Health Assessment of Artillery Command Information System Based on Combination Model

2020 ◽  
pp. 845-852
Author(s):  
Hongtu Cai ◽  
Yuwen Liu ◽  
Qinchao Lu ◽  
Yanan Duan
Keyword(s):  
Information System ◽  
Health Assessment ◽  
Combination Model

scholarly journals Container Throughput Forecasting of Tianjin-Hebei Port Group Based on Grey Combination Model

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Chen He ◽  
Huipo Wang
Keyword(s):  
Neural Network ◽  
Information System ◽  
Bp Neural Network ◽  
Capacity Planning ◽  
Forecasting Model ◽  
Forecasting Accuracy ◽  
Combination Model ◽  
Comparison Results ◽  
Container Operation ◽  
Better Than

Container throughput forecasting plays an important role in port capacity planning and management. Regarding the issue of container throughput of Tianjin-Hebei Port Group, considering the container throughput is an incomplete grey information system affected by various factors, the effect is often unsatisfactory by adopting a single forecasting model. Therefore, this paper studies the issue by combining fractional GM (1, 1) and BP neural network. The comparison results show that the combination model performs better than other single models separately and has a higher level of forecasting accuracy. Furthermore, the combination model is adopted to forecast the container throughput of Tianjin-Hebei Port Group from 2021 to 2025, which would be a data reference for the future development optimization for the container operation of Tianjin-Hebei Port Group.

scholarly journals Service Evaluation of the English Refugee Health Information System: Considerations and Recommendations for Effective Resettlement

2021 ◽  
Vol 18 (19) ◽  
pp. 10331
Author(s):  
Thomas James Dunn ◽  
Annabel Browne ◽  
Steven Haworth ◽  
Fatima Wurie ◽  
Ines Campos-Matos
Keyword(s):  
Information System ◽  
Local Government ◽  
Health Information ◽  
Health Assessment ◽  
Health Information System ◽  
Service Evaluation ◽  
Refugee Health ◽  
Special Educational Needs ◽  
The Uk ◽  
Governance Processes

Since 2015, the UK has resettled over 25,000 refugees. To support resettlement and integration, refugees undergo a pre-arrival medical health assessment (MHA), which is used for healthcare planning by local government in England. This study aimed to understand the utility and effectiveness of the MHA and flow of data to support resettlement planning. Seven local government representatives were interviewed regarding their experiences and perceptions of the refugee health information system (HIS) and the MHA for resettlement in England. Data was analyzed using thematic analysis. The three themes indicated that the HIS was perceived to be effective, however, issues on governance, timeliness of information and access were identified. Findings showed that for the MHA to be more useful for planning, assessments for mental health issues and child special educational needs (SEN) are needed. Findings also indicated resettlement promoted joint working and acceptability of refugee resettlement. In areas where data sharing and governance processes are well defined, the HIS is effective and the MHA supports resettlement. National agencies should put structures in place to support timely health information flow.

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