Machine Learning Approach for Rapid Estimation of Five-Day Biochemical Oxygen Demand in Wastewater
نویسندگان
چکیده
Improperly managed wastewater effluent poses environmental and public health risks. BOD evaluation is complicated by treatment. Using key parameters to estimate in can improve management monitoring. This study proposes a determination method based on the Artificial Neural Networks (ANN) model combine Chemical Oxygen Demand (COD), Suspended Solids (SS), Total Nitrogen (T-N), Ammonia (NH4-N), Phosphorous (T-P) concentrations wastewater. Twelve different transfer functions are investigated, including common Hyperbolic Tangent Sigmoid (HTS), Log-sigmoid (LS), Linear (Li) functions. research evaluated 576,000 ANN models while considering variable random number generator due ten alternative configuration parameters. new approach assessing water resources facility performance. It also demonstrates ANN’s educational applications. Based their RMSE index over testing datasets parameters, twenty architectures ranked. A prediction equation written Excel makes applying real-world applications easier. The developed proposed ANN-LM 5-8-1 depicting almost ideal performance metrics proved be reliable helpful tool for scientists, researchers, engineers, practitioners system monitoring design phase of treatment plants.
منابع مشابه
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ژورنال
عنوان ژورنال: Water
سال: 2022
ISSN: ['2073-4441']
DOI: https://doi.org/10.3390/w15010103