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Full-Text Articles in Physical Sciences and Mathematics

Application Of Data-Driven And Process-Based Modeling Approaches For Water Quality Simulation In Lakes And Freshwater Reservoirs, Ali Saber Sichani Dec 2019

Application Of Data-Driven And Process-Based Modeling Approaches For Water Quality Simulation In Lakes And Freshwater Reservoirs, Ali Saber Sichani

UNLV Theses, Dissertations, Professional Papers, and Capstones

Lakes and freshwater reservoirs often serve as the primary drinking and irrigation water sources for surrounding communities. They provide recreational and tourism opportunities, thereby promoting the prosperity of neighboring communities. Reliable estimates of water quality in lakes and reservoirs can improve management practices to protect water resources.

Seasonal water temperature and solar shortwave radiation variations, and their subsequent interactions with water column aquatic life, combined with seasonal variations of mixing intensity throughout the water column, result in variations of water quality constituents with depth during the annual cycle. The complexity of these variations entails the use of advanced water quality …


Implementation Of Multivariate Artificial Neural Networks Coupled With Genetic Algorithms For The Multi-Objective Property Prediction And Optimization Of Emulsion Polymers, David Chisholm Jun 2019

Implementation Of Multivariate Artificial Neural Networks Coupled With Genetic Algorithms For The Multi-Objective Property Prediction And Optimization Of Emulsion Polymers, David Chisholm

Master's Theses

Machine learning has been gaining popularity over the past few decades as computers have become more advanced. On a fundamental level, machine learning consists of the use of computerized statistical methods to analyze data and discover trends that may not have been obvious or otherwise observable previously. These trends can then be used to make predictions on new data and explore entirely new design spaces. Methods vary from simple linear regression to highly complex neural networks, but the end goal is similar. The application of these methods to material property prediction and new material discovery has been of high interest …