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Вид документа : Статья из журнала
Шифр издания :
Автор(ы) : Molokeev M. S., Kostyukov A. S., Ershov A. E., Maksimov D. N., Gerasimov V. S., Polyutov S. P.
Заглавие : Infrared bound states in the continuum: random forest method
Колич.характеристики :4 с
Место публикации : Opt. Lett. - 2023. - Vol. 48, Is. 17. - P.4460-4463. - ISSN 01469592 (ISSN), DOI 10.1364/OL.494629. - ISSN 15394794 (eISSN)
Примечания : Cited References: 42. - Ministry of Science and Higher Education of the Russian Federation (FSRZ-2023-0006)
Аннотация: In this Letter, we consider optical bound states in the continuum (BICs) in the infrared range supported by an all-dielectric metasurface in the form of subwavelength dielectric grating. We apply the random forest machine learning method to predict the frequency of the BICs as dependent on the optical and geometric parameters of the metasurface. It is found that the machine learning approach outperforms the standard least square method at the size of the dataset of ≈4000 specimens. It is shown that the random forest approach can be applied for predicting the subband in the infrared spectrum into which the BIC falls. The important feature parameters that affect the BIC wavelength are identified.
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Вид документа : Статья из журнала
Шифр издания :
Автор(ы) : Reushev M. Y., Podoprigora V. G., Makarov D. S., Kharlamov D. V., Vasiliev E. V.
Заглавие : Interaction of satellite navigation signals with forest and snow-ice layers
Колич.характеристики :6 с
Место публикации : Russ. Phys. J. - 2023. - Vol. 66, Is. 6. - P.706-711. - ISSN 10648887 (ISSN), DOI 10.1007/s11182-023-02996-z. - ISSN 15739228 (eISSN)
Примечания : Cited References: 8
Аннотация: The paper studies parameters of the snow-ice cover and forest ground determined by the integrated approach based on the global navigation satellite system reflectometry. Experimental data on the amplitude and time response of satellite navigation signals are processed by fast Fourier transform and then analyzed using mathematical methods based on the multipath echoes model in terms of geometrical optics. Using a combination of reflectometry and numerical simulation of the surface layers based on local weather data, it is possible to evaluate not only the current state of these layers, but also predict their dynamic development.
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Вид документа : Статья из журнала
Шифр издания :
Автор(ы) : Karavaisky A. Yu., Lukin Y. I.
Заглавие : Dielectric model of the upper organic layer of forest soils for a frequency of 435 MHz
Колич.характеристики :12 с
Место публикации : Izv. Atmos. Ocean. Phys. - 2023. - Vol. 59, Is. 9. - P.1208-1219. - ISSN 00014338 (ISSN), DOI 10.1134/S0001433823090104. - ISSN 1555628X (eISSN)
Примечания : Cited References: 57. - We are grateful to Cand. Sci. (Phys.–Math.) K.V. Muzalevskii, Head of the Laboratory of Remote Sensing Radiophysics, for supporting this work, as well as to I.V. Savin for selecting the studied soil samplesThe study was performed within the framework of the state assignment of the Ministry of Science and Higher Education of Russia, project no. 0287-2021-0034
Аннотация: A dielectric model based on the refractive dielectric model of the mixture of thawed and frozen forest organic soils in the root zone for a frequency of 435 MHz has been developed. The model is created on the basis of dielectric measurements of four soils whose organic matter content varies in the range from 15 to 31%. The dielectric measurements are carried out in the range of the gravimetric moisture from 0 to 0.6 g/g and temperature range from –30 to 25°C. The coefficient of determination (R2) between values calculated by themodel and measured values of the real (ε') and imaginary (ε'') parts of complex dielectric permittivity is 0.97. The normalized root-mean-square error is 16 and 21% for the real and imaginary parts of the complex dielectric permittivity, respectively. This dielectric model may be applied in remote sensing algorithms when retrieving the value of forest soil moisture in the root zone from radar and radiometric data.
