Imputation methods for recovering streamflow observation: A methodological review
Missing value in hydrological studies is an unexceptional riddle that has long been
discussed by researchers. There are various patterns and mechanisms of “missingness” that …
discussed by researchers. There are various patterns and mechanisms of “missingness” that …
A practical review and taxonomy of fuzzy expert systems: methods and applications
Purpose Expert systems are computer-based systems that mimic the logical processes of
human experts or organizations to give advice in a specific domain of knowledge. Fuzzy …
human experts or organizations to give advice in a specific domain of knowledge. Fuzzy …
Exploring temporal dynamics of river discharge using univariate long short-term memory (LSTM) recurrent neural network at East Branch of Delaware River
River flow prediction is a pivotal task in the field of water resource management during the
era of rapid climate change. The highly dynamic and evolving nature of the climatic …
era of rapid climate change. The highly dynamic and evolving nature of the climatic …
Optimized ANFIS model using hybrid metaheuristic algorithms for Parkinson's disease prediction in IoT environment
Throughout recent years, the progress of telemonitoring and telediagnostics devices for
evaluating and tracking Parkinson's (PD) disease has become increasingly important. The …
evaluating and tracking Parkinson's (PD) disease has become increasingly important. The …
The selection of the sustainable suppliers by the development of a decision support framework based on analytical hierarchical process and fuzzy inference system
The current state of sustainability is promoting the status of the supply chain from traditional
economic objectives related to the cost, quality, and time to the multidimensional …
economic objectives related to the cost, quality, and time to the multidimensional …
Comparison of self-organizing map, artificial neural network, and co-active neuro-fuzzy inference system methods in simulating groundwater quality: geospatial …
Water quality experiments are difficult, costly, and time-consuming. Therefore, different
modeling methods can be used as an alternative for these experiments. To achieve the …
modeling methods can be used as an alternative for these experiments. To achieve the …
Novel forecasting models for immediate-short-term to long-term influent flow prediction by combining ANFIS and grey wolf optimization
Accurate influent flow forecasting plays a significant role in management, operation,
scheduling and utilization of the sewage treatment plants. In design and operate such …
scheduling and utilization of the sewage treatment plants. In design and operate such …
A decomposition-ensemble learning model based on LSTM neural network for daily reservoir inflow forecasting
Reservoir inflow forecasting is one of the most important issues in delicacy water resource
management at reservoirs. Considering the non-linearity and of daily reservoir inflow data, a …
management at reservoirs. Considering the non-linearity and of daily reservoir inflow data, a …
Forecasting multi-step-ahead reservoir monthly and daily inflow using machine learning models based on different scenarios
Dam reservoir operations are a critical issue for decision-makers in maximizing the use of
water resources. Artificial Intelligence and Machine Learning models (AI & ML) approaches …
water resources. Artificial Intelligence and Machine Learning models (AI & ML) approaches …
Viability of the advanced adaptive neuro-fuzzy inference system model on reservoir evaporation process simulation: case study of Nasser Lake in Egypt
Reliable prediction of evaporative losses from reservoirs is an essential component of
reservoir management and operation. Conventional models generally used for evaporation …
reservoir management and operation. Conventional models generally used for evaporation …