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Seminar 41 — Optimizing Smart Building Operation with Machine Learning

$24.50

Conference Proceeding by ASHRAE, 2023

Category:

Description

This product is a zip file that contains files that consist of PowerPoint slides synchronized with the audio-recording of the speaker, PDF files of the slides, and audio only (mp3 format) as noted.

This advanced session discusses sophisticated machine learning (ML) optimization techniques and their application to improve operational efficiency and delivery of services for complex systems such as buildings and campuses. This session includes three presentations that focus on Supervised Learning and Reinforced Learning techniques for driving building controls towards superior strategies.

  1. A Comparison Study of ASHRAE Guideline 36 Supervisory Controls and Deep Reinforcement Learning-Based Controller for a Multi-Zone VAV System< /br> Zheng O’Neill, Ph.D., P.E., Fellow ASHRAE, Texas A&M University, College Station, TX
  2. Implementation of Structured Reinforcement Learning for Supply Air Temperature Control< /br> Amanda Pertzborn, Ph.D., Associate Member, NIST, Gaithersburg, MD
  3. Supervised Learning: A Powerful Tool for Smart Building Optimization< /br> Omar Abdelaziz, Member, Zewail City of Science and Technology, Giza, Egypt

Product Details

Published:
2023
Units of Measure:
Dual
File Size:
1 file , 87 MB
Product Code(s):
D-TO22Sem41
Sale!

Seminar 41 — Optimizing Smart Building Operation with Machine Learning

$24.50

Conference Proceeding by ASHRAE, 2022

Category:

Description

This product is a zip file that contains files that consist of PowerPoint slides synchronized with the audio-recording of the speaker, PDF files of the slides, and audio only (mp3 format) as noted.

This advanced session discusses sophisticated machine learning (ML) optimization techniques and their application to improve operational efficiency and delivery of services for complex systems such as buildings and campuses. This session includes three presentations that focus on Supervised Learning and Reinforced Learning techniques for driving building controls towards superior strategies.

  1. A Comparison Study of ASHRAE Guideline 36 Supervisory Controls and Deep Reinforcement Learning-Based Controller for a Multi-Zone VAV System
    Zheng O’Neill, Ph.D., P.E., Fellow ASHRAE, Texas A&M University, College Station, TX
  2. Implementation of Structured Reinforcement Learning for Supply Air Temperature Control
    Amanda Pertzborn, Ph.D., Associate Member, NIST, Gaithersburg, MD
  3. Supervised Learning: A Powerful Tool for Smart Building Optimization
    Omar Abdelaziz, Member, Zewail City of Science and Technology, Giza, Egypt

Product Details

Published:
2022
Units of Measure:
Dual
File Size:
1 file
Product Code(s):
D-TO22Sem-41
Note:
This product is unavailable in Russia, Belarus