artificial neural network

February 9, 2019, Filed Under: Publication

Artificial Neural Network‐Based Framework for Developing Ground‐Motion Models for Natural and Induced Earthquakes in Oklahoma, Kansas, and Texas

This paper led by PhD student Farid Khosravikia from Patricia Clayton's group has been published in Seismological Research Letters. Check it out y'all. Farid developed neural network based models for earthquakes. DOI: https://doi.org/10.1785/0220180218 This paper, as well as our recent Read more

The Intelligent Environments Laboratory (IEL), led by Prof. Zoltán Nagy, is an interdisciplinary research group within the Building Energy & Environments (BEE) and Sustainable Systems (SuS) Programs of the Department of Civil, Architectural and Environmental Engineering (CAEE) in the Cockrell School of Engineering of the University of Texas at Austin.

The aim of our research is to rethink the built environment and define Smart Buildings and Cities as spaces that adapt to their occupants and reduce their energy consumption.

We combine data science with building science and apply machine learning to the building and urban scale

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Artificial Neural Network‐Based Framework for Developing Ground‐Motion Models for Natural and Induced Earthquakes in Oklahoma, Kansas, and Texas

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UT Energy App – Privacy Policy

Fault detection and diagnostics of air handling units using machine learning and expert rule-sets

Reinforcement Learning in the Built Environment

Reinforcement learning for urban energy systems & demand response

Multi-Agent Reinforcement Learning for demand response & building coordination

IEA-EBC Annex 79: Occupant Centric Design and Operation of Buildings

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