Now showing items 1-5 of 5

    • Emotional ANN (EANN): a new generation of neural networks for hydrological modeling in IoT 

      Nourani, Vahid; Molajou, Amir; Najafi, Hessam; Danandeh Mehr, Ali (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, ...
    • Energy demand forecasting using deep learning 

      Hrnjica, Bahrudin; Danandeh Mehr, Ali (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 genetic programming approach to forecast daily electricity demand 

      Danandeh Mehr, Ali; Bagheri, Farzaneh; Reşatoğlu, Rifat (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) ...
    • Recurrent process on appointing an aid site: a case for airports 

      Demir, Emre (Université d'Evry / Université Paris-Saclay, 2019)
      Mathematical models have been used for many decades in order to improve the infrastructure design of transportation facilities. In this study, locational best fit airport infrastructure is determined for providing an urgent ...
    • Relationship between traffic density and pavement deflections 

      Demir, Emre; Koçkal, Niyazi Uğur (Université d'Evry / Université Paris-Saclay, 2019)
      Traffic density is one of the most important parameters to consider in road construction. The presence of different components in road construction makes it essential to know the individual layer and inter-layer behaviors. ...