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epidemic of DHF would occur in October 2015 by the seventh interpretation rule with the forecasted number of DHF (257 cases) and root-mean-squared error (RMSE = 46.71), as illustrated in Fig.  1 . The forecasted number of DHF cases from January 2014 to

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Thermal diesel-like analysis

Quality control by thermal and chemometric analysis

Journal of Thermal Analysis and Calorimetry
Authors:
Alexandre G. S. Prado
,
Rômulo D. A. Andrade
,
Jez W. B. Braga
, and
Paulo A. Z. Suarez

development. The choice of the best iPLSR model was done by comparing the prediction performance of these local models with the global model built with the full thermogram. The comparison is mainly based on the root mean squared error of cross validation

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compared for better results. The best prediction result can be derived from this analysis. The comparison can be made with the help of errors obtained in each model, namely Mean Square Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Percentage

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, & Pakpour, 2017 ), such as the BSMAS. A series of fit indices were used: comparative fit index (CFI) and Tucker–Lewis index (TLI) > 0.9; root mean square error of approximation (RMSEA) and standardized root mean square residual (SRMR) < 0.08; non

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Journal of Behavioral Addictions
Authors:
Elisabeth Franc
,
Yasser Khazaal
,
Katarzyna Jasiowka
,
Thibault Lepers
,
Francesco Bianchi-Demicheli
, and
Stéphane Rothen

.95 ( Bentler, 1990 ); and (e) root mean square error of approximation (RMSEA) <0.06 ( Hu & Bentler, 1999 ). The use and cutoff of the AGFI was recommended by Cole ( 1987 ), of the NFI by Bentler and Bonnet ( 1980 ), and of the RMSEA, TLI, and CFI by Hu and

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presented developed with the Markov-chain approach using the same dataset. Finally, the two approaches are being compared based on the root mean square error and the Speed-Acceleration Probability Distribution (SAPD), which precisely reflects the dynamic

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Abstract  

Using 1.0 MeV protons on thick targets of zeolite pellets, aluminium and silicon were determined by PIXE. Results were compared with XRF data. The relative root mean square error was 3.7% and the results of the two methods agreed with a correlation factor of 0.991. PIXE analysis can be carried out on very small samples, while sample preparation involves minimal handling.

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Nowadays, GPS is the best positioning system with its constellation, but number of GLONASS satellites increased to the required number, with launched new ones, for positioning. With recent revitalization of GLONASS, a great number of high precision GLONASS and GPS/GLONASS receivers have been produced. In this paper, baselines of two networks have been analyzed in order to assess the usability of GLONASS on global positioning. In both networks, repeatabilities of results were investigated by using GPS, GLONASS and GPS/GLONASS data. Results revealed that repeatabilities of all baselines by using GLONASS observations are not consistent when compared to the GPS and GPS/GLONASS.

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Fourier transform near infrared spectroscopy (FT-NIR) has been developed for determining the fat and protein contents of hard, semi-hard and processed cheeses. Multivariate calibration models were carried out by partial least squares (PLS) regression. The diffuse reflection spectra of different type of lyophilized cheeses were measured by FT-NIR analyser in the 800–2500 nm spectral range. The calibration set of 62 samples were validated by leave-oneout cross-validation and by prediction set of 31 samples. The optimal result for fat content (root mean square error of cross-validation (RMSECV)=1.0; R2=99.1%, PLS factor= 6) was obtained when the spectra were preprocessed by first derivation (FD) combined with multiplicative scatter correction (MSC) and smoothing. The optimal result for protein content (RMSECV=1.4, R2=97.2%, PLS factor=6) was observed when the first derivation combined with straight line subtraction (SLS) and smoothing spectral preprocessing method was applied.

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Single run heat capacity measurements

II. Experiments at subambient temperature

Journal of Thermal Analysis and Calorimetry
Authors:
Y. Jin
and
B. Wunderlich

A prior study of single-run differential scanning calorimetry that leads directly to heat capacity results is extended to low temperatures (180 K). The instrument considered was the duPont dual sample differential scanning calorimeter with auto sampler and liquid nitrogen cooling accessary-II. The major error is caused by the low temperature isotherm. After optimizing all parameters, heat capacities of selenium, aluminum, quartz, polystyrene, sodium chloride were measured between 180 to 370 K. The root mean square error of all measurements on comparison with well established adiabatic calorimetry is ±2.9%.

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