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Hatef Dastour and Quazi K. Hassan
Having a complete hydrological time series is crucial for water-resources management and modeling. However, this can pose a challenge in data-scarce environments where data gaps are widespread. In such situations, recurring data gaps can lead to unfavora...
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Zheren Liu, Chaogui Kang and Xiaoyue Xing
Similar time series search is one of the most important time series mining tasks in our daily life. As recent advances in sensor technologies accumulate abundant multi-dimensional time series data associated with multivariate quantities, it becomes a pri...
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Angel E. Muñoz-Zavala, Jorge E. Macías-Díaz, Daniel Alba-Cuéllar and José A. Guerrero-Díaz-de-León
This paper reviews the application of artificial neural network (ANN) models to time series prediction tasks. We begin by briefly introducing some basic concepts and terms related to time series analysis, and by outlining some of the most popular ANN arc...
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Lexin Zhang, Ruihan Wang, Zhuoyuan Li, Jiaxun Li, Yichen Ge, Shiyun Wa, Sirui Huang and Chunli Lv
This research introduces a novel high-accuracy time-series forecasting method, namely the Time Neural Network (TNN), which is based on a kernel filter and time attention mechanism. Taking into account the complex characteristics of time-series data, such...
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Anastasios Kaltsounis, Evangelos Spiliotis and Vassilios Assimakopoulos
We present a machine learning approach for applying (multiple) temporal aggregation in time series forecasting settings. The method utilizes a classification model that can be used to either select the most appropriate temporal aggregation level for prod...
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Yufei Wang, Honghai Zhang, Zongbei Shi, Jinlun Zhou and Wenquan Liu
General aviation accidents have complex interactions and influences within them that cannot be simply explained and predicted by linear models. This study is based on chaos theory and uses general aviation accident data to conduct research on different t...
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Abdul Razaque, Marzhan Abenova, Munif Alotaibi, Bandar Alotaibi, Hamoud Alshammari, Salim Hariri and Aziz Alotaibi
Time series data are significant, and are derived from temporal data, which involve real numbers representing values collected regularly over time. Time series have a great impact on many types of data. However, time series have anomalies. We introduce a...
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Eoin Cartwright, Martin Crane and Heather J. Ruskin
As the availability of big data-sets becomes more widespread so the importance of motif (or repeated pattern) identification and analysis increases. To date, the majority of motif identification algorithms that permit flexibility of sub-sequence length d...
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Qasem Abu Al-Haija
The determination of electric energy consumption is remarked as one of the most vital objectives for electrical engineers as it is highly essential in determining the actual energy demand made on the existing electricity supply. Therefore, it is importan...
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Pablo Felipe Andrés Unda, Paz Andrea Crisóstomo
Pág. 95 - 105
Los 80 (2008?2014), una de las series de ficción chilenas más destacadas en términos de críticas y resultados de audiencia, motiva un análisis narrativo enfocado en el primer capítulo de esta producción, para profundizar en el estudio dramático de series...
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Irina Belyaeva,Nikalay Chekanov,Natalia Chekanova,Igor Kirichenko,Oleg Ptashny,Tetyana Yarkho
Pág. 43 - 52
The Green?s function is widely used in solving boundary value problems for differential equations, to which many mathematical and physical problems are reduced. In particular, solutions of partial differential equations by the Fourier method are reduced ...
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Aytaç PEKMEZCI, Nevin Güler DINÇER, Öznur ISÇI GÜNERI
Pág. 307 - 320
Fuzzy Time Series (FTS) methods are used frequently in time series analysis due to their advantages such as having no assumptions, having few observations, being able to process incomplete, uncertain and linguistic data. The FTS consists of 6 steps, each...
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Yi Wang, Fei Lin, Zhongping Yang and Zhiyuan Liu
In this study, in order to determine the reasonable accuracy of the compensation capacitances satisfying the requirements on the output characteristics for a wireless power transfer (WPT) system, taking the series-series (SS) compensation structure as an...
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David Keast and Joanna Ellison
Flood frequency analysis using partial series data has been shown to provide better estimates of small to medium magnitude flood events than the annual series, but the annual series is more often employed due to its simplicity. Where partial series avera...
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Isabel Tamara Pedron
Pág. 205 - 208
Temperaturas podem ser correlacionadas por funções tipo leis de potência, e o termo de persistência pode ser caracterizado por uma função de autocorrelação C (t) de variações de temperatura, e t é o tempo entre as observações. Esta função decai como C(t)...
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Zhanling Li, Yuehua Wang, Wei Zhao, Zongxue Xu and Zhanjie Li
Statistical modeling of hydrological extremes is significant to the construction of hydraulic engineering. This paper, taking the Yingluoxia watershed as the study area, compares the annual maximum (AM) series and the peaks over a threshold (POT) series ...
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Zhanling Li, Yuehua Wang, Wei Zhao, Zongxue Xu, Zhanjie Li
Pág. 1 - 15
Statistical modeling of hydrological extremes is significant to the construction of hydraulic engineering. This paper, taking the Yingluoxia watershed as the study area, compares the annual maximum (AM) series and the peaks over a threshold (POT) series ...
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Natalí Carbo-Bustinza, Hasnain Iftikhar, Marisol Belmonte, Rita Jaqueline Cabello-Torres, Alex Rubén Huamán De La Cruz and Javier Linkolk López-Gonzales
In the modern era, air pollution is one of the most harmful environmental issues on the local, regional, and global stages. Its negative impacts go far beyond ecosystems and the economy, harming human health and environmental sustainability. Given these ...
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Kuiyong Song, Nianbin Wang and Hongbin Wang
High-dimensional time series classification is a serious problem. A similarity measure based on distance is one of the methods for time series classification. This paper proposes a metric learning-based univariate time series classification method (ML-UT...
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Knut Lehre Seip, Øyvind Grøn and Hui Wang
We show that oceanic cycle lengths persist across oceanic cyclic time-series by comparing cycles in series that come from ?sister? measurements in the North Atlantic Ocean. These are the North Atlantic oscillation (NAO), the Atlantic multidecadal oscilla...
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