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- W2153115422 abstract "A SVR modeling based online coal calorific value prediction method was introduced. Through wavelet transform and PCS process, coal flame radiation characteristics were extracted. Through SVR modeling, relationship model between radiation characteristic variables and coal calorific value was established. Proper SVR construction parameters were chosen through grid computing. Experiment results showed good coherence between SVR model prediction and laboratory results of coal calorific value. Proposed SVR based system relies on low cost multiband photoelectric sensors, which is easy to be installed at production spot, while satisfying system performance could meet practical needs of online operation adjusting to enhance production efficiency and diminish pollutant emissions." @default.
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- W2153115422 date "2012-07-01" @default.
- W2153115422 modified "2023-10-16" @default.
- W2153115422 title "Online coal calorific value prediction from mutiband coal/air combustion radiation characteristics" @default.
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- W2153115422 doi "https://doi.org/10.1109/isict.2012.6291636" @default.
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