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Full-Text Articles in Engineering
Water Quality Factor Prediction Using Supervised Machine Learning, Kathleen Joslyn
Water Quality Factor Prediction Using Supervised Machine Learning, Kathleen Joslyn
REU Final Reports
The objective of this research is to explore prediction accuracy of water quality factors, with techniques and algorithms in machine learning consisting of a variation of support vector machines - Support Vector Regression (SVR) and the gradient boosting algorithm Extreme Gradient Boosting (XGBoost). Both the XGBoost and SVR algorithms were used to predict nine different factors with success rates ranging from 79% to 99%. Parameters of these algorithms were also explored to test the prediction accuracy levels of individual water quality factors. These parameters included normalizing the data, filling missing data points, and training and testing on a large set …
Building Intelligence In The Automated Traffic Signal Performance Measures With Advanced Data Analytics, Tingting Huang, Subhadipto Poddar, Chris Aguilar, Anuj Sharma, Edward J. Smaglik, Sirisha Kothuri, Peter Koonce
Building Intelligence In The Automated Traffic Signal Performance Measures With Advanced Data Analytics, Tingting Huang, Subhadipto Poddar, Chris Aguilar, Anuj Sharma, Edward J. Smaglik, Sirisha Kothuri, Peter Koonce
Civil and Environmental Engineering Faculty Publications and Presentations
Automated traffic signal performance measures (ATSPMs) are an effort to equip traffic signal controllers with high-resolution data-logging capabilities and utilize this data to generate performance measures. These measures allow practitioners to improve operations as well as to maintain and operate their systems in a safe and efficient manner. Although these measures have changed the way that operators manage their systems, several shortcomings of the tool, identified by talking with signal operators, are a lack of data quality control and the extent of resources required to properly use the tool for system-wide management. To address these shortcomings, intelligent traffic signal performance …
Traser: A Traffic Signal Event-Based Recorder, Chenhui Liu, Anuj Sharma, Edward Smaglik, Sirisha Kothuri
Traser: A Traffic Signal Event-Based Recorder, Chenhui Liu, Anuj Sharma, Edward Smaglik, Sirisha Kothuri
Civil and Environmental Engineering Faculty Publications and Presentations
In the past decades, the demand for high-resolution event-based traffic signal indication and detector data has increased due to the need for the collection and reporting of performance measures. This paper will first lay a groundwork for why this type of data acquisition is important, followed by the introduction of a new low-cost, user-friendly, high-resolution traffic signal event-based recorder—TraSER, with integrated video. This paper describes TraSER’s structure, operating principles, and field applications. TraSER allows researchers to be able to collect high-resolution event-based controller data at signalized intersections easily and conveniently. The paper concludes with a discussion on future expansion of …