Ambulance Vehicle Routing in Smart Cities Using Artificial Neural Network

Javad Rahebi

Kitap Bölümü | 2022 | International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2022

This work proposes a routing ambulance vehicles method that uses the neural network. For the input of the neural network, eight features are selected. These features depend on the time, the position of the accident, ambulance and hospital, number of streets and injured person, type of accident, and age of the patient. With these features, the Ambulance can be decided to select the minimum route to find the nearest hospital. In this paper, we evaluate crucial metrics in responding to the accident, such as establishing temporary emergency units, the number of available ambulance units, and the city’s response and resources.

Harris Hawks Optimization Method based on Convolutional Neural Network for Face Recognition Systems

Javad Rahebi

Kitap Bölümü | 2022 | HORA 2022 - 4th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings

This paper discusses the momentum gradient dependent on the convolutional neural organization’s strong point. It is a new methodology introduced to detect evenness in the data set of faces. The proposed face recognition framework was created for various purposes. Through Gabor wavelet change, facial evenness was extracted from the face-preparing information. After that, we applied a profound learning process to carry out verification. After applying the proposed method to YALE and ORL data sets, we simulated them using MATLAB 2021a. Before this, similar trials were directly applied through Harris Hawks Optimization (HHO) for includi . . .ng the determination approach. The extraction process was conducted with many picture tests to execute the Gabor wavelet method, which proved more viable than other strategies applied in our examination. When we applied the HHO on the ORL dataset, the acknowledgment rate was 93.63%. It was 94.26% when the three techniques were applied to the YALE dataset. It shows that the HHO calculation improved the exactness rate to 96.44% in the case of the YALE dataset and 95.88% in the ORL datase Daha fazlası Daha az

Pulse Density Modulation Controlled WPT Charger for LEVs

Güngör BAL

Kitap Bölümü | 2022 | 10th International Conference on Smart Grid, icSmartGrid 2022

Light Electric Vehicles (LEV) are increasingly used today to provide mobility in crowded cities. The charging process of LEVs has been one of the issues that should be paid attention to. For this purpose, LEVs owned or rented by users need to be charged quickly and reliably. By using Wireless Power Transfer (WPT), this needed quick and reliable charging can be achieved for LEVs. In this paper, Pulse Density Modulation (PDM) is used for charging in Constant Voltage (CV) mode during wireless charging of LEVs with WPT. The simulation study required for CV charging was carried out with MATLAB/Simulink. A WPT system has been proposed tha . . .t produces a constant output voltage in response to changing equivalent load resistance in CV charging mode. Daha fazlası Daha az

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