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A brief review and a new automatic method for interpretation of polypropylene modified bitumen based on fuzzy radon transform and watershed segmentation
(Springer, 2019)
This paper reviews development exploitation semi and full automatic strategies for interpretation of Polypropylene Modifed Bitumen (PMB) in the last decade. The main purpose of this study is to provide a new automatic ...
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) ...
Seismic retrofit of full-scale substandard extended rectangular RC columns through CFRP jacketing: test results and design recommendations
(Journal of Composites for Construction, 2019)
Brittle behavior of substandard columns during earthquakes is among the most common reasons of structural failures. Because capacity design principles and ductile detailing concepts have not been properly adopted during ...
Ensemble gene expression programming: a new approach for evolution of parsimonious streamflow forecasting model
(Springer-Verlag, 2019)
A precise forecast of streamflow in intermittent rivers is of major difficulties and challenges in watershed management, particularly in arid and semiarid regions. The present research study introduces an ensemble gene ...
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 hybrid support vector regression-firefly model for monthly rainfall forecasting
(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 ...
Drones Path Planning for Collaborative Data Collection in ITS
(CRC Press, Taylor & Francis Group, 2019)
Unmanned aerial vehicles (UAVs) are used to physically interact with humans and urgent data collection in a shared workspace. They are flying collaborative robots that can be remotely supervised through a software-controlled ...
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, ...
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, ...
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 ...