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Вид документа : Статья из журнала
Шифр издания :
Автор(ы) : Molokeev M. S., Su, Binbin, Aleksandrovsky A. S., Golovnev, Nicolay N., Plyaskin M. E., Xia, Zhiguo
Заглавие : Machine learning analysis and discovery of zero-dimensional ns2 metal halides toward enhanced photoluminescence quantum yield
Место публикации : Chem. Mat. - 2022. - Vol. 34, Is. 2. - P.537-546. - ISSN 0897-4756, DOI 10.1021/acs.chemmater.1c02725. - ISSN 1520-5002(eISSN)
Примечания : Cited References: 66. - This work is supported by the National Natural Science Foundation of China (51961145101 and 51972118), International Cooperation Project of National Key Research and Development Program of China (2021YFE0105700), Guangzhou Science and Technology Project (202007020005), and the Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program (2017BT01X137). This work is also funded by RFBR according to the research project no. 19-52-80003
Предметные рубрики: RANDOM FOREST
CRYSTAL-STRUCTURE
TIN BROMIDE
CLASSIFICATION
Аннотация: The dependence of photoluminescence quantum yield (PLQY) on the crystal structure of existing zero-dimensional ns2 metal halides is analyzed with the help of principal component analysis and random forest methods. The primary role of the distance between metal ions in different compounds is revealed, and the influence of other structural features such as metal-halogen distance and the distortion of metal-halogen polyhedrons are quantified. Accordingly, the two previously unknown Sb3+-based zero-dimensional metal halides were synthesized to verify the obtained model. Experimental studies of the two compounds demonstrated good agreement with the predictions, and the PLQY of (C10H16N)2SbCl5 is found to be 96.5%. Via machine learning analysis, we demonstrate that concentration quenching is the main factor that determines PLQY for all s2 ion metal halides, which will accelerate the discovery of new luminescence metal halides.
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Вид документа : Статья из журнала
Шифр издания :
Автор(ы) : Endzhievskaya I. G., Endzhievskiy A. S., Galkin M. A., Molokeev M. S.
Заглавие : Machine learning methods in assessing the effect of mixture composition on the physical and mechanical characteristics of road concrete
Колич.характеристики :18 с
Место публикации : J. Build. Eng. - 2023. - Vol. 76. - Ст.107248. - ISSN 23527102 (eISSN), DOI 10.1016/j.jobe.2023.107248
Примечания : Cited References: 17. - The work was carried out within the framework of the Strategic Academic Leadership Program "Priority-2030" for the Siberian Federal University. The research in field of Machine Learning application was supported by the Tyumen Oblast Government, as part of the West-Siberian Interregional Science and Education Center’s project No. 89-DON (3)
Аннотация: Current manuscript presents a study on the use of 48 experimental data points containing parameters of concrete production technological process and its properties, such as strength, density, and bending strength. It was revealed that temporal characteristics, specifically - compressive strength at the age of 3, 7, 28 days, R3, R7, and R28, are significantly correlated with each other, indicating that only one characteristic, such as R28 or Rfl 28, is sufficient for prediction. The absence of multiple correlations between parameters and properties suggests that linear regression analysis may not be accurate. Therefore, the use of Machine Learning is optimal; specifically Random Forest method is preferable due to ease of use and minimum hyperparameters for tuning. Low prediction errors (?1–11%) for 30% of the test data, as determined by the cross-validation method, confirm a relationship between the experimental parameters and the concrete properties. The most important parameters for achieving high values of compressive and bending strengths, R28 and Rfl 28, were identified, namely: air-entraining additives, granite crushed stone consisting of a mixture of fractions 5–20 mm, crushed stone derived from gravel of high strength grains of large fractions 10–20 mm. To obtain explanatory model, another Machine Learning method, that was used, called Decision Tree. The model showed that a high amount of crushed stone 10–20 mm from gravel, more than 212 (kg per 1 m3 of concrete mix), leads to a higher number of strong grains with smooth, rounded surface, thereby, reducing the bending strength of concrete. However, a large concentration of crushed stone mix fractions of 5–20 mm from granite, more than 537 (kg per 1 m3 of concrete mix), leads to the maximum roughness, which makes a significant contribution to the increased strength of concrete due to the adhesion of the matrix and aggregates to each other.
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Вид документа : Статья из сборника (однотомник)
Шифр издания :
Автор(ы) : Mironov V. L., Bobrov P. P., Bobrov A. P., Mandrygina V. N., Stasuk V. D.
Заглавие : Microwave Dielectric Spectroscopy of Moist Soils for a Forest-tundra Region
Коллективы : IEEE International Geoscience and Remote Sensing Symposium
Место публикации : IEEE International Geoscience and Remote Sensing Symposium (IGRASS): Proceedings. - Seoul, 2005. - Vol. 6. - Ст.1525917. - P.4485-4488. - ISBN 978-078039050-8, DOI 10.1109/igarss.2005.1525917
Примечания : Библиогр.: 8
Аннотация: In this paper, the measured microwave dielectric data are presented for some soils collected in the forest-tundra area located at 64° N and 100° E, which is near the city of Tura in East Siberia. The measurements were developed in the range from 0.3 to 12.5 GHz at the temperature of 24°C. The Debye spectroscopic parameters related to the bound soil water (BSW) and free soil water (FSW) were derived with the use of the generalized refractive mixing dielectric model (GRMDM) [1], [2]. The foresttundra soils analyzed were found to contain the smaller percentage of bound water, with its complex dielectric constant (CDC) being less than that of the soils in the agricultural zones of Siberia [3]-[5], in spite of the fact that the forest-tundra soils demonstrated smaller clay and humus percentage as compared to the agricultural soils. The results obtained can be considered as a substantial contribution to the soil dielectric data base for the northern circumpolar region, which is a compulsory element of physically based both the remote sensing models and retrieving algorithms.
