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 ...

Türkiye’de son yıllarda sivil havacılık hızlı bir şekilde gelişmiştir ve bu ivme artarak devam etmektedir. Tüm dünyada ve ülkemizde hızla büyüyen sivil havacılık sektörü ve işletmeciliği hemen hemen herkesin kullanımına ...

Cyprus Island has very limited water resources. Recently, this problem has rather been resolved by transferring water from Turkey to the island known as Cyprus Water Supply Project (CWSP). The CWSP is comprised of three ...

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 ...

In this paper, the author determines the most suitable transportation location for intervention in a large scale disaster in the Republic of Bulgaria, by means of the Weber Problem and the Weiszfeld method. The objective ...

For many decades, mathematical models and methodologies have been essential in order to provide the understanding of countless engineering processes and technologies. Using mathematical models in many academic research, ...

In the present study, gene expression programming (GEP) technique was used to develop one-month ahead monthly rainfall forecasting models in two meteorological stations located at a semi-arid region, Iran. GEP was trained ...

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 ...

There is no standard accepted by highway authorities on the compaction procedures of 100 mm diameter gyratory compactor specimens. In previous studies on gyratory compaction, the utilisation of either coring from 150 mm ...

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 ...