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H. Boukhedouma, A. Meziane, S. Hammoudi, A. Benna
2020 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The mass of data generated from people's mobility in smart cities is constantly increasing, thus making a new business for large companies.  ...  These data are often used for mobility prediction in order to improve services or even systems such as the development of location-based services, personalized recommendation systems, and mobile communication  ...  Challenge 6 -Confidentiality and privacy of users data Mobility prediction solutions are mainly based on the historical data of individuals' movements, on their profile data, on their social relationships  ... 
doi:10.5194/isprs-archives-xliv-4-w2-2020-17-2020 doaj:35a76dcb3cb8469187a4eef013f40911 fatcat:bpakgst3avdgdpktpvjhlmqvue

A Deep Belief Network Based Model for Urban Haze Prediction

2018 Tehnički Vjesnik  
In order to improve the accuracy of urban haze prediction, a novel deep belief network (DBN)-based model was proposed.  ...  Thirdly, the meteorological data predictions were carried out by using a competitive adaptive-reweighed method.  ...  Additionally, real-time collection and monitoring of data and analysis of trends in the historical data can be carried out on mobile phones, as manifested in Fig. 6 and Fig. 7 .  ... 
doi:10.17559/tv-20180204162632 fatcat:56fhjgtqrnh3dai5qmaur5wezm

Electric vehicle assistant based on driver profile

Joao C. Ferreira, Vítor Monteiro, Joao L. Afonso
2014 International journal of electric and hybrid vehicles  
It is also proposed a range prediction approach based on probability to take into account unpredictable effects of personal driving style, traffic or weather.  ...  This is an application for mobile devices that is able to passively track the driver behaviour and to access several information related with the EV in real time.  ...  Range Prediction -This application estimates the range of EV based on the current battery SoC level and its historical data.  ... 
doi:10.1504/ijehv.2014.067626 fatcat:htiswvar65co5awbsbmaaqjddq

Dengue fatality prediction using data mining

N.F. Rahim, S. M. Taib, A. I. Z. Abidin
2018 Journal of Fundamental and Applied Sciences  
The aim of this research is to study the current implementation of dengue outbreak control in Malaysia and predict dengue fever cases usi fever and weather are collected from the Ministry of Health in  ...  its Perak Tengah district office and Perak Meteorological office are applied onto these data with the performance of each technique is measured.  ...  Such elements are:  Vector control which based on the principles of integrated vector management  Active disease surveillance based on a comprehensive health information system DATA MINING IN HEALTHCARE  ... 
doi:10.4314/jfas.v9i6s.52 fatcat:zext2w73lnguxobqecd2jctwyq

Aircraft 4D Trajectory Prediction in Civil Aviation: A Review

Weili Zeng, Xiao Chu, Zhengfeng Xu, Yan Liu, Zhibin Quan
2022 Aerospace (Basel)  
This paper firstly summarizes the background and significance of the trajectory prediction problems and then introduces the definition and basic process of trajectory prediction, including four modules  ...  Aircraft four dimensional (4D, including longitude, latitude, altitude and time) trajectory prediction is a key technology for existing automation systems and the basis for future trajectory-based operations  ...  Data Availability Statement: This study did not report any data. Conflicts of Interest: The authors declare no conflict of interest. Aerospace 2022, 9, 91  ... 
doi:10.3390/aerospace9020091 fatcat:j6ny5gg365eibdg77y3ixga7ge

Social Parking: Applying the Citizens as Sensors Paradigm to Parking Guidance and Information

Julio Barbancho, Jorge Ropero, Joaquín Luque, Alejandro Caraballo, Carlos León
2019 Sustainability  
For this reason, this paper presents social parking, a system that is based on the citizens as sensors paradigm, where data are collected by users and are processed using data mining techniques.  ...  With this aim, we used public parking data from eight parking lots in the city of Zaragoza. Client applications allowed testing of all the functions of the parking system.  ...  The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.  ... 
doi:10.3390/su11236549 fatcat:ec554pos7jesxajzemutijplnu

Study and Application on Big Data Information Fusion System Based on IoT

Lina Zheng, Jian Su
2021 Security and Communication Networks  
Prediction model presented a high accuracy outcome with 99% accuracy in training data and 100% in testing set.  ...  Therefore, we can conclude that big data fusion technology on the basis of IoT has a good future in many fields excepting agriculture crop, which is also an irreversible trend.  ...  At the same time, big data can also provide market forecasts and facilitate decision-making based on historical data analysis.  ... 
doi:10.1155/2021/5486162 fatcat:646qmh6b5be6digaoydvgawsfe

Moving Objects Analytics: Survey on Future Location & Trajectory Prediction Methods [article]

Harris Georgiou, Sophia Karagiorgou, Yannis Kontoulis, Nikos Pelekis, Petros Petrou, David Scarlatti, Yannis Theodoridis
2018 arXiv   pre-print
Phrases: mobility data, moving object trajectories, trajectory prediction, future location prediction.  ...  to Big Data applications.  ...  The mining phase facilitates to predict future life trends based on patterns harvested from historical life patterns.  ... 
arXiv:1807.04639v1 fatcat:lvje57kod5eldaplkl53wbwgti

