Input-Target database, machine learning modeling.xlsx (107.46 kB)

Input-Target database, machine learning modeling

dataset

posted on 2023-08-30, 10:19 authored by Daniel FozerDaniel Fozer

The dataset contains input and target variables for Waste-to-DME plant scenarios that were used to develop artificial neural networks. Applied waste types: (1) the organic fraction of municipal solid waste (OFMSW), (2) sewage sludge (SS).

Funding

OTKA: 128543

OTKA: 131586

EU LIFE program, LIFE-CLIMCOOP (LIFE19 CCA/HU/001320)

GINOP 2.3.4-15-2016-00004

EU project: CZ.02.1.01/0.0/0.0/15 003/0000456

FWO Vlaanderen/Research Foundation Flanders: 1215523N

History

ORCID for corresponding depositor

https://orcid.org/0000-0002-1712-8989

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Keywords

Waste-to-DME Hydrothermal Gasification OFMSW Sewage sludge Synthesis gas Dimethyl ether Machine learning Artificial neural network Chemical process design

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CC0

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