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Weiwen Zhou, Elise Miller-Hooks and Sagar Sahasrabudhe
Increasing popularity in gig employment has enabled the use of an at-will workforce of self-contracted couriers to participate in many service industries serving urban areas. This gig workforce has come to play a particularly important role in the growin...
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Anik Baul, Gobinda Chandra Sarker, Prokash Sikder, Utpal Mozumder and Ahmed Abdelgawad
Short-term load forecasting (STLF) plays a crucial role in the planning, management, and stability of a country?s power system operation. In this study, we have developed a novel approach that can simultaneously predict the load demand of different regio...
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Zhenzhen Li, Zhongyue Yan and Li Tang
Comprehending the changing patterns of flood magnitudes globally, particularly in the context of nonstationary conditions, is crucial for effective flood risk management. This study introduces a unique approach that employs simulated discharge data to un...
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Sen Wang, Jintai Gong, Haoyu Gao, Wenjie Liu and Zhongkai Feng
In the hydrology field, hydrological forecasting is regarded as one of the most challenging engineering tasks, as runoff has significant spatial?temporal variability under the influences of multiple physical factors from both climate events and human act...
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Xiaoyue Yang, Yi Yang, Shenghua Xu, Jiakuan Han, Zhengyuan Chai and Gang Yang
Geographically weighted regression (GWR) is a classical method for estimating nonstationary relationships. Notwithstanding the great potential of the model for processing geographic data, its large-scale application still faces the challenge of high comp...
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Chongxun Mo, Zhiwei Yan, Rongyong Ma, Xingbi Lei, Yun Deng, Shufeng Lai, Keke Huang and Xixi Mo
As the runoff series exhibit nonlinear and nonstationary characteristics, capturing the embedded periodicity and regularity in the runoff series using a single model is challenging. To account for these runoff characteristics and enhance the forecasting ...
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Lan Luo, Yanjun Zhang, Wenxun Dong, Jinglin Zhang and Liping Zhang
Water quality prediction is an important part of water pollution prevention and control. Using a long short-term memory (LSTM) neural network to predict water quality can solve the problem that comprehensive water quality models are too complex and diffi...
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Gang Tang, Jingyu Zhang, Jinman Lei, Haohao Du, Hongxia Luo, Yide Wang and Yuehua Ding
The accurate prediction of significant wave height (SWH) offers major safety improvements for coastal and ocean engineering applications. However, the significant wave height phenomenon is nonlinear and nonstationary, which makes any prediction work a no...
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Jian Liu, Yanyan Li, Yuankun Wang and Pengcheng Xu
The nonstationary characteristics caused by significant variation in hydrometeorological series in the context of climate change inevitably have a certain impact on the selection of an optimal gauging network. This study proposes an entropy-based, multi-...
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Quan Li, Hang Zeng, Pei Liu, Zhengzui Li, Weihou Yu and Hui Zhou
Recently, the homogenous flood generating mechanism assumption has become questionable due to changes in the underlying surface. In addition, flood is a multifaced natural phenomenon and should be characterized by both peak discharge and flood volume, es...
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