scholarly journals Tendency of Runoff and Sediment Variety and Multiple Time Scale Wavelet Analysis in Hongze Lake during 1975–2015

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 999 ◽  
Author(s):  
Yu Duan ◽  
Guobin Xu ◽  
Yuan Liu ◽  
Yijun Liu ◽  
Shixiong Zhao ◽  
...  
Keyword(s):  
Time Series ◽  
Time Scale ◽  
Change Point ◽  
Test Method ◽  
Practical Significance ◽  
Multiple Time ◽  
Hongze Lake ◽  
Runoff Variation ◽  
The Huaihe River ◽  
Short Time

Hongze Lake plays a key role in flood and waterlogging prevention, analyzing the variation process and characteristics of multi-time scales will have a great practical significance to water resources management and regulation in the Huaihe River basin of China. This research proposed a combinatorial mutation test method to study the interannual variation trends and change points of runoff and sediment flowing into and out of Hongze Lake during the period 1975–2015. It is concluded that the annual variation trend of the inflow and outflow runoff time series is consistent, with no obvious decreasing trend and change point, while the inflow and outflow sediment time series showed a decreasing trend, and the change point was 1991. Then, the runoff and sediment time series were analyzed by the wavelet method. The results showed that the time series has multi-time scale characteristics. The annual inflow runoff and sediment would enter into the dry period in a short time after 2015, and both would be in the valley floor stage. Among the influencing factors, the variation of rainfall in the basin was the main factor affecting the runoff variation. Changes in heavy rainfalls pattern, the construction of hydraulic engineering projects, and land use/cover change (LUCC) are the main reasons for the significant decrease and mutation variation of inflow sediment.

V351 Ori as a Target for the Wet

2003 ◽  
Vol 12 (1) ◽  
Author(s):  
V. Ripepi ◽  
M. Marconi ◽  
R. Silvotti
Keyword(s):  
Time Series ◽  
Time Scale ◽  
Short Time Scale ◽  
Short Time

AbstractWe present time series observations of the Herbig Ae star V351 Ori. This star presents light variations on short time scale (a few hours), typical of the δ Scuti pulsation. The new data are briefly described and the possibility to observe V351 Ori with the WET is discussed.

scholarly journals Block Hankel Tensor ARIMA for Multiple Short Time Series Forecasting

2020 ◽  
Vol 34 (04) ◽  
pp. 5758-5766 ◽  
Author(s):  
Qiquan Shi ◽  
Jiaming Yin ◽  
Jiajun Cai ◽  
Andrzej Cichocki ◽  
Tatsuya Yokota ◽  
...  
Keyword(s):  
Time Series ◽  
Moving Average ◽  
Computational Cost ◽  
Time Series Forecasting ◽  
Low Rank ◽  
Multiple Time ◽  
Tucker Decomposition ◽  
Unified Framework ◽  
Short Time Series ◽  
Short Time

This work proposes a novel approach for multiple time series forecasting. At first, multi-way delay embedding transform (MDT) is employed to represent time series as low-rank block Hankel tensors (BHT). Then, the higher-order tensors are projected to compressed core tensors by applying Tucker decomposition. At the same time, the generalized tensor Autoregressive Integrated Moving Average (ARIMA) is explicitly used on consecutive core tensors to predict future samples. In this manner, the proposed approach tactically incorporates the unique advantages of MDT tensorization (to exploit mutual correlations) and tensor ARIMA coupled with low-rank Tucker decomposition into a unified framework. This framework exploits the low-rank structure of block Hankel tensors in the embedded space and captures the intrinsic correlations among multiple TS, which thus can improve the forecasting results, especially for multiple short time series. Experiments conducted on three public datasets and two industrial datasets verify that the proposed BHT-ARIMA effectively improves forecasting accuracy and reduces computational cost compared with the state-of-the-art methods.

scholarly journals A Research on Change Point and Trend Scrutiny: with Reference to Castor in India

