المؤلفون: Wu, Dan¹ (AUTHOR) wudan17214@outlook.com, Zhou, Ming^1,2 (AUTHOR), Li, Liang¹ (AUTHOR), Leng, Xiangfeng³ (AUTHOR), Zhang, Zheng¹ (AUTHOR), Wang, Ning¹ (AUTHOR), Sun, Yanwei¹ (AUTHOR)

المصدر: Burns (03054179). Mar2019, Vol. 45 Issue 2, p387-397. 11p.

مصطلحات موضوعية: *TIME series analysis, *GENE expression profiling

المؤلفون: Rui Wang, Yijing Li

المصدر: ISPRS International Journal of Geo-Information, Vol 13, Iss 1, p 18 (2024)

مصطلحات موضوعية: COVID-19, lockdown, crime pattern, spatiotemporal analysis, Bayesian structural time series (BSTS), regression, geo

العلاقة: https://doaj.org/article/4c68ae1258bf4451ab5b96dd0b3ce4e4Test

الإتاحة: https://doi.org/10.3390/ijgi13010018Test
https://doaj.org/article/4c68ae1258bf4451ab5b96dd0b3ce4e4Test

المؤلفون: Zihao Zhou, Yimin Chen, Zhensheng Wang, Feidong Lu

المصدر: International Journal of Applied Earth Observations and Geoinformation, Vol 127, Iss , Pp 103676- (2024)

مصطلحات موضوعية: Urban expansion simulation, Time-series urban extent maps, Cellular automata, LSTM, Shapley algorithm, demo, geo

العلاقة: https://doaj.org/article/b25d1c4d916644c2855f8eff91b95d22Test

الإتاحة: https://doi.org/10.1016/j.jag.2024.103676Test
https://doaj.org/article/b25d1c4d916644c2855f8eff91b95d22Test

المؤلفون: Maosheng Li, Chen Zhang

المصدر: Sustainability, Vol 16, Iss 2, p 607 (2024)

مصطلحات موضوعية: short-term section flow prediction, time series decomposition, countermeasure neural network, graph convolutional neural network, geo, archi

العلاقة: https://doaj.org/article/3724bc65bf874ad890313f8029870a26Test

الإتاحة: https://doi.org/10.3390/su16020607Test
https://doaj.org/article/3724bc65bf874ad890313f8029870a26Test

المؤلفون: Tianyue Xu, Fumin Wang, Zhou Shi, Yuxin Miao

المصدر: International Journal of Applied Earth Observations and Geoinformation, Vol 127, Iss , Pp 103655- (2024)

مصطلحات موضوعية: Time-series, Data fusion, Grey level co-occurrence matrix, Machine learning, Observation scale, Scaling, geo, envir

العلاقة: https://doaj.org/article/59f115b8f6e34398afdacee1d6f41794Test

الإتاحة: https://doi.org/10.1016/j.jag.2024.103655Test
https://doaj.org/article/59f115b8f6e34398afdacee1d6f41794Test

المؤلفون: Seokhyun Chin, Victoria Lloyd

المصدر: Frontiers in Environmental Science, Vol 12 (2024)

مصطلحات موضوعية: climate forecasting, climate prediction, machine learning, time series, recurrent neural network, model development, envir, geo

العلاقة: https://doaj.org/article/1b8a100899cb4a08a6c607f638f27fb7Test

الإتاحة: https://doi.org/10.3389/fenvs.2024.1301343Test
https://doaj.org/article/1b8a100899cb4a08a6c607f638f27fb7Test

المؤلفون: Wabi, Moudjahid Akorede, Vanhove, Wouter, Idohou, Rodrigue, Hounkpèvi, Achille, Kakaï, Romain Lucas Glèlè, Van Damme, Patrick

المصدر: ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY ; ISSN: 1387-585X ; ISSN: 1573-2975

مصطلحات موضوعية: Agriculture and Food Sciences, Climate change, Rainfall, Cropping seasons, Risk management, Agriculture, National adaptation plan (NAP), TIME-SERIES, TREND ANALYSIS, DETECT TREND, PRECIPITATION, VARIABILITY, AFRICA, EVENTS, TEMPERATURE, PERCEPTIONS, envir, geo

العلاقة: https://biblio.ugent.be/publication/01H8BXZM47722BK0VH5WQGNH4ZTest

الإتاحة: https://biblio.ugent.be/publication/01H8BXZM47722BK0VH5WQGNH4ZTest

المؤلفون: Yufeng Jiang, Jing Li, Zhen Zhang, Yi Li

المصدر: International Journal of Applied Earth Observations and Geoinformation, Vol 127, Iss , Pp 103654- (2024)

مصطلحات موضوعية: Aquaculture pond, Inundation frequency, Object oriented, Time Series, Landsat, envir, geo

العلاقة: https://doaj.org/article/31ca32e8b4794ce99d1efbbc0bfe99fbTest

الإتاحة: https://doi.org/10.1016/j.jag.2024.103654Test
https://doaj.org/article/31ca32e8b4794ce99d1efbbc0bfe99fbTest

المؤلفون: Ashutosh Tiwari, Manoochehr Shirzaei

المصدر: International Journal of Applied Earth Observations and Geoinformation, Vol 126, Iss , Pp 103611- (2024)

مصطلحات موضوعية: InSAR, Time series displacement, Spatio-temporal analysis, Semi-supervised clustering, geo, manag

العلاقة: https://doaj.org/article/9cb697337dd945bd82ff11f7e2fb99a6Test

الإتاحة: https://doi.org/10.1016/j.jag.2023.103611Test
https://doaj.org/article/9cb697337dd945bd82ff11f7e2fb99a6Test

المؤلفون: Eatidal Amin, Luca Pipia, Santiago Belda, Gregor Perich, Lukas Valentin Graf, Helge Aasen, Shari Van Wittenberghe, José Moreno, Jochem Verrelst

المصدر: International Journal of Applied Earth Observations and Geoinformation, Vol 126, Iss , Pp 103636- (2024)

مصطلحات موضوعية: Sentinel-2, Crop yield forecasting, Machine learning, Gaussian process regression (GPR), Time series gap-filling, Growing degree days (GDD), geo, envir

العلاقة: https://doaj.org/article/a8bb85440b7f41fb9a8aa795e47f6f54Test

الإتاحة: https://doi.org/10.1016/j.jag.2023.103636Test
https://doaj.org/article/a8bb85440b7f41fb9a8aa795e47f6f54Test