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Hybrid Adaptive Neuro-Fuzzy Models for Water Quality Index Estimation

YASEEN, Zaher Mundher | RAMAL, Majeed Mattar | DIOP, Lamine | JAAFAR, Othman | DEMİR, Vahdettin | KİŞİ, Özgür

Soft computing models are known as an efficient tool for modelling temporal and spatial variation of surface water quality variables and particularly in rivers. These model’s performance relies on how effective their simulation processes are accomplished. Fuzzy logic approach is one of the authoritative intelligent model in solving complex problems that deal with uncertainty and vagueness data. River water quality nature is involved with high stochasticity and redundancy due to the its correlation with several hydrological and environmental aspects. Yet, the fuzzy logic theory can give robust ...Daha fazlası

Erişime Açık

Neurocomputing intelligence models for lakes water level forecasting: a comprehensive review

DEMİR, Vahdettin | YASEEN, Zaher Mundher

Hydrological processes forecasting is an essential step for better water management and sustainability. Among several hydrological processes, lake water level (LWL) forecasting is one of the significant processes within a particular catchment. The complexity of the LWL fluctuation is owing to the diversity of the influential parameters including climate, hydrology and some other morphology. In this study, several versions of neurocomputing intelligence models are developed for LWL fluctuation forecasting at five great lakes Lake Superior, Lake Michigan, Lake Huron, Lake Erie, and Lake Ontario, ...Daha fazlası

6698 sayılı Kişisel Verilerin Korunması Kanunu kapsamında yükümlülüklerimiz ve cerez politikamız hakkında bilgi sahibi olmak için alttaki bağlantıyı kullanabilirsiniz.

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