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Marius-Ionu? Gordan, Cosmin Alin Popescu, Jenica Calina, Tabita Cornelia Adamov, Camelia Maria Manescu and Tiberiu Iancu
Seasonal variations in the tourism industry consist of alternating patterns of overuse and underuse of touristic potential and resources, which correspond to overexertion in the peak periods and to reduced income levels in the trough periods. We analyze ...
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Hexiang Zheng, Hongfei Hou, Ruiping Li and Changfu Tong
To accurately forecast the future development trend of vegetation in dry areas, it is crucial to continuously monitor phenology, vegetation health indices, and vegetation drought indices over an extended period. This is because drought caused by high tem...
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Sihan Song, Qiujing Zhou, Tao Zhang and Yintao Hu
Concrete dam deformation prediction is important for assessing the safety of dams. A TPE-STL-LSTM deformation prediction model for concrete dams is established by introducing the TPE algorithm based on the decomposition?prediction model. Taking the Wanji...
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Xiaomei Fan, Tong Min and Xiaojie Dai
Shallow groundwater in coastal aquifers is a highly dynamic and complex system with a high risk of seawater intrusion. Analyzing the spatio-temporal dynamic patterns of groundwater can help to manage the groundwater resource and prevent it from degradati...
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M. Niranjannaik, Amit Kumar, Zafar Beg, Abhilash Singh, Somil Swarnkar and Kumar Gaurav
The Betwa River basin, a semi-arid catchment that has been classified as a major hotspot of groundwater depletion in Central India. The rainfall and streamflow intermittency have affected agricultural practices due to the variability of groundwater avail...
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Mengjie Yang, Zhe Chen, Mengjie Zhou, Xiaojin Liang and Ziyue Bai
The coronavirus disease 2019 (COVID-19) pandemic has had tremendous and extensive impacts on the people?s daily activities. In Chicago, the numbers of crime fell considerably. This work aims to investigate the impacts that COVID-19 has had on the spatial...
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Erhui Li, Xingmin Mu, Guangju Zhao and Peng Gao
Multifractal detrended fluctuation analysis (MFDFA) can provide information about inner regularity, randomness and long-range correlation of time series, promoting the knowledge of their evolution regularity. The MFDFA are applied to detect long-range co...
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