Modeling of Water Quality Parameters Using Data-Driven Models
作者： H. Orouji , O. Bozorg Haddad , E. Fallah-Mehdipour , M. A. Mariño
DOI: 10.1061/(ASCE)EE.1943-7870.0000706
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摘要: AbstractWater has a considerable role in all aspects of human life. Thus, evaluation water characteristics general and quality particular are necessary to enhance the health humans ecosystems. Data-driven models computing methods that capable extracting different system states without using complex relationships. Prediction simulation two branches data-driven modeling use previous previous-current data sets fill gaps time series. This paper investigates capability an adaptive neural fuzzy inference (ANFIS) genetic programming (GP) as predict simulate parameters (e.g., sodium, potassium, magnesium, sulfates, chloride, pH, electrical conductivity, total dissolved solids) at Astane station Sefidrood River, Iran. The writers considered six combinations sets, including previously noted river discharge mo...
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