Open Access. Powered by Scholars. Published by Universities.®

Civil and Environmental Engineering Commons™

Open Access. Powered by Scholars. Published by Universities.®

Machine learning

Discipline
Institution
Publication Year
Publication
Publication Type
File Type

Articles 151 - 157 of 157

Full-Text Articles in Civil and Environmental Engineering

Forecasting Harmful Algal Blooms For Western Lake Erie Using Data Driven Machine Learning Techniques, Nicholas L. Reinoso Jan 2017

Forecasting Harmful Algal Blooms For Western Lake Erie Using Data Driven Machine Learning Techniques, Nicholas L. Reinoso

ETD Archive

Harmful algal blooms (HAB) have been documented for more than a century occurring all over the world. The western Lake Erie has suffered from Cyanobacteria blooms for many decades. There are currently two widely available HAB forecasting models for Lake Erie. The first forecasting model gives yearly peak bloom forecast while the second provides weekly short-term forecasting and offers size as well as location. This study focuses on bridging the gap of these two models and improve HAB forecast accuracy in western Lake Erie by letting historical observations tell the behavior of HABs. This study tests two machine learning techniques, …

Go to article

Audio-Based Productivity Forecasting Of Construction Cyclic Activities, Chris A. Sabillon Jan 2017

Audio-Based Productivity Forecasting Of Construction Cyclic Activities, Chris A. Sabillon

College of Graduate Studies: Theses & Dissertations

Due to its high cost, project managers must be able to monitor the performance of construction heavy equipment promptly. This cannot be achieved through traditional management techniques, which are based on direct observation or on estimations from historical data. Some manufacturers have started to integrate their proprietary technologies, but construction contractors are unlikely to have a fleet of entirely new and single manufacturer equipment for this to represent a solution. Third party automated approaches include the use of active sensors such as accelerometers and gyroscopes, passive technologies such as computer vision and image processing, and audio signal processing. Hitherto, most …

Go to article

Traser: A Traffic Signal Event-Based Recorder, Chenhui Liu, Anuj Sharma, Edward Smaglik, Sirisha Kothuri Jan 2016

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 …

Go to article

Analytical Study Of Computer Vision-Based Pavement Crack Quantification Using Machine Learning Techniques, Soroush Mokhtari Jan 2015

Analytical Study Of Computer Vision-Based Pavement Crack Quantification Using Machine Learning Techniques, Soroush Mokhtari

Electronic Theses and Dissertations

Image-based techniques are a promising non-destructive approach for road pavement condition evaluation. The main objective of this study is to extract, quantify and evaluate important surface defects, such as cracks, using an automated computer vision-based system to provide a better understanding of the pavement deterioration process. To achieve this objective, an automated crack-recognition software was developed, employing a series of image processing algorithms of crack extraction, crack grouping, and crack detection. Bottom-hat morphological technique was used to remove the random background of pavement images and extract cracks, selectively based on their shapes, sizes, and intensities using a relatively small number …

Go to article

Data-Driven Simulation Modeling Of Construction And Infrastructure Operations Using Process Knowledge Discovery, Reza Akhavian Jan 2015

Data-Driven Simulation Modeling Of Construction And Infrastructure Operations Using Process Knowledge Discovery, Reza Akhavian

Electronic Theses and Dissertations

Within the architecture, engineering, and construction (AEC) domain, simulation modeling is mainly used to facilitate decision-making by enabling the assessment of different operational plans and resource arrangements, that are otherwise difficult (if not impossible), expensive, or time consuming to be evaluated in real world settings. The accuracy of such models directly affects their reliability to serve as a basis for important decisions such as project completion time estimation and resource allocation. Compared to other industries, this is particularly important in construction and infrastructure projects due to the high resource costs and the societal impacts of these projects. Discrete event simulation …

Go to article

Integrated Data Fusion And Mining (Idfm) Technique For Monitoring Water Quality In Large And Small Lakes, Benjamin Vannah Jan 2013

Integrated Data Fusion And Mining (Idfm) Technique For Monitoring Water Quality In Large And Small Lakes, Benjamin Vannah

Electronic Theses and Dissertations

Monitoring water quality on a near-real-time basis to address water resources management and public health concerns in coupled natural systems and the built environment is by no means an easy task. Furthermore, this emerging societal challenge will continue to grow, due to the ever-increasing anthropogenic impacts upon surface waters. For example, urban growth and agricultural operations have led to an influx of nutrients into surface waters stimulating harmful algal bloom formation, and stormwater runoff from urban areas contributes to the accumulation of total organic carbon (TOC) in surface waters. TOC in surface waters is a known precursor of disinfection byproducts …

Go to article

Analyses Of Crash Occurence And Injury Severities On Multi Lane Highways Using Machine Learning Algorithms, Abhishek Das Jan 2009

Analyses Of Crash Occurence And Injury Severities On Multi Lane Highways Using Machine Learning Algorithms, Abhishek Das

Electronic Theses and Dissertations

Reduction of crash occurrence on the various roadway locations (mid-block segments; signalized intersections; un-signalized intersections) and the mitigation of injury severity in the event of a crash are the major concerns of transportation safety engineers. Multi lane arterial roadways (excluding freeways and expressways) account for forty-three percent of fatal crashes in the state of Florida. Significant contributing causes fall under the broad categories of aggressive driver behavior; adverse weather and environmental conditions; and roadway geometric and traffic factors. The objective of this research was the implementation of innovative, state-of-the-art analytical methods to identify the contributing factors for crashes and injury …

Go to article

First Prev