Browsing İnşaat Mühendisliği Bölümü / Department of Civil Engineering by Author "55899085700 [Danandeh Mehr, Ali]"
Now showing items 1-13 of 13
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Chaos-based multigene genetic programming: a new hybrid strategy for river flow forecasting
Ghorbani, Mohammad Ali; Rahman, Khatibi; Danandeh Mehr, Ali; Hakimeh, Asadi (Elsevier, 2018)Chaos theory is integrated with Multi-Gene Genetic Programming (MGGP) engine as a new hybrid model for river flow forecasting. This is to be referred to as Chaos-MGGP and its performance is tested using daily historic flow ... -
Climate change impacts on meteorological drought using SPI and SPEI: case study of Ankara, Turkey
Danandeh Mehr, Ali; Sorman, Ali Ünal; Kahya, Ercan; Hesami Afshar, Mahdi (Hydrological Sciences Journal, 2019)Using regionally downscaled and adjusted outputs of three global climate models (GCMs), meteorological drought analysis was accomplished across Ankara, the capital city of Turkey. To this end, standardized precipitation ... -
Genetic programming in water resources engineering: a state-of-the-art review
Danandeh Mehr, Ali; Nourani, Vahid; Kahya, Ercan; Hrnjica, Bahrudin; Sattar, Ahmed M. A. (Elsevier, 2018)The state-of-the-art genetic programming (GP) method is an evolutionary algorithm for automatic generation of computer programs. In recent decades, GP has been frequently applied on various kind of engineering problems and ... -
A hybrid support vector regression-firefly model for monthly rainfall forecasting
Danandeh Mehr, Ali; Nourani, Vahid; Karimi Khosrowshahi, Vahid; Ghorbani, Moahmmad Ali (Springer Berlin Heidelberg, 2019)Long-term prediction of rainfalls is one of the most challenging tasks in stochastic hydrology owing to the highly random characteristics of rainfall events. In this paper, a novel approach is adopted to develop a hybrid ... -
An improved adaptive neuro-fuzzy inference system for hydrological drought prediction in algeria
Achite, Mohammed; Gul, Enes; Elshaboury, Nehal; Jehanzaib, Muhammad; Mohammadi, Babak; Danandeh Mehr, Ali (Elsevier, 2023)Drought has negative impacts on water resources, food security, soil degradation, desertification and agricultural productivity. The meteorological and hydrological droughts prediction using standardized precipitation/runoff ... -
An improved gene expression programming model for streamflow forecasting in intermittent streams
Danandeh Mehr, Ali (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 ... -
Multigene genetic programming for sediment transport modeling in sewers for conditions of non-deposition with a bed deposit
Safari, Mir Jafar Sadegh; Danandeh Mehr, Ali (Elsevier, 2018)It is known that construction of large sewers based on consideration of flow with non-deposition without a bed deposit is not economical. Sewer design based on consideration of flow with non-deposition with a bed deposit ... -
A new multi-objective genetic programming model for meteorological drought forecasting
Reihanifar, Masoud; Danandeh Mehr, Ali; Tur, Rifat; Ahmed, Abdelkader T.; Abualigah, Laith; Dąbrowska, Dominika (MDPI, 2023)Drought forecasting is a vital task for sustainable development and water resource management. Emerging machine learning techniques could be used to develop precise drought forecasting models. However, they need to be ... -
A novel fuzzy random forest model for meteorological drought classification and prediction in ungauged catchments
Danandeh Mehr, Ali; Tür, Rıfat; Cafer Çalışkan; Taş, Erkin (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
Danandeh Mehr, Ali; Jabarnejad, Masood; Nourani, Vahid (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 ... -
Season algorithm-multigene genetic programming: a new approach for rainfall-runoff modelling
Danandeh Mehr, Ali; Nourani, Vahid (Springer Netherlands, 2018)Genetic programming (GP) is recognized as a robust machine learning method for rainfall-runoff modelling. However, it may produce lagged forecasts if autocorrelation feature of runoff series is not taken carefully into ... -
Spatiotemporal variations in meteorological drought across the Mediterranean Region of Turkey
Soylu Pekpostalci, Dilayda; Tur, Rıfat; Danandeh Mehr, Ali (Springer, 2023)In this study, meteorological drought across the Mediterranean Region of Turkey (MRT) was investigated using fuzzy c-means clustering and innovative trend analysis (ITA). To this end, long-term (1971–2021) observed ... -
Trend analysis of hydroclimatological variables in Urmia lake basin using hybrid wavelet Mann–Kendall and Şen tests
Nourani, Vahid; Danandeh Mehr, Ali; Azad, Narges (Springer-Verlag, 2018)This paper investigates monthly, seasonal, and annual trends in rainfall, streamflow, temperature, and humidity amounts at Urmia lake (UL) basin and analyzes the interaction between these variables and UL’s water level ...