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Prediction of the higher heating value of biomass based on multiple classification methods

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Abstract

In general, measuring the higher heating value (HHV) of biomass by experimental methods is time-consuming and complex. These problems can be effectively avoided by studying HHV prediction of biomass. This study innovatively predicts the HHV of biomass from a new perspective, that is, biomass data samples are classified according to three different classification methods: biomass categories classification, K-means clustering classification, and ash and volatile matter (VM) content classification, and then predicting the HHV of biomass. It demonstrated that the predictive result of the classification methods was better than that of the non-classified. In the three methods, the method of classifying biomass by ash and VM content showed the best effect, with an average absolute error (MAE) of 0.755 MJ/kg and an average absolute percentage error (MAPE) of 4%. It revealed that modeling after sample classification can effectively improve the prediction accuracy of biomass HHV. It is a simple and feasible strategy and method. The improvement of prediction accuracy may be through different classification methods, which makes it easier for the model to capture the relationship between specific types of HHV, ash, VM, and fixed carbon (FC) in the prediction process, thus improving the efficiency of the model. Meanwhile, this study will provide a reference significance for the prediction of the products and properties of biomass in thermochemical conversion technology.

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Data availability

The collected data on the proximate analysis and HHV are listed in Appendix A of the supplementary document.

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Funding

This work was supported by the National “Belt and Road” Innovative Talent Exchange Program for Foreign Experts (DL2022012002L), the National Natural Science Foundation of China (51406045), and the Natural Science Foundation of Heilongjiang Province of China (LH2021E084).

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Authors and Affiliations

  1. School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin, 150080, China

    Chenxi Zhao, Xueying Lu & Yu Zhang

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  1. Chenxi Zhao
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  2. Xueying Lu
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  3. Yu Zhang
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Contributions

Chenxi Zhao conceptualized and designed the research problem. Material preparation, data collection, formal analysis, investigation, and interpretation were performed by Xueying Lu. Yu Zhang prepared and presented published works, especially data presentations, and submitted the MS. All authors read and approved the final manuscript.

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Correspondence to Chenxi Zhao.

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Zhao, C., Lu, X. & Zhang, Y. Prediction of the higher heating value of biomass based on multiple classification methods. Biomass Conv. Bioref. (2024). https://doi.org/10.1007/s13399-024-05305-x

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