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Fredelino A. Galleto Jr.
University of Southern Mindanao

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Comparison of ARIMA boost, Prophet boost, and TSLM models in forecasting Davao City weather data Jamal Kay B. Rogers; Tamara Cher R. Mercado; Fredelino A. Galleto Jr.
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp1092-1101

Abstract

The geography of the Philippines experiences climate variability thus, providing accurate and timely weather forecasts to the population is crucial. Climate forecasts, which are issued and disseminated by government agencies, serve as essential risk management tools. However, the country faces challenges in forecasting, further exacerbated by climate change. Thus, exploring the use of artificial intelligence has emerged as a strategy to enhance weather prediction accuracy. This research focuses on time series forecasting of rainfall, mean temperature, relative humidity, and wind speed weather data using a machine learning approach. Specifically, it aims to compare and identify the most beneficial forecasting models among autoregressive integrated moving average (ARIMA) boost, Prophet boost, and time series linear model (TSLM). It also seeks to evaluate the performance of these models using mean absolute error (MAE), mean absolute percentage error (MAPE), mean absolute scaled error (MASE), symmetric mean absolute percentage error (SMAPE), root mean squared error (RMSE), and R squared (RSQ) metrics. Results showed that the selection of the forecasting model varies based on the specific parameter under consideration, with no hyperparameter tuning in the analysis. For wind speed, ARIMA boost proves to be a favorable choice. At the same time, TSLM demonstrates effectiveness for relative humidity and mean temperature. Both ARIMA boost and TSLM exhibit strong performance for rainfall. Prophet boost consistently ranks as the least-performing model.
PID-based performance optimization of ultra-wideband microstrip patch antennas for indoor positioning systems Fredelino A. Galleto Jr.; Aaron Don M. Africa; Bettina Gaille H. Dayrit; Gia Kyla S. Guevarra; Chrismon Elijah Q. Mansilungan; Michael Angelo M. Obciana; Mariah Venice A. Rodriguez; Keane Dwight A. Sulit
Indonesian Journal of Electrical Engineering and Computer Science Vol 43, No 2: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v43.i2.pp450-459

Abstract

Ultra-wideband (UWB) technology has become a key enabler for high accuracy indoor positioning systems (IPSs), where antenna performance directly influences localization accuracy, signal quality, and communication reliability. However, designing compact UWB microstrip patch antennas with wide bandwidth, low reflection loss, and stable radiation characteristics remains a significant challenge. This paper presents a PID-based performance optimization approach for UWB microstrip patch antennas to improve antenna characteristics for indoor positioning applications. The proposed methodology integrates MATLAB-based electromagnetic simulation with parameter optimization to refine antenna geometry while incorporating optimization concepts inspired by rough set theory and fuzzy logic to support efficient design parameter selection. Using MATLAB and the Parallel Computing Toolbox, the proposed approach significantly reduces computational complexity while accelerating the optimization process. Experimental results demonstrate substantial improvements in reflection coefficient (S11), voltage standing wave ratio (VSWR), radiation pattern, and antenna directivity, particularly around the target operating frequency of 10 GHz. Among the evaluated configurations, the optimized rectangular microstrip patch antenna consistently outperformed the triangular design in terms of impedance matching and radiation performance. The proposed optimization framework provides an effective and computationally efficient solution for enhancing UWB antenna performance, making it well suited for high-precision indoor positioning and next-generation wireless communication systems.
Co-Authors Aaron Don M. Africa Bettina Gaille H. Dayrit Chrismon Elijah Q. Mansilungan Gia Kyla S. Guevarra Jamal Kay B. Rogers Keane Dwight A. Sulit Mariah Venice A. Rodriguez Michael Angelo M. Obciana Tamara Cher R. Mercado