气候变化领域集成服务门户(CCPortal): A long Short-Term memory cyclic model with mutual information for hydrology forecasting: A Case study in the xixian basin

CCPortal

DOI	10.1016/j.advwatres.2020.103622
	A long Short-Term memory cyclic model with mutual information for hydrology forecasting: A Case study in the xixian basin
	Lv N.; Liang X.; Chen C.; Zhou Y.; Li J.; Wei H.; Wang H.
发表日期	2020
ISSN	0309-1708
卷号	141
英文摘要	Floods result in substantial damage throughout the world every year. An accurate predictions of floods can significantly alleviate the loss of lives and properties. However, due to the complexity during flood formation, the accuracy of traditional flood forecasting models suffer from the performance degradation with the increasing of required prediction period. According to the mutual information(MI) analysis to practical hydrologic data of Xixian Basin from year 2011–2018 in China, this paper proposes a long-term cyclic hydrology prediction model with the help of an improved Long Short-Term Memory. Firstly, by flitering, classifying and MI analysis the original data, the hydrological features, e.g., rainfall, reservoir water-level and flow are extracted as the time series features of the long short-term memory cyclic(LSTMC) forecasting model. Next, the structure of the LSTMC model is trained and determined by modeling the rainfall process to reflect the long-term change of flood flow. Finally, the actual flood data is used to verify the output of our model. Compared with some traditional and machine-learning flood forecasting schemes, it can be demonstrated that our model can accurately complete the task of long and short lead time hydrology forecasting. © 2020
关键词	Brain Flood control Floods Long short-term memory Rain Reservoirs (water)Time series analysis Water levels Accurate prediction Flood forecasting models Forecasting modeling Hydrology prediction Mutual informations Performance degradation Reservoir water level Time series features Weather forecasting artificial neural network flood forecasting hydrological modeling information rainfall time series analysis China Henan Xixian
语种	英语
来源机构	Advances in Water Resources
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/131785
推荐引用方式 GB/T 7714	Lv N.,Liang X.,Chen C.,et al. A long Short-Term memory cyclic model with mutual information for hydrology forecasting: A Case study in the xixian basin[J]. Advances in Water Resources,2020,141.
APA	Lv N..,Liang X..,Chen C..,Zhou Y..,Li J..,...&Wang H..(2020).A long Short-Term memory cyclic model with mutual information for hydrology forecasting: A Case study in the xixian basin.,141.
MLA	Lv N.,et al."A long Short-Term memory cyclic model with mutual information for hydrology forecasting: A Case study in the xixian basin".141(2020).