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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Informatics (IJEEI) JURNAL ILMIAH PENDIDIKAN FISIKA AL BIRUNI Proceeding of the Electrical Engineering Computer Science and Informatics SINTECH (Science and Information Technology) Journal Indonesian Journal of Electrical Engineering and Computer Science SRIWIJAYA JOURNAL OF ENVIRONMENT International Conference on Sciences Development and Technology Journal of Multidisciplinary Academic and Practice Studies
Zainuddin Nawawi
Universitas Sriwijaya
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Journal : International Journal of Electrical and Computer Engineering

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Neural network training for serial multisensor of autonomous vehicle system Eka Nuryanto Budisusila; Sri Arttini Dwi Prasetyowati; Bhakti Yudho Suprapto; Zainuddin Nawawi
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5415-5426

Abstract

This study aims to find the best artificial neural network weight values to be applied to the autonomous vehicle system with ultrasonic multisensor. The implementation of neural network in the system required long time process due to its training process. Therefore, this research is using offline training before implementing to online training by embedding the best network weight values to obtain the outputs faster according to desired targets. Simulink were used to train the system offline. Eight ultrasonic sensors are used on all sides of the vehicle and arranged in a serial multisensory configuration as inputs of neural network. With eight inputs, one sixteen-depth hidden layer, and five outputs, it was trained using the back-propagation algorithm of artificial neural network. By 100000 iterations, the output values and the target values are almost the same, indicating its convergency with minimum of errors. The result of this training is the best weights of the networks. These weight values can be implemented as fixed-weight in online training.
Co-Authors ., Aulia ., Aulia Abduk-Malek, Zulkurnain Abu Bakar Sidik, Muhammad Abu Bakar Sidik, Muhammad Abu Bakar Sidik, Muhammad Adzis, Zuraimy Adzis, Zuraimy Agus Adhi Nugroho Agustini, Meily P Ahmad, Hussein Arief, Yanuar Arifin Rusli, Mohd Qamarul Asiah Muhamad, Nor Aulia . Aulia . Aulia Aulia ‘Irfan Jambak, Muhammad ‘Irfan Jambak, Muhammad Bhakti Yudho Suprapto Buntat, Zolkafle Buntat, Zolkafle Bustanul Arifin Cekmas Cekdin, Cekmas D. R. Yuniarti Eka Nuryanto Budi Susila Elnaz Akbari Ferlian Seftianto Fitria, Syarifa Hamizah Shahroom Hamizah Shahroom Hamizah Shahroom Hamizah Shahroom Hashem Ahmadi Hussein Ahmad Hussein Ahmad Ida Sriyanti Jaidan Jauhari Jambak, M. Irfan Jambak, Muhammad Irfan Jambak, Muhammad Irfan Lim Pai Hung Lim Pai Hung M. I. Jambak Mahmood, W. M. S. W. Maulana, Muhammad Bintang Meily P Agustini Mohd Qamarul Arifin Rusli Muhamad Haddin Muhammad Abu Bakar Sidik Muhammad Abu Bakar Sidik Muhammad Abu Bakar Sidik Muhammad Abu Bakar Sidik Muhammad Abu Bakar Sidik Muhammad Abu Bakar Sidik Muhammad Faizal Muhammad Irfan Jambak Muhammad Khosyi'in Muhammad Khosyi'in Muhammad ‘Irfan Jambak Muhammad ‘Irfan Jambak Muhammad ‘Irfan Jambak Muhammadjavad Mobarra N. F. A. Isa Nor Asiah Muhamad Norain Sahari Pai Hung, Lim Putra, Dian Eka Putra, Dian Eka R. F. Kurnia Rizda Fitri Kurnia, Rizda Fitri S. M. Zafar Iqbal Shahroom, Hamizah Shahroom, Hamizah Shahroom, Hamizah Sidik, Muhammad Abu Bakar Sri Arttini Dwi Prasetyawati Sukemi Sukemi Syed Muhammad Zafar Iqbal W. M. S. W. Mahmood Yanuar Arief Yanuar Z. Arief Yanuar Zulardiansyah Arief Yanuar Zulardiansyah Arief Z. Arief, Yanuar Z. Buntat Zolkafle Buntat Zolkafle Buntat Zulardiansyah Arief, Yanuar Zulkifli Azman Zulkurnain Abduk-Malek Zuraimy Adzis Zuraimy Adzis