Research on human resource management performance evaluation based on BP algorithm

[1] Yang S. Research on top manager comprehensive performance evaluation based on bp neural network algorithm. 2007. Search in Google Scholar

[2] Zhu S, Liu Y. Analysis of Human Resource Allocation Model for Tourism Industry Based on Improved BP Neural Network[J]. Journal of Mathematics, 2022, 2022. Search in Google Scholar

[3] Hongan H U, Sun Y. Quantitative analysis of the university human resources based on BP neural network[J]. Journal of Zhoukou Normal University, 2012. Search in Google Scholar

[4] Li X, Zhang L, Li D, et al. Construction and Simulation of a Strategic HR Decision Model Based on Recurrent Neural Network[J]. Journal of Mathematics, 2022, 2022. Search in Google Scholar

[5] Zhao J, Li B. Credit risk assessment of small and medium-sized enterprises in supply chain finance based on SVM and BP neural network[J]. Neural Computing and Applications:1-12. Search in Google Scholar

[6] Yan X, Deng X, Sun S. Analysis and Simulation of the Early Warning Model for Human Resource Management Risk Based on the BP Neural Network[J]. Complexity, 2020, 2020. Search in Google Scholar

[7] Zhang Z.BP neural network trade volume prediction and enterprises HRM optimization model based on ES-LM training[J]. Journal of Intelligent and Fuzzy Systems, 2020, 39(4):5883-5894. Search in Google Scholar

[8] Li T, Sun J, Wang L. An intelligent optimization method of motion management system based on BP neural network[J]. Neural Computing and Applications, 2020(4). Search in Google Scholar

[9] Gomez-Cedeno M, Castan-FaRrero J M, Guitart-Tarres L, et al. Impact of human resources on supply chain management and performance[J]. Industrial Management & Data Systems, 2015, 115(1):129-157. Search in Google Scholar

[10] Song S, Xiong X, Wu X, et al. Modeling the SOFC by BP neural network algorithm[J]. International Journal of Hydrogen Energy, 2021. Search in Google Scholar

[11] Yang Z, Shen Y, Yang F, et al. A comprehensive real-time state evaluation strategy for distribution equipment based on MI-PSO-BP algorithm[J]. International Transactions on Electrical Energy Systems, 2019(2). Search in Google Scholar

[12] Liang G M. A Closed-Loop Controlling Iterative Image Segmentation Algorithm Based on BP Neural-Network Evaluation[J]. Signal Processing, 2009. Search in Google Scholar

[13] Zhang I. An optimised product-unit neural network with a novel PSO–BP hybrid training algorithm: Applications to load–deformation analysis of axially loaded piles[J]. Engineering Applications of Artificial Intelligence, 2013. Search in Google Scholar

[14] Jing L, Ashraf M A. Face recognition method based on GA-BP neural network algorithm[J]. Open Physics, 2018, 16. Search in Google Scholar

[15] Zhao N, Tsai S B. Research on Prediction Model of Hotels-Development Scale Based on BP Artificial Neural Network Algorithm[J]. Mathematical Problems in Engineering, 2021. Search in Google Scholar

[16] Ran Y, Xiong G, Li S, et al. Study on deformation prediction of landslide based on genetic algorithm and improved BP neural network[J]. Kybernetes, 2010. Search in Google Scholar

[17] Lu X, Wang Y, Li J, et al. Three-dimensional coordinate measurement algorithm by optimizing BP neural network based on GA[J]. Engineering Computations, 2019, 36(6):2066-2083. Search in Google Scholar

[18] Bai, TC, Meng, et al. A forecasting method of forest pests based on the rough set and PSO-BP neural network[J]. NEURAL COMPUT APPL, 2014. Search in Google Scholar

[19] Shin Y,Mohanty BP.Grid-based disaggregation algorithm with a new simulation-optimization scheme for remotely sensed soil moisture[J]. human reproduction, 2010. Search in Google Scholar

[20] Li Z, Sun B, Xin Y, et al. A Computational Method for Optimizing Experimental Environments for Phellinus igniarius via Genetic Algorithm and BP Neural Network[J]. Biomed Research International, 2016, 2016:1-6. Search in Google Scholar

[21] Wei G, Jin Y. Human resource management model based on three-layer BP neural network and machine learning[J]. Journal of Intelligent and Fuzzy Systems, 2021, 40(2):2289-2300. Search in Google Scholar

[22] Yang X, Zhou J J, Wen D Q. An optimized BP neural network model for teaching management evaluation[J]. Journal of Intelligent and Fuzzy Systems, 2020(3):1-7. Search in Google Scholar

[23] Zhang C. Evaluation and analysis of human resource management mode and its talent screening factors based on decision tree algorithm[J]. The Journal of Supercomputing:1-33. Search in Google Scholar

[24] Bhattacharyya D S, Dutta G K, Nowrin I, et al. Implementing a digital human resources management tool in the government health sector in Bangladesh: a policy content analysis[J]. BMC Health Services Research, 2021. Search in Google Scholar

[25] Yang J, Hu Y, Zhang K, et al. An improved evolution algorithm using population competition genetic algorithm and self-correction BP neural network based on fitness landscape[J]. Soft Computing, 2020(3). Search in Google Scholar