Predict Hypotension Events during Spinal Anesthesia Based on Particle Swarm Optimization Neural Networks

摘要：

Neural network model based on particle swarm optimization (PSO) was established for predicting hypotension during general anesthesia. The BP neural network parameters optimized by pso, and learning samples are trained and modeled by BP neural network with optimal parameters. The simulation experiment is carried out with MATLAB. The result indicated that the model forecasting results are close with the actual results and meet the accuracy requirement to General Anesthesia.

关键词： Neural Network Particle Swarm Optimization Anesthesia

作者: Haijun Dai Yu Qiu

作者单位: Anesthesiology Department, The 209th Hospital of Peoples Liberation Army (PLA), Mudanjiang 157000, China

会议类型: 国际会议

会议名称: 2012 International Conference on Advanced Materials Design and Machanics(2012先进材料设计与机械学国际会议 ICAMDM 2012)

会议地点: 厦门

会议语种:英文

页码: 733-736

在线出版日期: 2012-06-05（万方平台首次上网日期，不代表论文的发表时间）