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Saeed Samadianfard, Salar Jarhan, Ely Salwana, Amir Mosavi, Shahaboddin Shamshirband and Shatirah Akib
Advancement in river flow prediction systems can greatly empower the operational river management to make better decisions, practices, and policies. Machine learning methods recently have shown promising results in building accurate models for river flow...
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Tao Tang, Shuhan Guo, Lu Tan, Tao Li, Ryan M. Burrows and Qinghua Cai
Although most lotic ecosystems are groundwater dependent, our knowledge on the relatively long-term ecological effects of groundwater discharge on downstream reaches remains limited. We surveyed four connected reaches of a Chinese karst stream network fo...
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Yanan Wu, Yalin Yang and May Yuan
Conventional spatiotemporal methods take frequentist or density-based approaches to map event clusters over time. While these methods discern hotspots of varying continuity in space and time, their findings overlook locations of routine occurrences where...
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Mukhtar Zhassuzak, Marat Akhmet, Yedilkhan Amirgaliyev and Zholdas Buribayev
Unpredictable strings are sequences of data with complex and erratic behavior, which makes them an object of interest in various scientific fields. Unpredictable strings related to chaos theory was investigated using a genetic algorithm. This paper prese...
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Hye-In Ho, Chae-Hong Park, Kyeong-Eun Yoo, Nan-Young Kim and Soon-Jin Hwang
Eutrophic freshwater ecosystems are vulnerable to toxin-producing cyanobacteria growth or harmful algal blooms. Cyanobacteria belonging to the Nostocales order form akinetes that are similar to the seeds of vascular plants, which are resting cells surrou...
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Alan F. Smeaton and Feiyan Hu
Periodic phenomena are oscillating signals found in many naturally occurring time series. A periodogram can be used to measure the intensities of oscillations at different frequencies over an entire time series, but sometimes, we are interested in measur...
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Xiuhua Si, Junshi Wang, Haibo Dong and Jinxiang Xi
This study presents a data-driven approach to identifying anomaly-sensitive parameters through a multiscale, multifaceted analysis of simulated respiratory flows. The anomalies under consideration include a pharyngeal model with three levels of constrict...
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Yuefei Sun, Xianbo Sun, Tao Hu and Li Zhu
Despite the widespread use of artificial intelligence-based methods in detecting electricity theft by smart grid customers, current methods suffer from two main flaws: a limited amount of data on electricity theft customers compared to that on normal cus...
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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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Zhihong Chang, Chunsheng Liu and Jianmin Jia
As an important component of intelligent transportation-management systems, accurate traffic-parameter prediction can help traffic-management departments to conduct effective traffic management. Due to the nonlinearity, complexity, and dynamism of highwa...
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