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EN
Humic and fulvic acids are important materials for the health of the soil. This is related to the capability of humic and fulvic acids as chelating agent for pollutant in soil. The relationship between humic and fulvic acids with that of the soil properties is an important aspect to determine the characteristics of soil. Furthermore, production of humic and fulvic acids is a time-consuming process with several stages. Regarding this problem, the selection of sample size to study humic and fulvic acids is important. The relationship between the soil properties was analysed using the Partial Least Square (PLS) analysis, which is regarded as a solution to solve the analysis of complicated problems by offering a powerful approach. This study aimed to analyse the relationship between humic and fulvic acids, in terms of their mineral and physicochemical properties using the PLS method. The study was carried out in West Java, Indonesia. The results showed that the relationship between the chemical, physical, mineral contents with humic and fulvic acids, affected the negative and positive aspects of the relationship. Humic acids had a weak to good model category (0.269–0.940) with regards to the soil properties, and fulvic acids had a moderate model category (0.495–0.603) against all soil properties. Thus, the PLS method can solve a problem in study relationship between the soil properties with small sample and can help in understanding the soil characteristics in general.
2
Content available remote Wirtualna kalibracja spektrometru do diagnostyki procesów spalania biomasy
PL
W artykule przedstawiono nieliniową metodę regresji w zastosowaniu do kalibracji. Ze względu na brak metody wytworzenia odpowiednich danych pomiarowych zastosowano modelowanie matematyczne. Składają się na nie: model cech spektralnych gazów oraz model spektralnych urządzenia pomiarowego. Jako procedurę regresji wybrano nieliniową regresję cząstkową opartą o radialne funkcje bazowe.
EN
These article is shown nonlinear regression method for calibration. There is no practical method to obtain suitable measurements data so the mathematical modeling method is used instead. Modeling consist of spectral gas feature model and measurement instrument spectral model. As a regression procedure nonlinear radial basis function partial least square RBF-PLS method is used.
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