期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
Prediction of Disease Transmission Risk in Universities Based on SEIR and Multi-hidden Layer Back-propagation Neural Network Model
1
作者 Jiangjiang Li Lijuan Feng 《IJLAI Transactions on Science and Engineering》 2024年第1期24-31,共8页
Against the background of regular epidemic prevention and control,in order to ensure the return of teachers to work,students to return to school and safe operation of schools,the risk of disease transmission is analyz... Against the background of regular epidemic prevention and control,in order to ensure the return of teachers to work,students to return to school and safe operation of schools,the risk of disease transmission is analyzed in key areas such as university canoons,auditoriums,teaching buildings and dormitories.The risk model of epidemic transmission in key regions of universities is established based on the improved SEIR model,considering the four groups of people,namely susceptible,latent,infected and displaced,and their mutual transformation relationship.After feature post-processing,the selected feature parameters are processed with monotone non-decreasing and smoothing,and used as noise-free samples of stacked sparse denoising automatic coding network to train the network.Then,the feature vectors after dimensionality reduction of the stacked sparse denoising automatic coding network are used as the input of the multi-hidden layer back-propagation neural network,and these features are used as tags to carry out fitting training for the network.The results show that the implementation of control measures can reduce the number of contacts between infected people and susceptible people,reduce the transmission rate of single contact,and reduce the peak number of infected people and latent people by 61%and 72%respectively,effectively controlling the disease spread in key regions of universities.Our method is able to accurately predict the number of infections. 展开更多
关键词 Disease transmission SEIR model PREDICTION Stacked sparse denoising automatic coding network
原文传递
Advanced ECU Software Development Method for Fuel Cell Systems 被引量:3
2
作者 田硕 刘原 +2 位作者 夏文川 李建秋 欧阳明高 《Tsinghua Science and Technology》 SCIE EI CAS 2005年第5期610-617,共8页
The electronic control unit (ECU) in electrical powered hybrid and fuel cell vehicles is exceedingly complex. Rapid prototyping control is used to reduce development time and eliminate errors during software develop... The electronic control unit (ECU) in electrical powered hybrid and fuel cell vehicles is exceedingly complex. Rapid prototyping control is used to reduce development time and eliminate errors during software development. This paper describes a high-efficiency development method and a flexible tool chain suitable for various applications in automotive engineering. The control algorithm can be deployed directly from a Matlab/Simulink/Stateflow environment into the ECU hardware together with an OSEK real-time operating system (RTOS). The system has been successfully used to develop a 20-kW fuel cell system ECU based on a Motorola PowerPC 555 (MPC555) microcontroller. The total software development time is greatly reduced and the code quality and reliability are greatly enhanced. 展开更多
关键词 automotive engineering fuel cell electronic controller unit (ECU) embedded software development rapid prototyping automatic code generation SIMULATION OSEK
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部