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Temperature and Hourly Precipitation Prediction System for Road Bridge using Artificial Neural Networks

Gnanasekar, Nithyakumaran
http://orcid.org/0000-0003-0755-1254
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448873819

Abstract Details

2015, MS, University of Cincinnati, Engineering and Applied Science: Computer Science.
UCII has designed and built the Weather monitoring system for Bridges, at multiple locations in North America. The Weather Monitoring System collects data from the local weather stations, airports around the bridge and the sensors installed on the bridge. This data is analyzed for inclement weather conditions on and around the bridge and whenever an abnormal behavior is detected, “Alarms” are sent out via email. Using the large amount of data collected from various stations and sensors correlation between every variable is studied. This detailed study is later used to build Eight Hour Ahead Temperature Prediction system and a Four Hours Ahead Hourly Precipitation Prediction System. The Prediction system uses machine learning techniques to predict new data based on prior data. The Atmospheric variables collected such as temperature, pressure, humidity, hourly precipitation, wind speed, wind direction, solar radiation is analyzed. The correlation between the afore-mentioned variables on time scale is also analyzed and is discussed in detail which aided in building the Prediction models. The prediction system uses an Artificial Neural network to train and provide predictions. The prediction system was designed and built to be used alongside Weather Monitoring system built by UCII and to further its intelligence coefficient in predicting inclement weather condition.
Arthur Helmicki, Ph.D. (Committee Chair)
Victor Hunt, Ph.D. (Committee Member)
Paul Talaga, Ph.D. (Committee Member)
131 p.
Engineering
Artificial Neural Network; Road way bridge; local weather prediction; weather monitoring system

Recommended Citations

Citations

  • Gnanasekar, N. (2015). Temperature and Hourly Precipitation Prediction System for Road Bridge using Artificial Neural Networks [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448873819

    APA Style (7th edition)

  • Gnanasekar, Nithyakumaran. Temperature and Hourly Precipitation Prediction System for Road Bridge using Artificial Neural Networks. 2015. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448873819.

    MLA Style (8th edition)

  • Gnanasekar, Nithyakumaran. "Temperature and Hourly Precipitation Prediction System for Road Bridge using Artificial Neural Networks." Master's thesis, University of Cincinnati, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448873819

    Chicago Manual of Style (17th edition)

ucin1448873819
549
© 2015, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.