An XGBoost Machine Learning Technique for RF Energy Harvesting Prediction in IP-enabled IoT Devices-Reference-Cited by-同舟云学术

An XGBoost Machine Learning Technique for RF Energy Harvesting Prediction in IP-enabled IoT Devices

Published:2023-07-06 Issue: Volume: Page:
ISSN:
Container-title:IEEE EUROCON 2023 - 20th International Conference on Smart Technologies
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Author:

Umeonwuka Obumneme Obiajulu¹,Adejumobi Babatunde Segun¹,Shongwe Thokozani²

Affiliation:

1. University of Johannesburg,Dept. of Elect. and Electr. Engr.,Johannesburg,South Africa

2. University of Johannesburg,Dept. of Elect. and Electr. Engr.,Johannesburg,2028

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10198869/10198877/10198926.pdf?arnumber=10198926

Reference20 articles.

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3. Support vector regression machines;drucker;Advances in neural information processing systems,1996

4. On a class of pattern-recognition learning algorithms;vapnik;Automation and Remote Control,1965

5. Predictive Modelling of RF Energy for Wireless Powered Communications

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