Improving accuracy and efficiency of the machined PEEK denture based on NSGA-II integrated GABP neural network.

Journal: Dental materials : official publication of the Academy of Dental Materials
PMID: 39127598

Abstract

OBJECTIVES: The polymer polyetheretherketone (PEEK) is gradually being used in dental restorations because of its excellent mechanical properties, chemical resistance, fatigue resistance, thermal stability, radiation translucency and good biocompatibility. To process PEEK dentures with lower surface roughness as quickly as possible, the non-dominated sorting genetic algorithm-II (NSGA-II) integrated genetic algorithm back propagation (GABP) neural network was proposed, which can adjust the combination of process parameters for milling PEEK dentures.

Authors

  • Hao Jia
    School of Environmental Science and Engineering, Shaanxi University of Science and Technology, Xi'an 170021, China.
  • Shuting Liang
    School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130025, China; Key Laboratory of CNC Equipment Reliability, Ministry of Education, Jilin University, Changchun, China.
  • Ji Zhao
    School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130025, China; Key Laboratory of CNC Equipment Reliability, Ministry of Education, Jilin University, Changchun, China; School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110167, China.
  • Jingjin Li
    School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130025, China; Key Laboratory of CNC Equipment Reliability, Ministry of Education, Jilin University, Changchun, China.
  • Handa Dai
    School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130025, China; Key Laboratory of CNC Equipment Reliability, Ministry of Education, Jilin University, Changchun, China.
  • Shijun Ji
    Department of Paediatric Orthopaedics, Shengjing Hospital of China Medical University, Shenyang, Liaoning Province, China.

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