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Investigating the effect of hydroclimatological variables on Urmia Lake water level using wavelet coherence measure
(IWA Publishing, 2019)
In this paper, wavelet transform coherence is implemented to examine the impacts of hydroclimatological variables on water level fluctuations in two large saline lakes in the Middle East with a similar geographical location, ...
Streamflow and sediment load prediction using linear genetic programming
(Uludağ University Journal of The Faculty of Engineering, 2018)
Daily flow and suspended sediment discharge are two major hydrological variables that affect rivers’ morphology and ecosystem, particularly during flood events. Artificial neural networks (ANNs) have been successfully used ...
Estimation of urban imperviousness and its impacts on flashfloods in Gazipaşa, Turkey
(Knowledge-Based Engineering and Sciences, 2021)
The paper examines flooding issues under rapid urbanization in Gazipasa city during the past seven years 2013-2019. The Storm Water Management Model (SWMM) integrated with the satellite images representing temporal variation ...
Energy demand forecasting using deep learning
(Springer Nature Switzerland AG, 2019)
Our cities face non-stop growth in population and infrastructures and require more energy every day. Energy management is the key success for the smart cities concept since electricity is one of the essential resources ...
A novel fuzzy random forest model for meteorological drought classification and prediction in ungauged catchments
(Pure and Applied Geophysics, 2020)
This paper presents a new tree-based model, namely Fuzzy Random Forest (FRF), for one month ahead Standardized Precipitation Evapotranspiration Index (SPEI) classification and prediction with a noteworthy application in ...
Pareto-optimal MPSA-MGGP: a new gene-annealing model for monthly rainfall forecasting
(Elsevier, 2019)
Rainfall is considered the hardest weather variable to forecast, and its cause-effect relationships often cannot be expressed in simple or complex mathematical forms. This study introduces a novel hybrid model to month ...
An improved gene expression programming model for streamflow forecasting in intermittent streams
(Elsevier, 2018)
Skilful forecasting of monthly streamflow in intermittent rivers is a challenging task in stochastic hydrology. In this study, genetic algorithm (GA) was combined with gene expression programming (GEP) as a new hybrid model ...
A genetic programming approach to forecast daily electricity demand
(Springer Nature Switzerland AG, 2019)
A number of recent researches have compared machine learning techniques to find more reliable approaches to solve variety of engineering problems. In the present study, capability of canonical genetic programming (GP) ...
Treated wastewater for concrete mixing; a comparitive study between astm and Turkisch standards
(12th International Scientific Conference on Production Engineering Development and Modernization of Production, 2019)
Water is one of the concrete mixing componenis that directly affecis the workability, durability, and mechanical properties of concrete elemenis. Generaliy, potable water which is suitable for human consumption is considered ...
Emotional ANN (EANN): a new generation of neural networks for hydrological modeling in IoT
(Springer Nature Switzerland AG, 2019)
Emotional artificial neural network (EANN) is a cutting-edge artificial intelligence method that has been used by researchers in the engineering and medical sciences over the recent years. First introduced in the 1999s, ...