Document Type : Original Research Manuscripts

Authors

• Ali Esmaili ¹
• Hoshang Taghizadeh ²
• Naser Faqhi Farhamand ³

¹ PhD student of Industrial Management, Tabriz Branch, Islamic Azad University, Tabriz, Iran.

² Professor of Industrial Management, Tabriz Branch, Islamic Azad University, Tabriz, Iran.

³ Associate Professor, Department of Management, Tabriz Branch, Islamic Azad University, Tabriz, Iran.

Abstract

This research aims to study the data-driven model of gas consumption management, with a focus on addressing unauthorized use through the analysis of information systems. Research was conducted using a metasynthesis approach and technique in the field of gas consumption management and mathematical programming with genetic algorithms. ATLAS.ti software was used for analysis. The influencing factors related to a specific period of time were examined and searched for in this research. Internal and external sources from the years 2006 to 2023 were analyzed. 27 studies were selected based on the Critical Appraisal Skills Programme (CASP) technique. In the continuation of mathematical modeling using MATLAB software, the simulation was conducted to compare the performance of three proposed algorithms. Based on the results obtained from the meta-combination technique, the main categories include the use of renewable energy, gas consumption management, shortcomings, obstacles, data-driven solutions, consequences of gas consumption management, and economic growth. All three models also demonstrated the basis for optimal gas consumption and the reduction of unauthorized consumption. The utilization of data analysis can enhance system efficiency, pinpoint weaknesses and losses, boost productivity, and optimize the utilization of gas energy. Based on the analysis, it was shown that data mining can be very useful in managing gas energy consumption and identifying unauthorized breaches. Overall, simulating gas energy consumption management using a genetic algorithm can provide efficient and effective solutions, handle complex and dynamic scenarios, and offer insights into optimizing gas consumption and energy efficiency.

Keywords

• Gas Consumption Management
• Data-Oriented Model
• Information Systems
• Gas Company
• East Azerbaijan Province

Main Subjects

• Data mining