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Full-Text Articles in Computer Sciences
Forecasting Smart Meter Energy Usage Using Distributed Systems And Machine Learning, Feiran Ji, Chris Dong, Lingzhi Du, Zizhen Song, Yuedi Zheng, Paul Intrevado
Forecasting Smart Meter Energy Usage Using Distributed Systems And Machine Learning, Feiran Ji, Chris Dong, Lingzhi Du, Zizhen Song, Yuedi Zheng, Paul Intrevado
Creative Activity and Research Day - CARD
In this research, we explore the technical and computational merits of a machine learning algorithm on a large data set, employing distributed systems. Using 167 million(10 GB) energy consumption observations collected by smart meters from residential consumers in London, England, we predict future residential energy consumption using a Random Forest machine learning algorithm. Distributed systems such as AWS S3 and EMR, MongoDB and Apache Spark are used. Computational times and predictive accuracy are evaluated. We conclude that there are significant computational advantages to using distributed systems when applying machine learning algorithms on large-scale data. We also observe that distributed systems …
An Optimization Approach To Automate The Generation Of Radiotherapy Treatment Plans, Qian Li
An Optimization Approach To Automate The Generation Of Radiotherapy Treatment Plans, Qian Li
Creative Activity and Research Day - CARD
The main goal of radiotherapy is to deliver a specified dose of radiation directly to the tumor while minimizing radiation damage to healthy tissues. Currently, the treatment plan is being developed by professional planners using a commercial treatment planning system. In this treatment planning system, the planner modifies the objectives and weights of the objectives until an ideal combination of doses is achieved. This arbitrary process can cost a few hours or a day to finish. My research aims to automate the generation of the plans by implementing an optimization algorithm on top of the treatment planning system using gradient …