Journal of Geo-information Science ›› 2020, Vol. 22 ›› Issue (8): 1617-1629.doi: 10.12082/dqxxkx.2020.190378
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LIU Xin(), ZHAO Ning, GUO Jinyun*(
), GUO Bin
Received:
2019-07-16
Revised:
2019-10-01
Online:
2020-08-25
Published:
2020-10-25
Contact:
GUO Jinyun
E-mail:xinliu1969@126.com;jinyunguo1@126.com
Supported by:
LIU Xin, ZHAO Ning, GUO Jinyun, GUO Bin. Prediction of Monthly Precipitation over the Tibetan Plateau based on LSTM Neural Network[J].Journal of Geo-information Science, 2020, 22(8): 1617-1629.DOI:10.12082/dqxxkx.2020.190378
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[1] |
Immerzeel W W, Beek L P H V, Bierkens M F P. Climate change will affect the asian water towers[J]. Science, 2010,328(5984):1382-1385.
doi: 10.1126/science.1183188 pmid: 20538947 |
[2] | Song C, Sheng Y. Contrasting evolution patterns between glacier-fed and non-glacier-fed lakes in the Tanggula Mountains and climate cause analysis[J]. Climatic Change, 2016,135(3-4):1-15. |
[3] | 冯松, 汤懋苍, 王冬梅. 青藏高原是我国气候变化启动区的新证据[J]. 科学通报, 1998,43(6):633-636. |
[ Feng S, Tang M C, Wang D M. The Qinghai-Tibet Plateau is a new evidence for the climate change start-up zone in China[J]. Chinese Science Bulletin, 1998,43(6):633-636. ] | |
[4] | 潘保田, 李吉均. 青藏高原:全球气候变化的驱动机与放大器-Ⅲ.青藏高原隆起对气候变化的影响[J]. 兰州大学学报, 1996,32(1):108-115. |
[ Pan B J, Li J J. Qinghai-Tibetan Plateau: A driver and amplifier of the global climatic change[J]. Journal of LanZhou University, 1996,32(1):108-115. ] | |
[5] | Yao T, Thompson L, Yang W, et al. Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings[J]. Nature Climate Change, 2012,2(9):663-667. |
[6] | Ke L, Ding X, Li W, et al. Remote sensing of glacier change in the central Qinghai-Tibet Plateau and the relationship with changing climate[J]. Remote Sensing, 2017,9(2):114-130. |
[7] | Nayagam L R, Janardanan R, Mohan H S R. An empirical model for the seasonal prediction of southwest monsoon rainfall over Kerala, a meteorological subdivision of India[J]. International Journal of Climatology, 2010,28(6):823-831. |
[8] | 赵莹. 葠窝水库降雨量灰色预测模型应用分析[J]. 中国水能及电气化, 2016,141(12):68-70. |
[ Zhao Y. Analysis on application of rainfall grey prediction model for Shenwo reservoir[J]. China Water Power & Electrification, 2016,141(12):68-70. ] | |
[9] | 潘刚, 芦冰, 邹兵, 等. 马尔可夫链在水库主汛期降雨状态预测中的应用[J]. 水利科技与经济, 2011,17(6):33-36. |
[ Pan G, Lu B, Zou B, et al. Markov chain state in the reservoir the main flood season rainfall forecast[J]. Water Conservancy Science & Technology & Economy, 2011,17(6):33-36. ] | |
[10] | Feng C Y. Application of singular spectrum analysis to summer precipitation prediction[J]. Meteorological Monthly, 2002,28(11):22-25. |
[11] | Burlando P, Rosso R, Cadavid L G, et al. Forecasting of short-term rainfall using ARMA models[J]. Journal of Hydrology, 1993,144(1-4):193-211. |
[12] | Liu C, Tian Y, Wang X H. Study of rainfall prediction model based on GM (1, 1) - Markov chain[C]. Xi'an: 2011 International Symposium on Water Resource and Environmental Protection, 2011,18(1):744-747. |
[13] | 宋帆, 杨晓华, 武翡翡, 等. 基于聚类分析的模糊马尔科夫链在降雨量预测中的应用[J]. 节水灌溉, 2018,278(10):38-41,46. |
[ Song F, Yang X H, Wu F F, et al. Rainfall prediction using clustering-fuzzy-markov chain model[J]. Water Saving Irrigation, 2018,278(10):38-41,46. ] | |
[14] | Luk K C, Ball J E, Sharma A. An application of artificial neural networks for rainfall forecasting[J]. Mathematical & Computer Modelling, 2001,33(6):683-693. |
[15] | Nanda T, Sahoo B, Beria H, et al. A wavelet-based non-linear autoregressive with exogenous inputs (WNARX) dynamic neural network model for real-time flood forecasting using satellite-based rainfall products[J]. Journal of Hydrology, 2016,539(87):57-73. |
[16] | Chattopadhyay S, Chattopadhyay G. Comparative study among different neural net learning algorithms applied to rainfall time series[J]. Meteorological Applications, 2010,15(2):273-280. |
[17] | Nasseri M, Asghari K, Abedini M J. Optimized scenario for rainfall forecasting using genetic algorithm coupled with artificial neural network[J]. Expert Systems with Applications, 2008,35(3):1415-1421. |
[18] | Baratta D, Masulli F, Cicioni G, et al. Application of an ensemble technique based on singular spectrum analysis to daily rainfall forecasting[J]. Neural Networks, 2003,16(3):375-387. |
[19] | Wu C L, Chau K W. Prediction of rainfall time series using modular soft computingmethods[J]. Engineering Applications of Artificial Intelligence, 2013,26(3):997-1007. |
[20] | Yaseen Z M, Ghareb M I, Ebtehaj I, et al. Rainfall pattern forecasting using novel hybrid intelligent model based ANFIS-FFA[J]. Water Resources Management, 2017,8(32):105-122. |
[21] | Chau K W, Wu C L. A hybrid model coupled with singular spectrum analysis for daily rainfall prediction[J]. Journal of Hydroinformatics, 2010,12(4):458-473. |
[22] |
Hochreiter S, Schmidhuber J. Long short-term memory[J]. Neural Computation, 1997,9(8):1735-1780.
doi: 10.1162/neco.1997.9.8.1735 pmid: 9377276 |
[23] | Graves A . Supervised sequence labelling with recurrent neural networks[J]. Studies in Computational Intelligence, 2012,2(385):42-45. |
[24] |
Graves A, Schmidhuber J. Framewise phoneme classification with bidirectional LSTM and other neural network architectures[J]. Neural Networks, 2005,18(5-6):602-610.
doi: 10.1016/j.neunet.2005.06.042 pmid: 16112549 |
[25] | Duchi J, Hazan E, Singer Y. Adaptive subgradient methods for online learning and stochastic optimization[J]. Journal of Machine Learning Research, 2011,12(7):257-269. |
[26] | Kingma D P, Ba J. Adam: A method for stochastic optimization[C]. 3rd International Conference for Learning Representations, 2015,78(1):116-130. |
[27] | Vautard R. Singular-spectrum analysis: A toolkit for short, noisy chaotic signals[J]. Physica D: Nonlinear Phenom. 1992,9(58):95-126. |
[28] | Golyandina N, Korobeynikov A. Basic singular spectrum analysis and forecasting with R[J]. Computational Statistics & Data Analysis, 2014,71(12):934-954. |
[29] | Box G E, Jenkins G M. Time series analysis: Forecasting and control rev.ed.[J]. Journal of Time, 1976,31(4):238-242. |
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