Predicting extreme events : the role of big data in quantifying risk in structural development

Predicting extreme events : the role of big data in quantifying risk in structural development

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2014.

Bibliographic Details
Main Author:	Newth, Oliver Edward
Other Authors:	Pierre Ghisbain and Jerome J. Connor.
Format:	Thesis
Language:	eng
Published:	Massachusetts Institute of Technology 2014
Subjects:	Civil and Environmental Engineering.
Online Access:	http://hdl.handle.net/1721.1/90028

Similar Items

Quantifying the risk of extreme seasonal precipitation events in a changing climate.
by: Palmer, T, et al.
Published: (2002)

Quantifying architects' and engineers' use of structural design software
by: Arnaud, Virginie B. (Virginie Blandine)
Published: (2013)

Quantifying human mobility resilience to extreme events using geo-located social media data
by: Roy, Kamol Chandra, et al.
Published: (2020)

Extreme Events: Mechanisms and Prediction
by: Farazmand, Mohammad M, et al.
Published: (2021)

Big data fusion to estimate driving adoption behavior and urban fuel consumption
by: Kalila, Adham
Published: (2018)

Extreme rainfall intensities and long-term rainfall risk from tropical cyclones
by: Langousis, Andreas, 1981-
Published: (2009)

Structural and mechanical properties of intermediate filaments under extreme conditions and disease
by: Qin, Zhao, Ph. D. Massachusetts Institute of Technology
Published: (2013)

An exploration of data-driven techniques for predicting extreme events in intermittent dynamical systems
by: Guth, Stephen Carrol.
Published: (2020)

Investigating the Use of Inductive Transfer Learning and RNN to Quantify Extreme Event Statistics of Ship Motions
by: Kramer, Jarod
Published: (2023)

Embracing the complexity of extreme weather events when quantifying their likelihood of recurrence in a warming world
by: Harrington, L, et al.
Published: (2019)

Ensemble-Based Risk Scoring with Extreme Learning Machine for Prediction of Adverse Cardiac Events
by: Liu, Nan, et al.
Published: (2018)

Big Data and Firm Risk
by: Paine, Fiona
Published: (2022)

Structural quality assurance of wood light-frame construction subject to extreme wind hazards
by: Ackerman, Christopher B. (Christopher Brian)
Published: (2005)

Are extreme dissipation events predictable in turbulent fluid flows?
by: Blonigan, Patrick J., et al.
Published: (2020)

Quantifying qualitative information on risks (QQIR) in structured finance transactions
by: Tillmann Sachs
Published: (2010)

Influence of extreme velocities on dynamic cavity expansion
by: Wittels, Kelsey Lynn
Published: (2017)

Quantifying and integrating constructability into multi-objective steel floor framing design
by: Tan, Melody, M. Eng Massachusetts Institute of Technology
Published: (2016)

Global warming and world ecosystem distribution : toward quantifying ecosystem change
by: Thomas, Christopher Kent
Published: (2011)

Flexible stadium design in the context of Olympics and Post-Olympics usage
by: Beacham, Oliver (Oliver Edward)
Published: (2015)

Light interstitials in iron under extreme mechanical conditions
by: Moeini Ardakani, Sina(Seyed Sina)
Published: (2020)

A wavelet-based system for event detection in online real-time sensor data
by: Varadharajan, Charuleka, 1980-
Published: (2005)

Application of linear moments and uncertainty analysis to extreme rainfall events in Sabah
by: Shu, Lim Chuah, et al.
Published: (2017)

Quantifying China's carrying capacity : using optimization to explore sustainable food production
by: Smith, Tiziana
Published: (2019)

Evaluating modeling techniques for quantifying production risk in contact lens manufacturing
by: Neff, Margaret E.(Margaret Ellen)
Published: (2020)

Active control of extremely prestressed simple supported composite bridges
by: Dagher, Bahjat (Bahjat Nouhad)
Published: (2007)

Soil microbiomes show consistent and predictable responses to extreme events
by: Knight, CG, et al.
Published: (2024)

Quantifying Extreme Event Statistics for Ship Motions and Loads Using Low-Fidelity Models and Recurrent Neural Networks
by: Howard, Dayne M.
Published: (2022)

A design methodology for hysteretic dampers in buildings under extreme earthquakes
by: Fleming, Cody Harrison
Published: (2005)

Patterns of extreme events in the climate over the South China Sea
by: Lim, Janet Miao Jin
Published: (2016)

Quantifying the cost uncertainty of climate stabilization policies
by: Franck, Travis Read
Published: (2006)

Form-maker and collaborator : the role of the structural engineer
by: Tao, Alice
Published: (2010)

The Alaskan Summer 2019 Extreme Heat Event: The Role of Anthropogenic Forcing, and Projections of the Increasing Risk of Occurrence
by: Weidman, Sarah K., et al.
Published: (2022)

Design of a watershed-based nitrogen trading system or the Big and Little Wood Rivers Watershed
by: Lopez-Bernal, Kristina Elizabeth, 1980-
Published: (2006)

Quantifying changes in climate variability and extremes: Pitfalls and their overcoming
by: Sippel, S, et al.
Published: (2015)

Seizing the teachable moment: extreme weather events as catalysts for climate change dialogue, learning, and action
by: Ettinger, JA
Published: (2023)

Breaking the Arc: Risk control for Big Data
by: Hodges, D, et al.
Published: (2013)

Breaking the Arc: Risk Control for Big Data
by: Hodges, D, et al.
Published: (2013)

Statistical estimation and prediction in probabilistic models with application to structural reliability.
by: Veneziano, Daniele
Published: (2014)

The role of new technology in improving data collection for public transportation
by: Wong, Albert Shing Fai
Published: (2008)

A model for predicting air flow during in-situ air sparging
by: Paonessa, Michael E. (Michael Edward), 1979-
Published: (2014)