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Determination of Rate of Medical Waste Generation Using RVM, MARS and MPMR
Jagan j, Pijush samui, Barnali dixon
Published in IGI Global
Pages: 1 - 18
The prediction of medical waste generation is an important task in hospital waste management. This article uses Relevance Vector Machine (RVM), Multivariate Adaptive Regression Spline (MARS) and Minimax Probability Machine Regression (MPMR) for prediction of rate of medical waste generation. Type of hospital, Capacity and Bed Occupancy has been used as inputs of RVM, MARS and MPMR. RVM is a probabilistic bayesian learning framework. MARS builds flexible model by using piecewise linear regressions. MPMR maximizes the minimum probability that future predicted outputs of the regression model will be within some bound of the true regression function. MARS, RVM and MPMR have been used as regression techniques. The results show that the developed RVM, MPMR and MARS give excellent models for determination of rate of medical waste generation.
About the journal
JournalAdvances in Environmental Engineering and Green Technologies Handbook of Research on Waste Management Techniques for Sustainability
PublisherIGI Global
Open Access0