A Study on the Development of Decision Support Tools Based on Simulation Using Machine Learning to Improve Energy Performance of Urban Rail Stations

被引:0
作者
Shin S.-K. [1 ]
Song H.-S. [1 ]
机构
[1] EAN TECHNOLOGY, Korea, Republic of
关键词
Energy performance simulation; Machine learning; Multiple regression analysis; Urban rail station;
D O I
10.5370/KIEE.2023.72.10.1275
中图分类号
学科分类号
摘要
According to the "Roadmap for Zero Energy in Urban rail Buildings", the goal is to promote zero energy building certification for all urban rail stations starting in 2025. However, it is not realistic to evaluate urban rail stations with existing evaluation tools. Therefore, this study developed a decision support tool to achieve ZEB rating. The research methodology is to perform energy simulation for three urban rail stations, and then calibrate the energy simulation model by comparing the results with the actual energy usage. Multiple regression analysis was performed with the calibrated model to build a prediction model for energy usage. The reliability of the model was verified through regression performance evaluation indicators. Finally, a web-based visualization dashboard on energy usage was developed. The visualization dashboard developed through this study provides a basis for decision-making for improving the energy performance of urban rail stations and obtaining ZEB ratings. © 2023 Korean Institute of Electrical Engineers. All rights reserved.
引用
收藏
页码:1275 / 1280
页数:5
相关论文
共 50 条
  • [41] Decision Support System Based on Machine Learning Techniques to Diagnosis Heart Disease Using Four-Lead ECG Recordings
    Hosni, Mohamed
    Medarhri, Ibtissam
    Touiti, Soufiane
    Tazi, Amal Mezalek
    Ngote, Nabil
    INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 2, WORLDCIST 2023, 2024, 800 : 121 - 130
  • [42] Forecasting electricity consumption based on machine learning to improve performance: A case study for the organization of petroleum exporting countries (OPEC)
    Khan, Abdullah
    Chiroma, Haruna
    Imran, Muhammad
    Khan, Asfandyar
    Bangash, Javed Iqbal
    Asim, Muhammad
    Hamza, Mukhtar F.
    Aljuaid, Hanan
    COMPUTERS & ELECTRICAL ENGINEERING, 2020, 86
  • [43] Mapping Seafloor Sediment Distributions Using Public Geospatial Data and Machine Learning to Support Regional Offshore Renewable Energy Development
    Capizzano, Connor W.
    Rhoads, Alexandria C.
    Croteau, Jennifer A.
    Taylor, Benjamin G.
    Guarinello, Marisa L.
    Shumchenia, Emily J.
    GEOSCIENCES, 2024, 14 (07)
  • [44] A practical tutorial on bagging and boosting based ensembles for machine learning: Algorithms, software tools, performance study, practical perspectives and opportunities
    Gonzalez, Sergio
    Garcia, Salvador
    Del Ser, Javier
    Rokach, Lior
    Herrera, Francisco
    INFORMATION FUSION, 2020, 64 : 205 - 237
  • [45] Machine Learning Approach to Reduce Alert Fatigue Using a Disease Medication-Related Clinical Decision Support System: Model Development and Validation
    Poly, Tahmina Nasrin
    Islam, Md Mohaimenul
    Muhtar, Muhammad Solihuddin
    Yang, Hsuan-Chia
    Nguyen, Phung Anh
    Li, Yu-Chuan
    JMIR MEDICAL INFORMATICS, 2020, 8 (11)
  • [46] Radiology Decision Support System for Selecting Appropriate CT Imaging Titles Using Machine Learning Techniques Based on Electronic Medical Records
    Shokrollahi, Peyman
    Chaves, Juan M. Zambrano
    Lam, Jonathan P. H.
    Sharma, Avishkar
    Pal, Debashish
    Bahrami, Naeim
    Chaudhari, Akshay S.
    Loening, Andreas M.
    IEEE ACCESS, 2023, 11 : 99222 - 99236
  • [47] A Machine Learning-Based Decision Support System for Predicting and Repairing Cracks in Undisturbed Loess Using Microbial Mineralization and the Internet of Things
    Yue, Yangyang
    Lv, Yiqing
    SUSTAINABILITY, 2023, 15 (10)
  • [48] Big Data Analysis Using Hadoop Framework and Machine Learning as Decision Support System (DSS) (Case Study: Knowledge of Islam Mindset)
    Nurhayati
    Busman
    Amrizal, Victor
    2018 6TH INTERNATIONAL CONFERENCE ON CYBER AND IT SERVICE MANAGEMENT (CITSM), 2018, : 43 - 48
  • [49] Reliability enhancement with coordinated operation of wind power and battery energy storage using machine learning based unit commitment decision
    Jain, Tanmay
    Verma, Kusum
    JOURNAL OF ENERGY STORAGE, 2025, 111
  • [50] Toward Precision Medicine: Development and Validation of A Machine Learning Based Decision Support System for Optimal Sequencing in Castration-Resistant Prostate Cancer
    Lim, Hakyung
    Yoo, Jeong Woo
    Lee, Kwang Suk
    Lee, Young Hwa
    Baek, Sangyeop
    Lee, Sujin
    Kang, Hoyong
    Choi, Young Deuk
    Ham, Won Sik
    Lee, Seung Hwan
    Chung, Byung Ha
    Halawani, Abdulghafour
    Ahn, Jae-Hyeon
    Koo, Kyo Chul
    CLINICAL GENITOURINARY CANCER, 2023, 21 (04) : E211 - +