A Novel Flower Pollination Algorithm for Modeling the Boiler Thermal Efficiency

  • Peifeng Niu
  • Jinbai Li
  • Lingfang Chang
  • Xianchen Zhang
  • Rongyan Wang
  • Guoqiang Li


The flower pollination algorithm (FPA) is a nature-inspired optimization algorithm. To improve the solution quality and convergence speed of FPA, we proposed a novel flower pollination algorithm (NFPA) which is a hybrid algorithm based on original FPA and wind driven optimization algorithm. Simulation experiments demonstrate that NFPA has better search performance on classical numerical function optimizations compared with other the state-of-the-art optimization methods. In addition, the NFPA is adopted to optimize parameters of fast learning network to build thermal efficiency model of a 330 MW coal-fired boiler and a well-generalized model is obtained. Experimental results show that the tuned fast learning network model by NFPA has better prediction accuracy and generalization ability than other combination models.


Flower pollination algorithm Fast learning network Thermal efficiency Coal-fired boiler 



Project supported by the National Natural Science Foundation of China (Grant Nos. 61573306 and 61403331), Natural Science Foundation of Hebei Province (Grant No. F2016203427). We would like to thank reviewers and editors for their constructive suggestions.

Compliance with Ethical Standards

Conflict of interest

All authors declares that they have no conflict of interest.

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the authors.


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Authors and Affiliations

  1. 1.Key Lab of Industrial Computer Control Engineering of Hebei ProvinceYanshan UniversityQinhuangdaoChina
  2. 2.National Engineering Research Center for Equipment and Technology of Cold Strip RollingQinhuangdaoChina

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