2019 ◽  
Vol 9 (1S5) ◽  
pp. 240-244
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Statistical Methods ◽  
Time Scale ◽  
Change Point ◽  
Maximum Growth ◽  
Edible Oil ◽  
Standard Normal ◽  
Leading Position ◽  
Slope Estimator

Castor is treated as an important non-edible oil crop among Mahua, Karanja and Jatropha. India occupies a leading position in the production of castor followed by China and Brazil. Castor has been used in various purposes from thousands of years ago which has important characteristics. The main objectives of current work are i) Identification of change point and ii) Trend analysis with respect to area, yield and production of castor for the period from 1961 to 2016 in India. The non-parametric statistical methods such as Pettitt's, Standard Normal Homogeneity (SNH) and Buishand’s Range tests have conceded to detect the mutation point whereas the magnitude of trend is measured and analysed with the help of Sen’s slope estimator and their significance is tested by MannKendall test. The results revealed that the change is identified by mutation point at initially 1988. Interestingly the maximum growth is captured in the second sub-time series on the basis of time scale and area, yield and production. However, the production of castor cannot meet up its annual enormous demand for India.

scholarly journals Deciphering Dynamical Nonlinearities in Short Time Series Using Recurrent Neural Networks

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Radhakrishnan Nagarajan
Keyword(s):  
Time Series ◽  
Statistical Hypothesis ◽  
Multiple Time ◽  
Correlated Noise ◽  
Statistical Hypothesis Testing ◽  
Short Time Series ◽  
Classification Framework ◽  
Experimental Time Series ◽  
Short Time ◽  
The Given

Abstract Surrogate testing techniques have been used widely to investigate the presence of dynamical nonlinearities, an essential ingredient of deterministic chaotic processes. Traditional surrogate testing subscribes to statistical hypothesis testing and investigates potential differences in discriminant statistics between the given empirical sample and its surrogate counterparts. The choice and estimation of the discriminant statistics can be challenging across short time series. Also, conclusion based on a single empirical sample is an inherent limitation. The present study proposes a recurrent neural network classification framework that uses the raw time series obviating the need for discriminant statistic while accommodating multiple time series realizations for enhanced generalizability of the findings. The results are demonstrated on short time series with lengths (L = 32, 64, 128) from continuous and discrete dynamical systems in chaotic regimes, nonlinear transform of linearly correlated noise and experimental data. Accuracy of the classifier is shown to be markedly higher than ≫50% for the processes in chaotic regimes whereas those of nonlinearly correlated noise were around ~50% similar to that of random guess from a one-sample binomial test. These results are promising and elucidate the usefulness of the proposed framework in identifying potential dynamical nonlinearities from short experimental time series.

Robust Test Method of TSOP PEMs for Space Application

2019 ◽  
Author(s):  
Yasunobu Iwai ◽  
Koichi Shinozaki ◽  
Daiki Tanaka
Keyword(s):  
Evaluation Method ◽  
Low Cost ◽  
Reliability Evaluation ◽  
Test Method ◽  
Thermal Shock Test ◽  
Space Application ◽  
Space Applications ◽  
Limit Test ◽  
Long Time ◽  
Short Time

Abstract Compared with space parts, consumer parts are highly functional, low cost, compact and lightweight. Therefore, their increased usage in space applications is expected. Prior testing and evaluation on space applicability are necessary because consumer parts do not have quality guarantees for space application [1]. However, in the conventional reliability evaluation method, the test takes a long time, and the problem is that the robustness of the target sample can’t be evaluated in a short time. In this report, we apply to the latest TSOP PEM (Thin Small Outline Package Plastic Encapsulated Microcircuit) an evaluation method that combines preconditioning and HALT (Highly Accelerated Limit Test), which is a test method that causes failures in a short time under very severe environmental conditions. We show that this method can evaluate the robustness of TSOP PEMs including solder connections in a short time. In addition, the validity of this evaluation method for TSOP PEM is shown by comparing with the evaluation results of thermal shock test and life test, which are conventional reliability evaluation methods.

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