Enhancing the Prediction of Influent Total Nitrogen in Wastewater Treatment Plant Using Adaptive Neuro-Fuzzy Inference System–Gradient-Based Optimization Algorithm

For the accurate estimation of daily influent total nitrogen of sewage plants, a novel hybrid approach is proposed in this study, where a gradient-based optimization (GBO) algorithm is employed to adjust the hyper-parameters of an adaptive neuro-fuzzy system (ANFIS). Several benchmark methods for op...

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Veröffentlicht in:	Water (Basel) Jg. 16; H. 21; S. 3038
Hauptverfasser:	Ikram, Misbah, Liu, Hongbo, Al-Janabi, Ahmed Mohammed Sami, Kisi, Ozgur, Mo, Wang, Ali, Muhammad, Adnan, Rana Muhammad
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.11.2024
Schlagworte:	Algorithms Artificial intelligence Chemical oxygen demand Efficiency Effluents Energy consumption Environment Environmental aspects Environmental impact Fuzzy algorithms Fuzzy logic Fuzzy systems Generalized linear models Genetic algorithms Neural networks Nitrogen Optimization algorithms Pollutants Public health Purification Sewage Stream flow Support vector machines Water quality Water treatment Water treatment plants China
ISSN:	2073-4441, 2073-4441
Online-Zugang:	Volltext
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