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Wyszukujesz frazę "size distribution function" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Evaluation of soil texture determination using soil fraction data resulting from laser diffraction method
Autorzy:
Mako, A.
Szabo, B.
Rajkai, K.
Szabo, J.
Bakacsi, Z.
Labancz, V.
Hernadi, H.
Barna, G.
Powiązania:
https://bibliotekanauki.pl/articles/2082643.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Instytut Agrofizyki PAN
Tematy:
laser diffraction
particle-size distribution
pedotransfer function
soil texture triangle
Opis:
There are global aspirations to harmonize soil particle- size distribution data measured by the laser diffraction method and by traditional sedimentation techniques, e.g. sieve-pipette methods. The need has arisen therefore to build up a database, containing particle-size distribution values measured by the sieving and pipette method according to the Hungarian standard (sieve-pipette methods-MSZ) and the laser diffraction method according to a widespread and widely used procedure. In our current publication, 155 soil samples measured with sieve-pipette methods-MSZ and laser diffraction method (Malvern Mastersizer 2000, HydroG dispersion unit) were compared. Through the application of the usual size limits at the laser diffraction method, the clay fraction was under- and the silt fraction was overestimated compared to the sieve-pipette methods-MSZ results, and subsequently the soil texture classes were determined according to the results of both methods also differed significantly from each other. Based on our previous experience, the extension of the upper size limit of the clay fraction from 2 to 7 μm increases the comparability of sievepipette methods-MSZ and laser diffraction method, in this way the texture classes derived from the particle-size distributions were also more in accordance with each other. The difference between the results of the two kinds of particle-size distribution measurement methods could be further reduced with the pedotransfer functions presented.
Źródło:
International Agrophysics; 2019, 33, 4; 445-454
0236-8722
Pojawia się w:
International Agrophysics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Prediction of CEC using fractal parameters by artificial neural networks
Autorzy:
Bayat, H.
Davatgar, N.
Jalali, M.
Powiązania:
https://bibliotekanauki.pl/articles/25675.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Instytut Agrofizyki PAN
Tematy:
cation exchange capacity
prediction
fractal structure
fractal theory
particle size distribution
artificial neural network
pedotransfer function
Opis:
The prediction of cation exchange capacity from readily available soil properties remains a challenge. In this study, firstly, we extended the entire particle size distribution curve from limited soil texture data and, at the second step, calculated the fractal parameters from the particle size distribution curve. Three pedotransfer functions were developed based on soil properties, parameters of particle size distribution curve model and fractal parameters of particle size distribution curve fractal model using the artificial neural networks technique. 1 662 soil samples were collected and separated into eight groups. Particle size distribution curve model parameters were estimated from limited soil texture data by the Skaggs method and fractal parameters were calculated by Bird model. Using particle size distribution curve model parameters and fractal parameters in the pedotransfer functions resulted in improvements of cation exchange capacity predictions. The pedotransfer functions that used fractal parameters as predictors performed better than the those which used particle size distribution curve model parameters. This can be related to the non-linear relationship between cation exchange capacity and fractal parameters. Partitioning the soil samples significantly increased the accuracy and reliability of the pedotransfer functions. Substantial improvement was achieved by utilising fractal parameters in the clusters.
Źródło:
International Agrophysics; 2014, 28, 2
0236-8722
Pojawia się w:
International Agrophysics
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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