Comparison of Traditional ML Algorithms for Energy Consumption Prediction Models-Reference-Cited by-同舟云学术

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Comparison of Traditional ML Algorithms for Energy Consumption Prediction Models

Published:2022-10 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Future Networks World Forum (FNWF)
language:
Short-container-title:

Author:

Estrada Rebeca¹,Asanza Víctor²,Torres Danny³,Valeriano Irving³,Alvarado Daniel⁴

Affiliation:

1. Escuela Superior Politécnica del Litoral,Information Technology Center & Electrical Eng. and Computer Science Dep.,Guayaquil,Ecuador

2. Escuela Superior Politécnica del Litoral,Electrical Eng. and Computer Science Dep.,Guayaquil,Ecuador

3. Information Technology Center Escuela Superior Politécnica del Litoral,Guayaquil,Ecuador

4. Escuela Superior Politécnica del Litoral,Mechanical and Production Sciences Eng. Dep.,Guayaquil,Ecuador

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10056380/10056381/10056675.pdf?arnumber=10056675

Reference32 articles.

1. A regression-tree multilayer-perceptron hybrid strategy for the prediction of ore crushing-plate lifetimes

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