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Вид документа : Статья из журнала
Шифр издания :
Автор(ы) : Sorokin A. V., Podoprigora V. G., Makarov D. S., Kharlamov D. V., Baltice V. V.
Заглавие : Orientational ordering of tree elements in the dielectric permittivity model of a forest stand
Место публикации : Russ. Phys. J. - 2020. - Vol. 63, Is. 2. - P.238-243. - ISSN 1064-8887, DOI 10.1007/s11182-020-02026-2. - ISSN 1573-9228(eISSN)
Примечания : Cited References: 8
Аннотация: The dielectric characteristics of trees are studied for a dielectric permittivity model of a forest stand of L1 band signals of navigation satellites. The contribution of the orientational ordering of tree elements and of the wood anisotropy to the effective wood dielectric permittivity epsilon has been estimated. The crown layer has the height-depend anisotropy increment epsilon and the orientational ordering of branch tensor elements. The anisotropy gradients in the layer of trunks are determined by the height-dependent wood volume of a single tree and the tree height distribution in a large forest.
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Вид документа : Статья из сборника (однотомник)
Шифр издания :
Автор(ы) : Podoprigora V. G., Sorokin A. V.
Заглавие : Forest vegetation interaction with L-band satellite signals
Коллективы : Региональные проблемы дистанционного зондирования Земли, международная конференция, Conference on regional problems of earth remote sensing, Сибирский федеральный университет
Место публикации : E3S Web of Conferences. - 2019. - Vol. 75. - Ст.01007. - ISBN 2267-1242, DOI 10.1051/e3sconf/20197501007
Примечания : Cited References: 9
Аннотация: A method for calculating the electro-physical parameters of forest vegetation cover interacting with the signals of navigation satellites in the frequency bands 1.2-1.6 GHz is proposed. A technique for the experimental measurement of linear attenuation coefficient of satellite signals on test areas of canopies was developed, taking into account their calibration at the input. The proposed forest vegetation model describes the group of crowns as a system of quasi spherical "capsules", located chaotically in the air matrix. The scattering and penetration cross sections and the coefficient of linear attenuation of radio waves were calculated using the approximation of anomalous diffraction for crowns and the results of solving the diffraction problem for trunks. The effects of multiple scattering were taken into account.
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Вид документа : Статья из сборника (однотомник)
Шифр издания :
Автор(ы) : Bobrov P.P., Kondratieva O.V., Mironov V.L., Shvetsov E., Sukhinin A.I., Yashchenko A.S.
Заглавие : Results of the SMOS Data Validation over a Steppe and Forest Area in Siberia
Коллективы : Progress In Electromagnetics Research Symposium
Место публикации : Proc. PIER. - 2011. - С. 55-58
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10.

Вид документа : Статья из сборника (однотомник)
Шифр издания :
Автор(ы) : Sorokin A. V., Podoprigora V. G., Ponomarev E. I.
Заглавие : Forest dielectric characteristics for navigation satellites signals in L1 range
Коллективы : Региональные проблемы дистанционного зондирования Земли, международная конференция, Conference on regional problems of earth remote sensing, Сибирский федеральный университет
Место публикации : E3S Web of Conferences. - 2019. - Vol. 75. - Ст.01011. - ISBN 2267-1242, DOI 10.1051/e3sconf/20197501011
Примечания : Cited References: 9
Аннотация: A structural dielectric model of the forest is presented taking into account the wood Biomass distribution. The multi-scale structural formations of the individual trees and the stand as a whole as a hierarchical system of non-interacting components of the mixed dielectric are discussed. Layers of crowns and trunks are distinguished as anisotropic dielectric media with gradient boundaries. The possibility of using the orientation parameter of the order of branches in the crown layer to estimate the gradients of the effective permittivity of the inhomogeneous distribution and its spatial anisotropy is analyzed. A comparative analysis of the features of the effective dielectric permittivity of pine and birch forests is carried out. The possibilities of using a layered anisotropic dielectric forest model to describe the transformation of GPS and GLONASS signals in order to restore the biometric characteristics of the forest are considered.
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