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Wind Power Prediction in View of Ramping Events Based on Classified Spatiotemporal Network

Bingbing Xia, Qiyue Huang, Hao Wang, Liheng Ying
2022 Frontiers in Energy Research  
This paper presents a wind power prediction model of ramping events based on classified spatiotemporal network.  ...  Combined with the probability weight, the spatiotemporal neural network considering numerical weather prediction data is used to realize power prediction.  ...  This paper presents a wind power prediction model of ramping events based on classified spatiotemporal network.  ... 
doi:10.3389/fenrg.2021.754274 fatcat:5yddfgds5fclnbvern4pwa5odi

Meta-Learning and Self-Supervised Pretraining for Real World Image Translation [article]

Ileana Rugina, Rumen Dangovski, Mark Veillette, Pooya Khorrami, Brian Cheung, Olga Simek, Marin Soljačić
2021 arXiv   pre-print
We follow this line of work and explore spatio-temporal structure in a recently introduced image-to-image translation problem in order to: i) formulate a novel multi-task few-shot image generation benchmark  ...  deep-learning to the semi-supervised and few-shot domains.  ...  ACKNOWLEDGEMENTS The authors acknowledge the MIT SuperCloud and Lincoln Laboratory Supercomputing Center (Reuther et al., 2018) for providing HPC and consultation resources that have contributed to the  ... 
arXiv:2112.11929v1 fatcat:2a3bjrxr7bfmnkea4cec5oaevm

CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting [article]

Chaoyun Zhang, Marco Fiore, Iain Murray, Paul Patras
2021 arXiv   pre-print
We apply our proposed architecture to two representative, practical use cases that involve point-cloud streams, i.e., mobile service traffic forecasting and air quality indicator forecasting.  ...  network models.  ...  Acknowledgments This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no.101017109 "DAEMON", and from the Cisco University Research  ... 
arXiv:1907.12410v3 fatcat:3wea4b2uvjbctnhmfw7v2obgjm

Multi-scale Bushfire Detection from Multi-modal Streams of Remote Sensing Data

Thanh Cong Phan, Thanh Tam Nguyen, Thanh Dat Hoang, Quoc Viet Hung Nguyen, Jun Jo
2020 IEEE Access  
In this paper, we propose a multi-scale deep neural network model that combines both satellite images and weather data for detecting and locating bushfires at both image and pixel level.  ...  adversarial effects.  ...  ACKNOWLEDGMENT This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 102.01-2019.323.  ... 
doi:10.1109/access.2020.3046649 fatcat:pcoyokt6xnaanpphah3vsy7vye

Graph Neural Networks in IoT: A Survey [article]

Guimin Dong, Mingyue Tang, Zhiyuan Wang, Jiechao Gao, Sikun Guo, Lihua Cai, Robert Gutierrez, Bradford Campbell, Laura E. Barnes, Mehdi Boukhechba
2022 arXiv   pre-print
., convolution neural networks and recurrent neural networks) have been extensively employed in solving IoT tasks by learning patterns from multi-modal sensory data.  ...  The Internet of Things (IoT) boom has revolutionized almost every corner of people's daily lives: healthcare, home, transportation, manufacturing, supply chain, and so on.  ...  For instance, CMA China [317] provides weather information to aid air quality prediction.  ... 
arXiv:2203.15935v2 fatcat:jkqg5ukg5fezbewu5mr5hqsp4e

Spatiotemporal Data Mining: A Survey on Challenges and Open Problems [article]

Ali Hamdi, Khaled Shaban, Abdelkarim Erradi, Amr Mohamed, Shakila Khan Rumi, Flora Salim
2021 arXiv   pre-print
Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay between space and time.  ...  We attempt to fill this gap by providing a comprehensive literature survey on state-of-the-art advances in STDM.  ...  [239, 339] proposed hybrid predictive models for air quality prediction combining different predictors, e.g., spatial, temporal, and inflection predictors.  ... 
arXiv:2103.17128v1 fatcat:ci5pt5bytndr5inolznjsaizpi

2021 Index IEEE Transactions on Intelligent Transportation Systems Vol. 22

2021 IEEE transactions on intelligent transportation systems (Print)  
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages.  ...  ., +, TITS Dec. 2021 7619-7630 Image quality Haze Removal of Railway Monitoring Images Using Multi-Scale Residual Network.  ... 
doi:10.1109/tits.2021.3139738 fatcat:p2mkawtrsbaepj4zk24xhyl2oa

2021 Index IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 14

2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages.  ...  ., +, JSTARS 2021 8730-8743 SA-JSTN: Self-Attention Joint Spatiotemporal Network for Temperature Forecasting.  ... 
doi:10.1109/jstars.2022.3143012 fatcat:dnetkulbyvdyne7zxlblmek2qy

A deep generative model for probabilistic energy forecasting in power systems: normalizing flows [article]

Jonathan Dumas and Antoine Wehenkel Damien Lanaspeze and Bertrand Cornélusse and Antonio Sutera
2021 arXiv   pre-print
The models producing weather-based wind, solar power, and load scenarios are properly compared in terms of forecast value by considering the case study of an energy retailer and quality using several complementary  ...  networks and variational autoencoders.  ...  Nevertheless, the comparison is only based on quality metrics, and the models do not take into account weather forecasts; 2.  ... 
arXiv:2106.09370v4 fatcat:iyl7tswwarecho7faa6pdnbjo4

