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Full-Text Articles in Engineering
Machine Learning Methods To Map Stabilizer Effectiveness Based On Common Soil Properties, Amit Gajurel
Machine Learning Methods To Map Stabilizer Effectiveness Based On Common Soil Properties, Amit Gajurel
Boise State University Theses and Dissertations
Unconfined compressive strength (UCS) has been widely used as one of the primary criteria for the selection of optimum type and amount of chemical stabilizer for subgrade/base stabilization. Guidelines established by various state and federal agencies aid in selecting these optimum values by recommending an initial type and amount based on a wide range of soil index properties. A significant number of laboratory trials have to be done to establish the optimum type and amount of stabilizer for a given target strength. This process takes a copious amount of time, money, and the workforce. In addition to that, the finite …
A Machine Learning Approach For Power Allocation In Hetnets Considering Qos, Roohollah Amiri, Hani Mehrpouyan, Lex Fridman, Ranjan K. Mallik, Arumugam Nallanathan, David Matolak
A Machine Learning Approach For Power Allocation In Hetnets Considering Qos, Roohollah Amiri, Hani Mehrpouyan, Lex Fridman, Ranjan K. Mallik, Arumugam Nallanathan, David Matolak
Electrical and Computer Engineering Faculty Publications and Presentations
There is an increase in usage of smaller cells or femtocells to improve performance and coverage of next-generation heterogeneous wireless networks (HetNets). However, the interference caused by femtocells to neighboring cells is a limiting performance factor in dense HetNets. This interference is being managed via distributed resource allocation methods. However, as the density of the network increases so does the complexity of such resource allocation methods. Yet, unplanned deployment of femtocells requires an adaptable and self-organizing algorithm to make HetNets viable. As such, we propose to use a machine learning approach based on Q-learning to solve the resource allocation …