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  • About
    • The mission
    • Contacts
    • People who are involved
    • External Advisory Board
  • Events
    • HPC4AI – Intelligenza Artificiale e Big Data: opportunità e servizi al Politecnico
    • 6th SmartData@Polito Workshop
    • Computing@PoliTO Workshop
  • Seminars
    • Is Natural Language Processing the Holy Grail of Artificial Intelligence?
    • Uncertainty damping in the macroscopic forecast of vehicular traffic flow
    • Information Exposure for Consumer IoT Devices: A Multidimensional, Network-Informed Measurement Approach
  • Education
    • Courses for PhD students
    • PhD Course: Data Science for Networks
    • Corporate training on Digital Transformation
    • PhD Course: Introduction to Random Matrices – Theory and Practice
  • Research
    • Publications
    • Current PhD
    • Projects
    • Open Datasets & Libraries
    • Topics
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    • open position – Assistant Professor with time contract (RTD-A)
    • open position – PostDoc researchers
    • Open position – Technologist
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Home » Publications » Forecasting Heating Consumption in Buildings: A Scalable Full-Stack Distributed Engine

Forecasting Heating Consumption in Buildings: A Scalable Full-Stack Distributed Engine

Andrea Acquaviva, Daniele Apiletti, Antonio Attanasio, ELENA MARIA Baralis, Lorenzo Bottaccioli, Tania Cerquitelli, SILVIA ANNA Chiusano, Enrico Macii, Edoardo Patti (2019) Forecasting Heating Consumption in Buildings: A Scalable Full-Stack Distributed Engine, In: ELECTRONICS, pp. 1-31, ISSN: 2079-9292

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