SpectraGAN

Kai Xu, Rajkarn Singh, Marco Fiore, Mahesh K. Marina, Hakan Bilen, Muhammad Usama, Howard Benn, Cezary Ziemlicki
2021 Proceedings of the 17th International Conference on emerging Networking EXperiments and Technologies  
City-scale spatiotemporal mobile network traffic data can support numerous applications in and beyond networking.  ...  SpectraGAN is an original conditional GAN design with the defining feature of generating spectra of mobile traffic at all locations of the target region based on their contextual features.  ...  ACKNOWLEDGMENTS We thank the anonymous shepherd and reviewers for their helpful comments.  ... 
doi:10.1145/3485983.3494844 fatcat:o53wlbvlazanjhpfh3rws5cbsq

Urban Safety: An Image-Processing and Deep-Learning-Based Intelligent Traffic Management and Control System

Selim Reza, Hugo S. Oliveira, José J. M. Machado, João Manuel R. S. Tavares
2021 Sensors  
Our analysis found that deep-learning-based approaches for short-term traffic state forecast and multi-intersection signal control showed reasonable results, but lacked robustness for unusual scenarios  ...  Reliable implementations of ITMC improve the safety of inhabitants and the quality of life, leading to economic growth.  ...  and tested an Elman network, a partial RNN, and a TDNN Lacked robustness RMSE: around (8-20)% Bohan and Yun, 2019 [48] Applied a BRNN, LSTM, and GRU for prediction Less and low-quality data MAE of BRNN  ... 
doi:10.3390/s21227705 pmid:34833794 pmcid:PMC8623406 fatcat:d245ucplzbcwdfukxn2ndgnxii

Learning Neural Textual Representations for Citation Recommendation

Binh Thanh Kieu, Inigo Jauregi Unanue, Son Bao Pham, Hieu Xuan Phan, Massimo Piccardi
2021 2020 25th International Conference on Pattern Recognition (ICPR)  
Features and Multi-View Images DAY 2 -Jan 13, 2021 Simonsson, Simon; Dias Casagrande, Flávia; Zouganeli, Evi 2496 Location Prediction in Real Homes of Older Adults based on K- Means in Low-Resolution  ...  Deep Homography-Based Video Stabilization DAY 2 -Jan 13, 2021 Arsalan, Muhammad; Santra, Avik; Bierzynski, Kay; Issakov, Vadim 2442 Air-Writing with Sparse Network of Radars Using Spatio-Temporal  ... 
doi:10.1109/icpr48806.2021.9412725 fatcat:3vge2tpd2zf7jcv5btcixnaikm

A Survey of Traffic Prediction: from Spatio-Temporal Data to Intelligent Transportation

Haitao Yuan, Guoliang Li
2021 Data Science and Engineering  
Third, we focus on three kinds of traffic prediction problems (i.e., classification, generation and estimation/forecasting).  ...  Later, we review existing work on the four parts. First, we summarize traffic data into five types according to their difference on spatial and temporal dimensions.  ...  ., measuring surface temperature using weather balloons), while raster data correspond to traffic or meteorological data collected at fixed ST grids (e.g., air quality of Earth's surface collected by ground-based  ... 
doi:10.1007/s41019-020-00151-z fatcat:nnnnxnpo3bgk3l4hpr7kk2n4xa

Transfer Learning with Time Series Data: A Systematic Mapping Study

Manuel Weber, Maximilian Auch, Christoph Doblander, Peter Mandl, Hans-Arno Jacobsen
2021 IEEE Access  
This benefits learning in various time series domains, including a variety of domains based on sensor values.  ...  Following the review guidelines of Kitchenham and Charters, we identify and analyze 223 relevant publications. We describe the pursued approaches and point out trends.  ...  ACKNOWLEDGMENT This work was financially supported by the Munich University of Applied Sciences and the German Research Foundation (DFG) through the "Open Access Publishing" program.  ... 
doi:10.1109/access.2021.3134628 fatcat:66sxrp35bndjjeffxwy5jisa6q

2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57

2019 IEEE Transactions on Geoscience and Remote Sensing  
., and Drake, V.A., Insect Biological Parameter Estimation Based on the Invariant Target Parameters of the Scattering Matrix; TGRS Aug. 2019 6212-6225 Hu, C., see Zhang, M., TGRS Sept. 2019 6666-6674  ...  on Arbitrary Region of Interest; TGRS Oct. 2019 7995-8010 Hu, T., see Kang, Z., TGRS Jan. 2019 181-193 Hu, T., Wu, Y., Zheng, G., Zhang, D., Zhang, Y., and Li, Y., Tropical Cyclone Center  ...  ., +, TGRS Feb. 2019 815-828 Classification of Hyperspectral Images Based on Multiclass Spatial-Spectral Generative Adversarial Networks.  ... 
doi:10.1109/tgrs.2020.2967201 fatcat:kpfxoidv5bgcfo36zfsnxe4aj4
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