Titlebook: Quality, Reliability, Security and Robustness in Heterogeneous Systems; 19th EAI Internation Victor C.M. Leung,Hezhang Li,Zhaolong Ning Con

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書目名稱Quality, Reliability, Security and Robustness in Heterogeneous Systems影響因子(影響力)




書目名稱Quality, Reliability, Security and Robustness in Heterogeneous Systems影響因子(影響力)學科排名




書目名稱Quality, Reliability, Security and Robustness in Heterogeneous Systems網(wǎng)絡(luò)公開度




書目名稱Quality, Reliability, Security and Robustness in Heterogeneous Systems網(wǎng)絡(luò)公開度學科排名




書目名稱Quality, Reliability, Security and Robustness in Heterogeneous Systems被引頻次




書目名稱Quality, Reliability, Security and Robustness in Heterogeneous Systems被引頻次學科排名




書目名稱Quality, Reliability, Security and Robustness in Heterogeneous Systems年度引用




書目名稱Quality, Reliability, Security and Robustness in Heterogeneous Systems年度引用學科排名




書目名稱Quality, Reliability, Security and Robustness in Heterogeneous Systems讀者反饋




書目名稱Quality, Reliability, Security and Robustness in Heterogeneous Systems讀者反饋學科排名

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Quality, Reliability, Security and Robustness in Heterogeneous Systems978-3-031-65126-7Series ISSN 1867-8211 Series E-ISSN 1867-822X

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Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engihttp://image.papertrans.cn/q/image/780406.jpg

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1867-8211 y and Privacy;?Quality of Service (QoS) and Quality of Experience (QoE);?Artificial Intelligence and Machine Learning II; Autonomous Vehicles..978-3-031-65125-0978-3-031-65126-7Series ISSN 1867-8211 Series E-ISSN 1867-822X

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Identification of?Economic Factors for?Mass Depression Based on?Panel Study and?Machine Learning economic indicators and mental disorders. This article is aimed to analyze the relationship between economic factors and the level of mass depression based on a panel study and machine learning methods. Experimental results based on panel study and machine learning demonstrate effectiveness of our proposed econometric model.

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Design and Implementation of Traffic Flow Prediction Model Based on Short and Long Time Memory Netwodel obtains the minimum average absolute percentage error MAPE value of 10.6% and the highest average accuracy of 89.4%, which has a good prediction effect and can improve the prediction work of short-term traffic flow.

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