Genetic Programming Based Automated Machine Learning in Classifying ESG Performances-Reference-Cited by-同舟云学术

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Genetic Programming Based Automated Machine Learning in Classifying ESG Performances

Published:2024 Issue: Volume:12 Page:59612-59629
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Rahman Abdullah Sani Abd¹^ORCID,Masrom Suraya²,Rahman Rahayu Abdul³,Ibrahim Roslina⁴^ORCID,Gilal Abdul Rehman⁵^ORCID

Affiliation:

1. Faculty of Sciences and Information Technology, Universiti Teknologi PETRONAS, Seri Iskandar, Perak, Malaysia

2. College of Computing, Informatics and Mathematics, Universiti Teknologi MARA, Perak Branch, Malaysia

3. Faculty of Accounting, Universiti Teknologi MARA, Perak Branch, Malaysia

4. Razak Faculty of Technology and Informatics, Universiti Teknologi Malaysia, Kuala Lumpur, Malaysia

5. Knight Foundation School of Computing and Information Sciences, Florida International University, Miami, FL, USA

Funder

Universiti Teknologi PETRONAS through the International Collaborative Research Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10508368.pdf?arnumber=10508368

Reference41 articles.

1. Prediction of oil flow rate through an orifice flow meter: Artificial intelligence alternatives compared

2. A novel cluster detection of COVID-19 patients and medical disease conditions using improved evolutionary clustering algorithm star

3. Prediction of recurrent spontaneous abortion using evolutionary machine learning with joint self-adaptive sime mould algorithm

4. Robust multimodal registration of fluorescein angiography and optical coherence tomography angiography images using evolutionary algorithms

5. Evolutionary algorithms and decision trees for predicting poor outcome after endovascular treatment for acute ischemic stroke

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