Modified aquila optimizer for forecasting oil production-Reference-Cited by-同舟云学术

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Modified aquila optimizer for forecasting oil production

Published:2022-05-10 Issue:4 Volume:25 Page:519-535
ISSN:1009-5020
Container-title:Geo-spatial Information Science
language:en
Short-container-title:Geo-spatial Information Science

Author:

Al-qaness Mohammed A. A.¹^ORCID,Ewees Ahmed A.²³^ORCID,Fan Hong¹^ORCID,AlRassas Ayman Mutahar⁴^ORCID,Abd Elaziz Mohamed⁵⁶⁷^ORCID

Affiliation:

1. State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China

2. Systems, University of Bisha Department of e-, Bisha, Kingdom of Saudi Arabia

3. Department of Computer, Damietta University, Damietta, Egypt

4. School of Petroleum Engineering, China University of Petroleum (East China), Qingdao, China

5. Department of Mathematics, Faculty of Science, Zagazig University, Zagazig, Egypt

6. Artificial Intelligence Research Center (AIRC), Ajman University, Ajman 346, United Arab Emirates

7. Faculty of Computer Science & Engineering, Galala University, Suze 435611, Egypt

Funder

National Key Research and Development Program of China

LIESMARS Special Research Funding

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Computers in Earth Sciences,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10095020.2022.2068385

Reference59 articles.

1. Improving Adaptive Neuro-Fuzzy Inference System Based on a Modified Salp Swarm Algorithm Using Genetic Algorithm to Forecast Crude Oil Price

2. Development of Oil Production Forecasting Method based on Deep Learning

3. Aquila Optimizer: A novel meta-heuristic optimization algorithm

4. A LSSVM approach for determining well placement and conning phenomena in horizontal wells

5. Comparison of machine learning methods for estimating permeability and porosity of oil reservoirs via petro-physical logs

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