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Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Online And Adjusted Human Activities Recognition With Statistical Learning, Yanjia Zhang
Online And Adjusted Human Activities Recognition With Statistical Learning, Yanjia Zhang
USF Tampa Graduate Theses and Dissertations
Wearable human activity recognition (HAR) is a widely application system for our daily life. It hasbeen built in many devices, such as smartphone, smartwatch, activity tracker, and health monitor. Many researchers try to develop a system which requires less memory space and power, but has fast and accurate classification results. Moreover, the objective of adjusting the classifier by the system self is also a study direction. In the present study, we introduced the machine learning methods to both smartphone data and smartwatch data and an adjusted model with the continuous generating data. Further, we also proposed a new HAR system …
Adaptive Analytics: It’S About Time, Charles Dziuban, Colm Howlin, Patsy Moskal, Tammy Muhs, Connie Johnson, Rachel Griffin, Carissa Hamilton
Adaptive Analytics: It’S About Time, Charles Dziuban, Colm Howlin, Patsy Moskal, Tammy Muhs, Connie Johnson, Rachel Griffin, Carissa Hamilton
Current Issues in Emerging eLearning
This article describes a cooperative research partnership among a large public university, a for-profit private institution and their common adaptive learning platform provider. The focus of this work explored adaptive analytics that uses data the investigators describe as metaphorical “digital learning dust” produced by the platform as a matter of course. The information configured itself into acquired knowledge, growth, baseline status and engagement. Two complimentary models evolved. The first, in the public university, captured end-of-course data for predicting success. The second approach, in the private university, formed the basis of a dynamic real-time data analytic algorithm. In both cases the …
Deep Learning For Load Forecasting With Smart Meter Data: Online Adaptive Recurrent Neural Network, Mohammad Navid Fekri, Harsh Patel, Katarina Grolinger, Vinay Sharma
Deep Learning For Load Forecasting With Smart Meter Data: Online Adaptive Recurrent Neural Network, Mohammad Navid Fekri, Harsh Patel, Katarina Grolinger, Vinay Sharma
Electrical and Computer Engineering Publications
No abstract provided.
An Experimental Analysis Of Adaptive Learning In A Multi-Subject Economy, David Martin
An Experimental Analysis Of Adaptive Learning In A Multi-Subject Economy, David Martin
Business and Economics Honors Papers
The rational expectations hypothesis (REH) has long served as a foundation in macroeconomic laws of motion. However, the assumptions of REH are likely too powerful to be representative of economic actors. This research evaluates adaptive learning, a developing alternative to rational expectations, using a multi-agent macroeconomic prediction “game.” Data was gathered from a group of students, each predicting the outcome of a single economy over time. Each agent was asked to forecast output (GDP) and inflation in each period based on historic levels of output, inflation, and interest rates. These data were then analyzed under various theoretical models of adaptive …