Article Per Year (5 Year)
p-Index From 2021 - 2026
1.048
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics Buletin Ilmiah Sarjana Teknik Elektro Vokasi UNESA Bulletin of Engineering, Technology and Applied Science
Oliva, Diego
Unknown Affiliation
Computer Science & IT Electrical & Electronics Engineering Engineering Mechanical Engineering Transportation

Published : 6 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Bulletin of Electrical Engineering and Informatics

 1 
A novel modified mountain gazelle optimizer for tuning parameter proportional integral derivative of DC motor Aribowo, Widi; Abualigah, Laith; Oliva, Diego; Prapanca, Aditya
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.5575

Abstract

This article presents a modified method of mountain gazelle optimizer (MMGO) as a direct current (DC) motor control. Mountain gazelle optimizer (MGO) is an algorithm inspired by the life of the mountain gazelle animal in nature. This animal concept has five essential steps that are duplicated in mathematical modeling. This article uses two tests to get the performance of the MMGO method. The first test uses a benchmark function test with a comparison method, namely the sine tree seed algorithm (STSA) and the original MGO. The second test is the application of MMGO as a DC motor control. The simulation results show that MMGO can reduce the overshoot of conventional proportional integral derivative (PID) control by 0.447% and has a better integral time square error (ITSE) value of 5.345 than conventional PID control. Thus, the MMGO method shows promising performance.
Enhancing photovoltaic parameters based on modified puma optimizer Aribowo, Widi; Abualigah, Laith; Oliva, Diego; Elsayed Abd Elaziz, Mohamed; Soleimanian Gharehchopogh, Farhad; A. Shehadeh, Hisham; Sabo, Aliyu; Prapanca, Aditya
Bulletin of Electrical Engineering and Informatics Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i3.8977

Abstract

This article presents a photovoltaic (PV) optimization approach using the puma optimizer (PO) approach, which has been enhanced by utilizing Lévy flight optimization. The name of this approach is modified puma optimizer (MPO). PV generation systems are essential for sustainable solar energy utilization. It is an innovation and clean energy. There is an urgent demand for suitable and reliable simulation and optimization techniques for PV systems. This will result in increased efficiency. Algorithms with a high degree of reliability are needed to ensure optimal PV parameters. This study was conducted with MATLAB software. This article introduces the original PO method as a means to evaluate the performance of the MPO approach. The root mean square error (RMSE) function serves as a benchmark. Based on the simulation findings, the MPO approach shows superior RMSE compared to the PO method, specifically at a value of 0.0026%.
Co-Authors A. Shehadeh, Hisham Abualigah, Laith Aditya Prapanca Aljohani, Abeer Amaliah, Fithrotul Irda As’ad Shidqy Aziz B, Nur Vidia Laksmi Elsayed Abd Elaziz, Mohamed Mzili, Toufik Sabo, Aliyu Soleimanian Gharehchopogh, Farhad Widi Aribowo Zangana, Hewa Majeed