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PRODID:-//Société canadienne de génie civil - section est - ECPv4.2//NONSGML v1.0//EN
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X-WR-CALNAME:Société canadienne de génie civil - section est
X-ORIGINAL-URL:https://www.scgcquebec.ca/?lang=en
X-WR-CALDESC:Events for Société canadienne de génie civil - section est
BEGIN:VEVENT
DTSTART;TZID=UTC+0:20180326T180000
DTEND;TZID=UTC+0:20180326T190000
DTSTAMP:20260525T021847
CREATED:20180309T191542
LAST-MODIFIED:20180327T002047
UID:2079-1522087200-1522090800@www.scgcquebec.ca
SUMMARY:Putting Computers to the Task of Solving a Part of our Ageing Infrastructure Problem
DESCRIPTION:Registration – free for members\, $ 40 for non-members (payable locally):\n\nhttps://www.eventbrite.ca/e/bim-vdc-for-the-lifecycle-of-a-project-what-is-missing-tickets-39833877199\n\nSummary of the conference:\n\nThroughout the world\, ageing public infrastructure has been suffering from a chronic lack of funding. Canada is no exception\, where the lack of investments has led to an alarming number of structures which are in an advanced state of deterioration. Public infrastructure is essential to the economic development. Nevertheless\, the society cannot afford to mitigate this risk by retrofitting or replacing every deficient structure; we thus face the challenge of increasing their service life. A promising solution for mitigating the risk posed by ageing infrastructure is to have arrays of sensors deployed across cities to monitor\, in real time\, the condition of infrastructure. We now have the technological capacity to measure and store the data for thousands of structures. However\, what is holding back structural health monitoring (SHM) is that there is currently no generic and robust way to interpret the data collected by sensors. Factors such as the complexity of the interactions between structures and their environment\, the errors caused by difficult operational conditions\, and the large volume of data\, are all causing false alarms undermining the economic viability of SHM. This seminar will expose how methods issued from the fields of Machine Learning and Artificial Intelligence allow overcoming these limitations by putting computers to the task of detecting structural state changes.\n\n—\n\nBiography of the speaker:\n\nDr. Goulet is an Assistant Professor in the Civil Engineering Department at Polytechnique de Montréal. His research focuses on Machine Learning Methods for Civil Engineering applications such as structural health monitoring (SHM)\, infrastructure maintenance\, soil contamination characterization and probabilistic material models.
URL:https://www.scgcquebec.ca/event/putting-computers-to-the-task-of-solving-a-part-our-ageing-infrastructure-problem/?lang=en
LOCATION:3480 rue University \, Montreal\, Quebec\, H3A 0E9\, Canada
CATEGORIES:EN
ATTACH;FMTTYPE=image/png:https://www.scgcquebec.ca/wp-content/uploads/2018/03/Machine-Learning-Civil-Engineering.png
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