Comparative analysis of global and national systems for observing, monitoring and forecasting natural disasters and hazards with а view to reducing risk

Yaryna Tuzyak
2021 Technology Audit and Production Reserves  
various branches of science on the goal of mitigating or preventing negative effects.  ...  weather, climate and water are described.  ...  Historical meteorological and hydrological data are essential for assessing the sensitivity and vulnerability of communities to weather, climate and water hazards.  ... 
doi:10.15587/2706-5448.2021.245825 fatcat:yy5tysxej5eapd3iwdf5y3xjqm

Concept of Horticulture Ambient Intelligence System

A. Vasilenko, Department of Information Technologies, Faculty of Economics and Management, Czech University of Life Sciences Prague, Czech Republic, M. Ulman, Department of Information Technologies, Faculty of Economics and Management, Czech University of Life Sciences Prague, Czech Republic
2015 Agris on-line Papers in Economics and Informatics  
Abstract In the context of climate changes, there are predictions about the lack of rainfall and water to satisfy the needs of population and farmers.  ...  There is scope for the application of intelligent systems for the sustainable management of water resources.  ...  Acknowledgements The results and knowledge included herein have been obtained owing to support from the Internal grant agency of the Faculty of Economics and Management, Czech University of Life  ... 
doi:10.7160/aol.2015.070420 fatcat:jydai4ldfvc5jof35rooutyw24


Yuecheng Rong, Zhimian Xu, Ruibo Yan, Xu Ma
2018 Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining - KDD '18  
of datasets we observed in the city, such as meteorology, events, map mobility trace data and navigation data from Baidu map, and POIs.  ...  In this paper, we estimate the realtime parking availability throughout a city using historical parking availability data reported by a limited number of existing sensors of parking lots and a variety  ...  ACKNOWLEDGMENT We would like to thank Zhang Chuanming and Yu Yongjian for their valuable suggestion that has helped to improve the quality of the manuscript.  ... 
doi:10.1145/3219819.3219876 dblp:conf/kdd/RongXYM18 fatcat:aoetbsb7xfb7xdd2uctkygvvki

The Simpler The Better

Yongxin Tong, Yuqiang Chen, Zimu Zhou, Lei Chen, Jie Wang, Qiang Yang, Jieping Ye, Weifeng Lv
2017 Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '17  
The simpler the better: A unified approach to predicting original taxi demands on large-scale online platforms. (2017).  ...  We envision our experiences to adopt simple linear models with high-dimensional features in UOTD prediction as a pilot study and can shed insights upon other industrial large-scale spatio-temporal prediction  ...  ACKNOWLEDGMENT We are grateful to anonymous reviewers for their constructive comments on this work. Yongxin Tong is supported in part by  ... 
doi:10.1145/3097983.3098018 dblp:conf/kdd/TongCZCWYYL17 fatcat:7vmt7jczqfdnndraqmarw4w7uq

On how to incorporate public sources of situational context in descriptive and predictive models of traffic data

Sofia Cerqueira, Elisabete Arsenio, Rui Henriques
2021 European Transport Research Review  
Methodology We propose a methodology anchored in data science methods to integrate situational context in the descriptive and predictive models of traffic data, with a focus on the three following major  ...  Results The gathered results stress the importance of incorporating historical and prospective context data for a guided description and prediction of urban mobility dynamics, irrespective of the underlying  ...  Acknowledgements The authors thank the support of CARRIS, METRO and Câmara Municipal de Lisboa) (particularly, Gabinete de Mobilidade and Centro de Operações Integrado) for the data provision and valuable  ... 
doi:10.1186/s12544-021-00519-w fatcat:u3y4vk33orbsjeualot2kqawjm

A Destination Prediction Network Based on Spatiotemporal Data for Bike-Sharing

Jian Jiang, Fei Lin, Jin Fan, Hang Lv, Jia Wu
2019 Complexity  
First, the data is preprocessed and a pool of likely candidate destinations is generated based on frequent item mining.  ...  In the final step, DPNst dynamically aggregates the output of the three neural networks based on the given data and generates the predictions.  ...  Acknowledgments This work is partially supported by grants from the National Natural Science Foundation of China (No. 61602141) and Science and Technology Program of Zhejiang Province (No. 2018C04001).  ... 
doi:10.1155/2019/7643905 fatcat:4g6sljmb2jemrl3lfdcmdnuosi

Deep Learning for Spatio-Temporal Data Mining: A Survey [article]

Senzhang Wang, Jiannong Cao, Philip S. Yu
2019 arXiv   pre-print
Next we classify existing literatures based on the types of ST data, the data mining tasks, and the deep learning models, followed by the applications of deep learning for STDM in different domains including  ...  In this paper, we provide a comprehensive survey on recent progress in applying deep learning techniques for STDM.  ...  Predictive Learning The basic objective of predictive learning is to predict the future observations of the ST data based on its historical data.  ... 
arXiv:1906.04928v2 fatcat:4zrdtgkvirfuniq3rb2gl7ohpy
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