Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering
Tokhmetov, Akylbek
Unknown Affiliation
Computer Science & IT Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Energy consumption prediction methods in a cyber-physical system Nurgaliyev, Kenzhegali; Tokhmetov, Akylbek
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i3.pp3054-3063

Abstract

In recent decades, cyber-physical systems (CPS) have become an essential part of modern industry and daily life. These systems integrate physical processes with computer and network components, allowing them to interact with their environment and manage their components autonomously. One of the most significant aspects of CPS efficiency is managing energy consumption, which significantly affects their reliability, efficiency, and economic performance. CPS devices generate vast amounts of diverse data, which is crucial to accurately model. Researchers use predictive analysis to develop models that forecast trends and simulate real-world conditions, enabling them to make better-informed decisions. This article presents a comparative analysis of different predictive models for CPS data analytics, focusing on energy consumption in smart buildings. Short-term models include gradient-boosted regressor (XGBoost), random forest (RF) and long short-term memory (LSTM). The comparative results have been studied in terms of prediction errors to determine accuracy.
Co-Authors Nurgaliyev, Kenzhegali