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Full-Text Articles in Business
Machine Learning Predictions Of Electricity Capacity, Marcus Harris, Elizabeth Kirby, Ameeta Agrawal, Rhitabrat Pokharel, Francis Puyleart, Martin Zwick
Machine Learning Predictions Of Electricity Capacity, Marcus Harris, Elizabeth Kirby, Ameeta Agrawal, Rhitabrat Pokharel, Francis Puyleart, Martin Zwick
Systems Science Faculty Publications and Presentations
This research applies machine learning methods to build predictive models of Net Load Imbalance for the Resource Sufficiency Flexible Ramping Requirement in the Western Energy Imbalance Market. Several methods are used in this research, including Reconstructability Analysis, developed in the systems community, and more well-known methods such as Bayesian Networks, Support Vector Regression, and Neural Networks. The aims of the research are to identify predictive variables and obtain a new stand-alone model that improves prediction accuracy and reduces the INC (ability to increase generation) and DEC (ability to decrease generation) Resource Sufficiency Requirements for Western Energy Imbalance Market participants. This …
Reconstructability Analysis: Discrete Multivariate Modeling, Martin Zwick
Reconstructability Analysis: Discrete Multivariate Modeling, Martin Zwick
Systems Science Faculty Publications and Presentations
An introduction to Reconstructability Analysis for the Discrete Multivariate Modeling course and for other purposes.
Using Reconstructability Analysis For Input Variable Reduction: A Business Example, Stephen Shervais, Martin Zwick
Using Reconstructability Analysis For Input Variable Reduction: A Business Example, Stephen Shervais, Martin Zwick
Systems Science Faculty Publications and Presentations
We demonstrate the use of reconstructability analysis (RA) on the UCI Australian Credit dataset to reduce the number of input variables for two different analysis tools. Using 14 variables, an artificial neural net (NN) is able to predict whether or not credit was granted, with a 79.1% success rate. RA preprocessing allows us to reduce the number of independent variables from 14 to two different sets of three, which have success rates of 77.2% and 76.9% respectively. The difference between these rates and that of the 14-variable NN is not statistically significant. The three-variable rulesets given by RA achieve success …
An Agent-Based Model Of Trade With Distance-Based Transaction Cost, Kumar Venkat, Wayne W. Wakeland
An Agent-Based Model Of Trade With Distance-Based Transaction Cost, Kumar Venkat, Wayne W. Wakeland
Systems Science Faculty Publications and Presentations
This paper describes an application of agent-based modeling to investigate the effect of a distance-based transaction cost on trade. Long-distance trade is rapidly increasing, but may ultimately be constrained by our ability to move material goods between sellers and buyers. Unlike information exchange, trade in material goods is dependent on the price of oil and vulnerable to future scarcities of oil. In addition, there are growing concerns about greenhouse gas emissions from long-distance transportation. Our purpose in this study is to take the first step in understanding the impact of a distance constraint on free global trade using a simple …