Kinetic model and parameters optimization for Tangkou bituminous coal by the bi-Gaussian function and Shuffled Complex Evolution

Energy ◽  
2021 ◽  
pp. 123012
Author(s):  
Juan Zhang ◽  
Lulu Sun ◽  
Yu Zhong ◽  
Yanming Ding ◽  
Wenzhou Du ◽  
...  
Keyword(s):  
Kinetic Model ◽  
Bituminous Coal ◽  
Gaussian Function ◽  
Parameters Optimization ◽  
Shuffled Complex Evolution

DWT-PLS Regression on Near-Infrared Spectra for Moisture and Volatile Determination of Coal

2013 ◽  
Vol 848 ◽  
pp. 313-316
Author(s):  
Xiao Li Yang ◽  
Fan Wang ◽  
Ji Shu Chen ◽  
Gong Zhe Ma
Keyword(s):  
Partial Least Squares Regression ◽  
Bituminous Coal ◽  
Near Infrared ◽  
Parameters Optimization ◽  
Discrete Wavelet ◽  
Pls Regression ◽  
Least Squares Regression ◽  
Satisfactory Performance ◽  
Near Infrared Spectra

We studied moisture and volatile determination in bituminous coal samples using near-infrared (NIR) spectra. This research was developted by applying partial least squares regression (PLS) and discrete wavelet transform (DWT). Firstly, NIR spectra were pre-processed by DWT for fitting and compression. Then, DWT coefficients were used to build regression model with PLS. We used NIR spectra to determination moisture and volatile determination in coal samples seperately and simultaneously. Through parameters optimization, the results show that DWT-PLS can obtain satisfactory performance for separate and simultanous determination.

DWT-SVM on Near-Infrared Spectra for Moisture and Volatile Determination of Coal

2013 ◽  
Vol 483 ◽  
pp. 71-74
Author(s):  
Xiao Li Yang ◽  
Fan Wang ◽  
Ji Shu Chen ◽  
Shui Hua Zhang
Keyword(s):  
Support Vector Machine ◽  
Wavelet Transform ◽  
Bituminous Coal ◽  
Near Infrared ◽  
Parameters Optimization ◽  
Support Vector ◽  
Discrete Wavelet ◽  
Satisfactory Performance ◽  
Near Infrared Spectra

We studied moisture and volatile determination in bituminous coal samples using near-infrared (NIR) spectra. This research applied support vector machine (SVM) and discrete wavelet transform (DWT). Firstly, NIR spectra were pre-processed by DWT for fitting and compression. Then, DWT coefficients were used to build regression model with SVM. We used NIR spectra to determination moisture and volatile determination in coal samples separately. Through parameters optimization, the results show that DWT-SVM can obtain satisfactory performance for moisture and volatile determination in coal samples.

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