Recurrence Based Similarity Identification of Climate Data

Bai, Anita; Hira, Swati; Parag, S. Deshpande

doi:10.1155/2017/7836720

Cited by 8 publications

(5 citation statements)

References 28 publications

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“…A crucial advantage of RP techniques over other nonlinear methods is that they perform reasonably well even when the length of the nonlinear time series is very short (even 50-100 data points) and in cases when the underlying system is not sufficiently deterministic have proven useful in characterizing their behavior [21]. Therefore, the RP and RQA methods may be used in all types of signals including periodic, non-stationary, and chaotic [22].…”

Section: Nonlinear Time Series Methodsmentioning

confidence: 99%

Damage detection by recurrence and entropy methods on the basis of time series measured during composite milling

Kęcik

Ciecieląg

Zaleski

2020

Int J Adv Manuf Technol

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This paper presents methods for damage detection in machined material on the basis of time series measured during milling of glass-fiber–reinforced polymer (GFRP). Recurrence methods and different types of entropy have emerged as useful tools for detecting subtle non-stationarities and/or changes in nonlinear signals. In this research, a recurrence plot, recurrence quantifications, an approximate entropy, and sample entropy are used. By identifying changes in the cutting force measured during the composite milling process, the damage occurrence has been detected. Firstly, the damage has been modelled as the intentionally introduced hole with different diameters and depths in order to estimate the size detectable damages and to select proper recurrence measures as damage indicators. Next, the experiments with the real damage have been performed and the damage indicators have used.

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Section: Nonlinear Time Series Methodsmentioning

confidence: 99%

Damage detection by recurrence and entropy methods on the basis of time series measured during composite milling

Kęcik

Ciecieląg

Zaleski

2020

Int J Adv Manuf Technol

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“…To validate the effectiveness and reliability of our approach we are using recurrence quantification analysis (recurrence plot, cross recurrence plots) [5] and association rules methods [13]. The recurrence plot and cross recurrence plots are shown in Fig.…”

Section: Correctness Of Proposed Methodsmentioning

confidence: 99%

“…al. analyzed such periodic variations using recurrence plot (RP), cross recurrence plot (CRP), recurrence rate (RR), and correlation of probability of recurrence (CPR) methods to find similarities between and within united states climatic regions and to identify their connectivity trend [5]. Information and Communication technology (ICT) is the efficient way to increase the productivity of agriculture.…”

Section: Introductionmentioning

confidence: 99%

Estimating the difference of agriculture productivity in ASIAN regions

Hira¹,

Bai²

2018

IJET

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Agriculture is the major sector in the economy of Asia. The aim of this paper is to identify the importance of agriculture in Asia continent. In this paper, we evaluate differences between and within regions of Asia (Eastern-Asia, South-Central Asia, South-East Asia, and Western Asia and Middle Asia) and their countries. We used five agriculture parameters (Agriculture Land, Cereal production, Machinery, Tractors, Cereal yield, Land under cereal production) which widely represent agriculture productivity of Asia. The means of all Asian regions and its countries are identically similar is considered as a hypothesis for agriculture parameters. We use One-way ANOVA (analysis of variance) technique for analysis. Further, Asian regions and countries are estimated to test the differences of the means between and within regions and countries of each Asian region. The results show that each Asian region and their countries are having different agriculture productivity for agriculture parameters.

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“…More recently, recurrence analysis, that is, another advanced nonlinear dynamic analysis technique, has been increasingly applied to examine the chaotic time series, especially with regard to meteorological parameters (Bigdeli and Sadegh Lafmejani, 2016; Bai et al ., 2017; Adeniji et al ., 2018; Shu et al ., 2020a; 2020c). The main goal of this study is to shed some lights on the application of recurrence analysis in various meteorological time series (i.e., wind speed, pressure, temperature and relative humidity), with the emphasis on diagnosing and characterizing the hidden chaotic structures, and hence addressing problems in meteorological variability from a view of nonlinear dynamic system framework.…”

Section: Introductionmentioning

confidence: 99%

Dynamic analysis of meteorological time series in Hong Kong: A nonlinear perspective

Yan¹,

Chan

et al. 2021

Intl Journal of Climatology

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Many meteorological systems are chaotic in nature, which inevitably limits its predictability. Accurate prediction of meteorological variables depends primarily on properly diagnosing the complex underlying dynamics. Nonlinear dynamic analysis has shown to be particularly useful for such purpose. In this study, the concept of recurrence analysis was extended to investigate and characterize the underlying dynamics of meteorological time series (i.e., wind speed, temperature, pressure and relative humidity) based on daily observation in Hong Kong during a period from 1998 to 2018. The existence of chaos was clearly identified based on the phase space reconstruction diagram and the recurrence plot. It was shown that the underlying dynamics associated with wind speed appears to indicate higher level of complexity as compared to those of pressure and temperature, which, in consequence, may lead to more irregular time‐dependent behaviour and lower predictability. Moreover, season‐to‐seasonal variability in the dynamics of meteorological time series was evident, particularly for wind speed and temperature. Overall, this study shows that the recurrence analysis can be well applied as a useful diagnostic tool to investigate the dynamics of meteorological systems, which is expected to provide a new avenue regarding the modelling and prediction of the behaviour of meteorological parameters.

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Recurrence Based Similarity Identification of Climate Data

Cited by 8 publications

References 28 publications

Damage detection by recurrence and entropy methods on the basis of time series measured during composite milling

Damage detection by recurrence and entropy methods on the basis of time series measured during composite milling

Estimating the difference of agriculture productivity in ASIAN regions

Dynamic analysis of meteorological time series in Hong Kong: A nonlinear perspective

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