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Operations Research, Systems Engineering and Industrial Engineering Commons™
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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Analyzing The Fundamental Aspects And Developing A Forecasting Model To Enhance The Student Admission And Enrollment System Of Msom Program, Sultanul Nahian Hasnat
Analyzing The Fundamental Aspects And Developing A Forecasting Model To Enhance The Student Admission And Enrollment System Of Msom Program, Sultanul Nahian Hasnat
Graduate Theses and Dissertations
A forecasting model, associated with predictive analysis, is an elementary requirement for academic leaders to plan course requirements. The M.S. in Operations Management (MSOM) program at the University of Arkansas desires to understand future student enrollment more accurately. The available literature shows that there is an absence of forecasting models based on quantitative, qualitative and predictive analysis. This study develops a combined forecasting model focusing on three admission stages. The research uses simple regression, Delphi analysis, Analysis of Variance (ANOVA), and classification tree system to develop the models. It predicts that 272, 173, and 136 new students will apply, matriculate …
Solar Irradiance Forecasting Using Deep Neural Networks, Ahmad Alzahrani, Pourya Shamsi, Cihan H. Dagli, Mehdi Ferdowsi
Solar Irradiance Forecasting Using Deep Neural Networks, Ahmad Alzahrani, Pourya Shamsi, Cihan H. Dagli, Mehdi Ferdowsi
Electrical and Computer Engineering Faculty Research & Creative Works
Predicting solar irradiance has been an important topic in renewable energy generation. Prediction improves the planning and operation of photovoltaic systems and yields many economic advantages for electric utilities. The irradiance can be predicted using statistical methods such as artificial neural networks (ANN), support vector machines (SVM), or autoregressive moving average (ARMA). However, they either lack accuracy because they cannot capture long-term dependency or cannot be used with big data because of the scalability. This paper presents a method to predict the solar irradiance using deep neural networks. Deep recurrent neural networks (DRNNs) add complexity to the model without specifying …