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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Towards Food Service Sustainability In Suburban Environments By Optimally Locating Shared Anaerobic Digester Units, Rebecca Loraamm, Joni Downs, Robert Alonso Bair, Daniel Yeh
Towards Food Service Sustainability In Suburban Environments By Optimally Locating Shared Anaerobic Digester Units, Rebecca Loraamm, Joni Downs, Robert Alonso Bair, Daniel Yeh
Suburban Sustainability
Anaerobic digestion is an effective method for reducing food waste at the consumer level. Drawbacks associated with this strategy include high construction costs for multiple digester units and limited public awareness of the method’s commercial potential. Given the large scale problem of food waste, an approach establishing community partnerships between local businesses and primary schools is offered to combat the problem of food waste. Optimizing the placement of shared digester units enabling utilization by multiple stakeholders is the suggested mitigation method. This research explores application of the p-median problem to determine the set of optimal sites for shared anaerobic digester …
Generalized Clusterwise Regression For Simultaneous Estimation Of Optimal Pavement Clusters And Performance Models, Mukesh Khadka
Generalized Clusterwise Regression For Simultaneous Estimation Of Optimal Pavement Clusters And Performance Models, Mukesh Khadka
UNLV Theses, Dissertations, Professional Papers, and Capstones
The existing state-of-the-art approach of Clusterwise Regression (CR) to estimate pavement performance models (PPMs) pre-specifies explanatory variables without testing their significance; as an input, this approach requires the number of clusters for a given data set. Time-consuming ‘trial and error’ methods are required to determine the optimal number of clusters. A common objective function is the minimization of the total sum of squared errors (SSE). Given that SSE decreases monotonically as a function of the number of clusters, the optimal number of clusters with minimum SSE always is the total number of data points. Hence, the minimization of SSE is …