BP neural network is optimized by improved particle swarm optimization (PSO), the prediction model of knowledge transfer effect is established, and the prediction effect is compared with that of BP neural network model. The research results show that the prediction effect of knowledge transfer effect prediction model based on particle swarm optimization (PSO) optimized BP neural network is due to BP neural network.

Lin Wang. Prediction of Knowledge Transfer Effect Based on Particle Swarm Optimization Improved BP Neural Network. International Journal of New Developments in Engineering and Society (2021) Vol.5, Issue 3: 26-30. https://doi.org/10.25236/IJNDES.2021.050303.

[1] LIU Guoxin, CUI Hainan, WANG Lin. Simulation Research on the Prediction of Knowledge Transfer Effect in Enterprise Innovation Network [J]. Journal of WUT (Information & Management Engineering), 2021, 43(2): 155-160.

[2]Szulanski G, Cappetta R, Jensen R. J. When and How Trustworthiness Matters: Knowledge Transfer and the Moderating Effect of Causal Ambiguity [J]. Organization Science, 2004, 15(5): 600-613.

[3]Walton R. E. The Diffusion of New Work Structures: Explaining Why Success Didn't Take [J]. Organizational Dynamics, 1975, 3(3): 3-22.

[4] Jiang Huawei, Guo Tao, Yang Zhen. Prediction model of wheat storage quality based on IPSO-BPNN algorithm [J]. Science Technology and Engineering, 2021, 21(21): 8951-8956.

[5] HE Dan, LIN Laipeng, LI Xiaoyong, NIU Guoqiang, YI Xiaohui,HUANG Mingzhi. A Soft Measurement Model of Wastewater Treatment Process Based onBP Neural Network with Improved Particle Swarm Optimization Algorithms [J]. .Journal of South China Normal University (Natural Science Edition), 2021, 53(2): 114-120.

[6] DUAN Xin-hui, LI Wen-xin. Ultra-short-term Wind Speed Prediction Based on Improved Particle Swarm Neural Network Algorithm [J]. Automation & Instrumentation, 2021, 36(3): 76-80.