spatial change factors, and execution time. This approach significantly facilitated decision-making in ranking models. The ANFIS-ACOR annual model considering discharge had the best performance in the Vanyar Station; Furthermore, ANFIS-ACOR monthly model ignoring discharge was outstanding in the Gotvand Station. In total, after utilizing two defined and proposed temporal and spatial change factors, ANFIS-ACOR and ANFIS-DE hybrid models had the best and worst performance in TDS prediction, respectively.

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Section: Introductionmentioning

confidence: 99%