Novel data mining algorithms for computing biomass policy determinations in the Union of Myanmar

Abstract

High biomass consumptions have large social, economic and ecological blessings as well as challenges to contend with. Computing biomass determinations demand renewable and non-renewable energy fact-findings. The study aims to exponent novel algorithms for computing biomass policy determinations for understanding benefits, costs, and uncertainties biomass energy uses bring to environment, livelihood and national economy. Conceptual frameworks for data mining algorithms help reveal critical understanding about biomass uses. Study normalizes data between 0 and 1 to avoid unseen biases. Analysis of results shows 0.8 for uses of biomass over net of other energies in Myanmar, the study area. This means energy uses place biomass in high performance level scientifically agreeing with Paretto 80-20 principle to influence biomass policy determinations. This analysis shows biomass offer solutions, nonetheless with some associating problems. Extrapolating renewable and non-renewable costs suggest policy design to improve economic, environment and social challenges using innovative research findings and outcomes.