Application of a modified MOPSO algorithm and multi-layer artificial neural network in centrifugal pump optimization-Reference-Cited by-同舟云学术

Application of a modified MOPSO algorithm and multi-layer artificial neural network in centrifugal pump optimization

Published:2022-01-05 Issue:4 Volume:55 Page:580-598
ISSN:0305-215X
Container-title:Engineering Optimization
language:en
Short-container-title:Engineering Optimization

Author:

Gan Xingcheng¹^ORCID,Pei Ji¹^ORCID,Wang Wenjie¹²^ORCID,Yuan Shouqi¹^ORCID,Lin Bin³

Affiliation:

1. National Research Center of Pumps, Jiangsu University, Zhenjiang, P.R. China

2. Jiangsu Key Laboratory of Green Process Equipment, Zhenjiang, P.R. China

3. Shenyang Blower Group Nuclear Pump Co. Ltd, Shenyang, P.R. China

Funder

Natural Science Foundation of Jiangsu Province

Natural Science Foundation of China

Primary Research & Development Plan of Jiangsu Province

Jiangsu Key Laboratory of Green Process Equipment

Postgraduate Research & Practice Innovation Program of Jiangsu Province

China Scholarship Council

Publisher

Informa UK Limited

Subject

Applied Mathematics,Industrial and Manufacturing Engineering,Management Science and Operations Research,Control and Optimization,Computer Science Applications

Link

https://www.tandfonline.com/doi/pdf/10.1080/0305215X.2021.2015585

Reference37 articles.

1. Clerc, Maurice. 1999. “The swarm and the queen: towards a deterministic and adaptive particle swarm optimization.” In Proceedings of the 1999 congress on evolutionary computation-CEC99 (Cat. No. 99TH8406). Vol. 3. IEEE.

2. Application of Multipoint Optimization to the Design of Turbomachinery Blades

3. Application of modified NSGA-II algorithm to Combined Economic and Emission Dispatch problem

4. Eberhart, Russell, and James Kennedy. 1995. “A New Optimizer Using Particle Swarm Theory.” In Proceedings of the Sixth International Symposium on Micro Machine and Human Science (MHS'95), 39–43. Piscataway, NJ: IEEE.

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