標題: Titlebook: Big Data Analytics for Smart Transport and Healthcare Systems; Saeid Pourroostaei Ardakani,Ali Cheshmehzangi Book 2023 The Editor(s) (if a [打印本頁] 作者: 法官所用 時間: 2025-3-21 17:03
書目名稱Big Data Analytics for Smart Transport and Healthcare Systems影響因子(影響力)
書目名稱Big Data Analytics for Smart Transport and Healthcare Systems影響因子(影響力)學科排名
書目名稱Big Data Analytics for Smart Transport and Healthcare Systems網(wǎng)絡(luò)公開度
書目名稱Big Data Analytics for Smart Transport and Healthcare Systems網(wǎng)絡(luò)公開度學科排名
書目名稱Big Data Analytics for Smart Transport and Healthcare Systems被引頻次
書目名稱Big Data Analytics for Smart Transport and Healthcare Systems被引頻次學科排名
書目名稱Big Data Analytics for Smart Transport and Healthcare Systems年度引用
書目名稱Big Data Analytics for Smart Transport and Healthcare Systems年度引用學科排名
書目名稱Big Data Analytics for Smart Transport and Healthcare Systems讀者反饋
書目名稱Big Data Analytics for Smart Transport and Healthcare Systems讀者反饋學科排名
作者: 考得 時間: 2025-3-21 23:21 作者: Glower 時間: 2025-3-22 00:25
Big Data for Social Media Analysis During the COVID-19 Pandemic: An Emotion Analysis ?Based on Influhe COVID-19?pandemic. The study also investigates the relationship between COVID-19?trends or topics and public sentiments?on social networks. Machine learning?is used to verify the correlation between emotion on social media and the COVID-19?pandemic trends. The study concludes with a prediction mo作者: jarring 時間: 2025-3-22 05:16 作者: WITH 時間: 2025-3-22 10:50
Robert Fantina,Andriy Storozhuk,Kamal Goyal, reaching an accuracy?of 99.89%. The preprocessing stage is proven to be vital for the performance of the LSTM?model. As a result, models using our preprocessed nine features are much more accurate on this freight transportation prediction task. Discussions are also raised to understand better frei作者: 藥物 時間: 2025-3-22 15:13
SEO Hub: Utilities and Toolsets,red with four classifiers, including Multilayer Perceptron, Decision Tree, Multinomial Logistics Regression, and LR one versus rest. According to the results, the Random Forest?model outperforms the benchmarks?regarding prediction accuracy. The findings of this chapter help optimise prediction accur作者: bonnet 時間: 2025-3-22 21:01
https://doi.org/10.1007/978-1-4842-1766-5he COVID-19?pandemic. The study also investigates the relationship between COVID-19?trends or topics and public sentiments?on social networks. Machine learning?is used to verify the correlation between emotion on social media and the COVID-19?pandemic trends. The study concludes with a prediction mo作者: 水汽 時間: 2025-3-22 22:09 作者: 加入 時間: 2025-3-23 02:57
Big Data-Enabled Time Series Analysis for Climate Change Analysis in Brazil : An Artificial Neural Nate data and analyze the changing climate trends in the same province. An artificial neural network is established as the model in this project to implement this objective. The performance shows that this model can complete this classification task.作者: 口訣 時間: 2025-3-23 07:11
Optimized Clustering Model for Healthcare Sentiments on Twitter: A Big Data Analysis Approache experiment results indicate that self-organized map model with the TF-IDF extraction method can achieve the best clustering accuracy. Moreover, the optimized model can have great potential to handle large-scale data in real practice.作者: PAN 時間: 2025-3-23 11:20 作者: 虛構(gòu)的東西 時間: 2025-3-23 17:24
Introducing the Google Tools Suite, to be more accurate by using feature relevance to assist people in making real-time transportation decisions to improve mobility and reduce accidents. The findings help improve urban transportation network?and systems at multiple spatial levels.作者: Bronchial-Tubes 時間: 2025-3-23 21:16 作者: harrow 時間: 2025-3-23 23:49
A Predictive Data Analysis for Traffic Accidents: Real-Time Data Use for Mobility Improvement and Ac to be more accurate by using feature relevance to assist people in making real-time transportation decisions to improve mobility and reduce accidents. The findings help improve urban transportation network?and systems at multiple spatial levels.作者: 幾何學家 時間: 2025-3-24 06:18
Healthcare Infrastructure Development and Pandemic Prevention: An Optimal Model for Healthcare Inveshts how big data could be used to improve the availability and development of urban critical infrastructures, such as healthcare infrastructure. An optimal model is suggested as part of the conclusion of this study.作者: PAC 時間: 2025-3-24 08:52 作者: Watemelon 時間: 2025-3-24 12:30
Robert Fantina,Andriy Storozhuk,Kamal Goyalynomial regression?models to predict the delay time of a flight. The data analysis algorithm?runs on a well-known dataset, which comprises flight data from more than ten US airlines?from 2009 to 2019. The result indicates that 97.04. of the predicted result has a difference of fewer than 15?min between the actual value.作者: Progesterone 時間: 2025-3-24 16:37
https://doi.org/10.1007/978-1-4302-2992-6ese transitions happening at a gradual pace. Thus, we believe these two sectors are leading the Big Data analytics research and practice, particularly in the context of smartness and smart city development. The chapter also summarises some of the key lessons from all case study chapters.作者: 疏忽 時間: 2025-3-24 21:45 作者: 昏迷狀態(tài) 時間: 2025-3-25 02:13 作者: infarct 時間: 2025-3-25 04:02 作者: Obituary 時間: 2025-3-25 07:35 作者: 想象 時間: 2025-3-25 14:11
