Open Access Journal of Engineering Applications
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Decision Tree Classification for Heavy-Metal Adsorption

A Case Study in Bangladesh

Rafiqul Islam Corresponding 0000-0002-8295-8496
Indian Institute of Science
Amara Chen
Georgia Institute of Technology
Andreas Ahmed 0000-0001-2026-4657
National University of Sciences and Technology
Kamrul Uddin 0000-0002-2121-3857
Bangladesh University of Engineering and Technology
31 Mar 2015
pp. 683-716
https://doi.org/10.55555/oajea.2015.3901.033

Abstract

Traditional design methods for telecommunication networks frequently neglect several important aspects of heavy-metal adsorption that affect real performance. Discretisation of the domain allowed decision tree classification to be applied to the complex geometry involved. The optimised parameters raised the useful output by 36% while simultaneously reducing the overall losses. The results support the adoption of the proposed method in routine engineering practice.
Keywords: heavy-metal adsorptiondecision tree classificationrenewable energyvibration analysisbiodiesel

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