Engineering Commons^™

Development Of Flood Prediction Models Using Machine Learning Techniques, Bhanu Kanwar

Doctoral Dissertations

"Flooding and flash flooding events damage infrastructure elements and pose a significant threat to the safety of the people residing in susceptible regions. There are some methods that government authorities rely on to assist in predicting these events in advance to provide warning, but such methodologies have not kept pace with modern machine learning. To leverage these algorithms, new models must be developed to efficiently capture the relationships among the variables that influence these events in a given region. These models can be used by emergency management personnel to develop more robust flood management plans for susceptible areas. The research …

Machine Learning Applications In Plant Identification, Wireless Channel Estimation, And Gain Estimation For Multi-User Software-Defined Radio, Viraj K. Gajjar

Doctoral Dissertations

"This work applies machine learning (ML) techniques to selected computer vision and digital communication problems. Machine learning algorithms can be trained to perform a specific task without explicit programming. This research applies ML to the problems of: plant identification from images of leaves, channel state information (CSI) estimation for wireless multiple-input-multiple-output (MIMO) systems, and gain estimation for a multi-user software-defined radio (SDR) application.

In the first task, two methods for plant species identification from leaf images are developed. One of the methods uses hand-crafted features extracted from leaf images to train a support vector machine classifier. The other method combines …

Enhancing Management Of Built And Natural Water And Sanitation Systems With Data Science, Nelson Da Luz

Doctoral Dissertations

In the age of the data revolution, the civil engineer can enhance the management of infrastructure systems using new techniques focused on data. This dissertation present three studies in which data science approaches are used to enhance management of water and sanitation systems in both the built and natural environments. Chapters 1 and 2 focus on improving methods for data collection relating to water quality monitoring. In Chapter 1, the efficacy of different water quality sampling program designs is evaluated as the programs relate to meeting monitoring goals. Considerations include how timing, location, and distribution system operations can affect monitoring …