https://doi.org/10.1007/978-1-4302-2992-6ate data and analyze the changing climate trends in the same province. An artificial neural network is established as the model in this project to implement this objective. The performance shows that this model can complete this classification task.作者: Costume 時間: 2025-3-25 17:28
WCF RIA Services and Silverlight for Mobilee experiment results indicate that self-organized map model with the TF-IDF extraction method can achieve the best clustering accuracy. Moreover, the optimized model can have great potential to handle large-scale data in real practice.作者: misanthrope 時間: 2025-3-25 20:00 作者: 干涉 時間: 2025-3-26 02:07
The Role of Big Data Analytics in Urban Systems: Review and Prospect for Smart Transport and Healthe current information age. The chapter starts with an overview of Big Data analytics for urban systems and follows the discussions from the sector-based perspectives.It then explores Big Data Applications (BDA) in two key areas of smart transportation and healthcare, particularly in cities and as pa作者: Geyser 時間: 2025-3-26 08:11
Big Data Analysis for?an?Optimised Classification for?Flight Status : Prediction Analysis Using Machtive impacts of such delays. Machine learning-enabled?Big data solutions have been widely utilized in recent studies to anticipate aircraft delays. They need a data pre-processing to understand and grasp the relevance of each data attribute. The results of data attribute relevance are used to filter作者: mercenary 時間: 2025-3-26 11:50
On-Board Unit Freight Transport Data Analysis and Prediction: Big Data Analysis for Data Pre-processontribute to society’s efficient production and development, particularly in optimising urban systems. This chapter aims to build a precise model to predict the number of freight vehicles?in future timestamps?based on historical data provided On-Board Unit (OBU)?datasets in Belgium’s?road networks. 作者: MORT 時間: 2025-3-26 14:36
Data-Driven Multi-target Prediction Analysis for Driving Pattern Recognition: A Machine Learning Appers, such as the car’s speed, traffic, weather, and road status. This article investigates the correlations between driving attributes and proposes a multi-target prediction model?to recognise driving patterns. For this, a pre-processing data approach, including Pearson’s Correlation Coefficient, Qu作者: Restenosis 時間: 2025-3-26 17:02 作者: ligature 時間: 2025-3-26 21:08 作者: 畢業(yè)典禮 時間: 2025-3-27 03:27
Big Data for Social Media Analysis During the COVID-19 Pandemic: An Emotion Analysis ?Based on Influyears, news and social media were covered with information, updates, and daily/regular reports on the COVID-19?pandemic. When face-to-face activities were restricted, people started to use social networks?more than before. The situation led to the empowerment?of digital media, such as social media a作者: 幻想 時間: 2025-3-27 06:26 作者: 細胞 時間: 2025-3-27 11:37
Optimized Clustering Model for Healthcare Sentiments on Twitter: A Big Data Analysis Approache social events, e-commerce products, healthcare, etc. This chapter proposes a best-fitted clustering method to classify sentiment samples related to healthcare topics. Thus, we examine other clustering models with keyword extraction methods on the real healthcare datasets collected from Twitter. Th作者: 壕溝 時間: 2025-3-27 16:56 作者: tinnitus 時間: 2025-3-27 21:35
Saeid Pourroostaei Ardakani,Ali CheshmehzangiCovers big data solutions in urban sustainability applications—mainly smart transportation and healthcare systems.Remains as the only book dealing with data analytic problems in urban sustainability a作者: Sinus-Rhythm 時間: 2025-3-28 01:32
Urban Sustainabilityhttp://image.papertrans.cn/b/image/185615.jpg作者: cornucopia 時間: 2025-3-28 05:55
Introducing Relational Political Analysise current information age. The chapter starts with an overview of Big Data analytics for urban systems and follows the discussions from the sector-based perspectives.It then explores Big Data Applications (BDA) in two key areas of smart transportation and healthcare, particularly in cities and as pa作者: 不愛防注射 時間: 2025-3-28 06:24
Robert Fantina,Andriy Storozhuk,Kamal Goyaltive impacts of such delays. Machine learning-enabled?Big data solutions have been widely utilized in recent studies to anticipate aircraft delays. They need a data pre-processing to understand and grasp the relevance of each data attribute. The results of data attribute relevance are used to filter作者: 高興一回 時間: 2025-3-28 13:50
Robert Fantina,Andriy Storozhuk,Kamal Goyalontribute to society’s efficient production and development, particularly in optimising urban systems. This chapter aims to build a precise model to predict the number of freight vehicles?in future timestamps?based on historical data provided On-Board Unit (OBU)?datasets in Belgium’s?road networks. 作者: affinity 時間: 2025-3-28 18:22 作者: Etymology 時間: 2025-3-28 21:33
Introducing the Google Tools Suite,avel and improve the road system’s safety, it is essential to identify the data patterns?in the dataset for extracting the main influencing features associated with traffic accidents. The analysis of traffic accidents?is complex as they affect each other and are also affected by many other factors. 作者: 指派 時間: 2025-3-28 23:09 作者: 使增至最大 時間: 2025-3-29 05:07 作者: ALT 時間: 2025-3-29 11:09
https://doi.org/10.1007/978-1-4302-2992-6 many industries, such as agriculture and shipping. In this project, we use the climate data in Brazil from 2000 to 2020. Attributes of the data mainly are date and time, temperature, precipitation, wind speed, and the province in which these data are measured. This study aims to classify these clim
