correlation distance
Recently Published Documents


TOTAL DOCUMENTS

61
(FIVE YEARS 12)

H-INDEX

9
(FIVE YEARS 2)

2021 ◽  
Vol 2090 (1) ◽  
pp. 012153
Author(s):  
Agron Gjana ◽  
Sander Kovaçi

Abstract In this work we have considered the study of the exchange rate series for the specific case where the formal financial market is not active. In those situations, we would be interested in the parallelization of the exchange rate with financial indexes for stabilized financial market. We observed that the stationarity of the distribution for some the exchange rate of currencies traded in the country differs significantly. The time dynamics shows the presence of the elements of local critical behavior, but those tendencies attenuate and fade away in an a periodic fashion. Next, we considered and evidenced the correlation distances and dissimilarity between exchange rates of national currencies versus euro and dollar and golden prices. It resulted that two exchange rates do have different distance from golden price taken for references. The correlation distance between the series of the return in different period has evidenced that there is not a regular behavior in this respect.


2021 ◽  
Vol 13 (15) ◽  
pp. 3017
Author(s):  
Xiang Zhang ◽  
Wenmin Lv ◽  
Lei Zhang ◽  
Jinhai Zhang ◽  
Yangting Lin ◽  
...  

Most previous studies tend to simplify the lunar regolith as a homogeneous medium. However, the lunar regolith is not completely homogeneous, because there are weak reflections from the lunar regolith layer. In this study, we examined the weak heterogeneity of the lunar regolith layer using a self-organization model by matching the reflection pattern of both the lunar regolith layer and the top of the ejecta layer. After a series of numerical experiments, synthetic results show great consistency with the observed Chang’E-4 lunar penetrating radar data and provide some constraints on the range of controlling parameters of the exponential self-organization model. The root mean square permittivity perturbation is estimated to be about 3% and the correlation distance is about 5–10 cm. Additionally, the upper layer of ejecta has about 1–2 rocks per square meter, and the rock diameter is about 20–30 cm. These parameters are helpful for further study of structural characteristics and the evolution process of the lunar regolith. The relatively small correlation distance and root mean square perturbation in the regolith indicate that the regolith is mature. The weak reflections within the regolith are more likely to be due to structural changes rather than material composition changes.


Author(s):  
Arben Pitarka ◽  
Robert Mellors

ABSTRACT In an ongoing effort to improve 3D seismic-wave propagation modeling for frequencies up to 10 Hz, we used cross correlations between vertical-component waveforms from an underground chemical explosion to estimate the statistical properties of small-scale velocity heterogeneities. The waveforms were recorded by a dense 2D seismic array deployed during the Source Physics Experiments for event number 5 (SPE-5) in a series of six underground chemical explosions, conducted at the Nevada National Security Site. The array consisted of 996 geophones with a 50–100 m grid spacing, deployed at the SPE site at the north end of the Yucca Flat basin. The SPE were conducted to investigate the generation and propagation of seismic and acoustic waves from underground explosions. Comparisons of decay rates of waveform cross correlations as function of interstation distance, computed for observed and synthetic seismograms from the SPE-5 chemical explosion, were used to constrain statistical properties of correlated stochastic velocity perturbations representing small-scale heterogeneities added to a geology-based velocity model of the Yucca Flat basin. Using comparisons between recorded and simulated waveform cross correlations, we were able to recover sets of statistical properties of small-scale velocity perturbations in the velocity model that produce the best-fit between the recorded and simulated ground motion. The stochastic velocity fluctuations in the velocity model that produced the smallest misfits have a horizontal correlation distance of between 400 and 800 m, a vertical correlation distance between 100 and 200 m, and a standard deviation of 10% from the nominal model velocity in the alluvium basin layers. They also have a horizontal correlation distance of 1000 m, a vertical correlation distance of 250 m, and a standard deviation of 6% in the underlying and consolidated sedimentary layers, up to a depth of 4 km. Comparisons between observed and simulated wavefields were used to assess the proposed small-scale heterogeneity enhancements to the Yucca Flat basin model. We found that adding a depth-resolved stochastic variability to the geology-based velocity model improves the overall performance of ground-motion simulations of an SPE-5 explosion in the modeled frequency range up to 10 Hz. The results may be applicable to other similar basins.


Author(s):  
Aidan Hughes ◽  
Sung Yun Jun ◽  
Camillo Gentile ◽  
Derek Caudill ◽  
Jack Chuang ◽  
...  

2020 ◽  
Vol 163 ◽  
pp. 107213
Author(s):  
Alzahra Badi ◽  
Sangwook Park ◽  
David K. Han ◽  
Hanseok Ko

Author(s):  
Hanfei Zhang ◽  
Yumei Jian ◽  
Ping Zhou

: A class correlation distance collaborative filtering recommendation algorithm is proposed to solve the problems of category judgment and distance metric in the traditional collaborative filtering recommendation algorithm, which is using the advantage of the distance between the same samples and the class related distance. First, the class correlation distance between the training samples is calculated and stored. Second, the K nearest neighbor samples are selected, the class correlation distance of training samples and the difference ratio between the test samples and training samples are calculated respectively. Finally, according to the difference ratio, we classify the different types of samples. The experimental result shows that the algorithm combined with user rating preference can get lower MAE value, and the recommendation effect is better. With the change of K value, CCDKNN algorithm is obviously better than KNN algorithm and DWKNN algorithm, and the accuracy performance is more stable. The algorithm improves the accuracy of similarity and predictability, which has better performance than the traditional algorithm.


Sign in / Sign up

Export Citation Format

Share Document