348
Views
7
CrossRef citations to date
0
Altmetric
Research Article

An artificial intelligence approach to predict a lower heating value of municipal solid waste

References

  • Akkaya, E., and Demir, A. 2010. Predicting the heating value of municipal solid waste-based materials: an artificial neural network model. Energy Sour. Part A-Recovery Util. Environ. Eff. 32:1777–1783.
  • Burden, F., and Winkler, D. 2008. Bayesian regularization of neural networks. Methods Mol. Biol. 458:25–44.
  • Cevoli, C., Cerretani, L., Gori, A., Caboni, M. F., Toschi, T. G., and Fabbri, A. 2011. Classification of Pecorino cheeses using electronic nose combined with artificial neural network and comparison with GC-MS analysis of volatile compounds. Food Chem. 129:1315–1319.
  • Chang, Y. F., Lin, C. J., Chyan, J. M., Chen, I. M., and Chang, J. E. 2007. Multiple regression models for the lower heating value of municipal solid waste in Taiwan. J. Environ. Manage. 85:891–899.
  • Chavan, P. D., Sharma, T., Mall, B. K., Rajurkar, B. D., Tambe, S. S., Sharma, B. K., and Kulkarni, B. D. 2012. Development of data-driven models for fluidized-bed coal gasification process. Fuel 93:44–51.
  • Dong, C. Q., Jin, B. S., and Li, D. J. 2003. Predicting the heating value of MSW with a feed forward neural network. Waste Manage. 23:103–106.
  • Dong, C. Q., Jin, B. S., Zhong, Z. P., and Lan, J. X. 2002. Tests on co-firing of municipal solid waste and coal in a circulating fluidized bed. Energy Convers. Manage. 43:2189–2199.
  • Jin, Y., Yan, J., Chi, Y., Li, X., Ma, Z., Jiang, X., Ni, M., and Kefa, C. 2002. Combustion characteristics of municipal solid wastes in China. Huan Jing Ke Xue 23:107–110.
  • Jorjani, E., Chelgani, S. C., and Mesroghli, S. 2008. Application of artificial neural networks to predict chemical desulfurization of Tabas coal. Fuel 87:2727–2734.
  • Khan, M. Z. A., and Abughararah, Z. H. 1991. New approach for estimating energy content of municipal solid-waste. J. Environ. Eng.-Asce 117:376–380.
  • Lau, K. T., Guo, W. M., Kiernan, B., Slater, C., and Diamond, D. 2009. Non-linear carbon dioxide determination using infrared gas sensors and neural networks with Bayesian regularization. Sensors and Actuators B-Chemical 136:242–247.
  • Lin, S. H., Chen, X. L., Zhu, X. C., Ding, Y. Q., and Wang, K. 2009. Prediction of heat value of chongqing municipal solid waste using artificial neural networks. Fuzzy Inf. Eng. 2:1519–1528.
  • Lin, C. J., Chyan, J. M., Chen, I. M., and Wang, Y. T. 2013. Swift model for a lower heating value prediction based on wet-based physical components of municipal solid waste. Waste Manage. 33:268–276.
  • Lin, X. B., Wang, F., Chi, Y., Huang, Q. X., and Yan, J. H. 2015. A simple method for predicting the lower heating value of municipal solid waste in China based on wet physical composition. Waste Manage. 36:24–32.
  • Liu, J. I., Paode, R. D., and Holsen, T. M. 1996. Modeling the energy content of municipal solid waste using multiple regression analysis. J. Air Waste Manage. Assoc. 46 (7):650–656.
  • Mesroghli, S., Jorjani, E., and Chelgani, S. 2009. Estimation of gross calorific value based on coal analysis using regression and artificial neural networks. Int. J. Coal Geol. 79:49–54.
  • Mikulandric, R., Loncar, D., Bohning, D., Bohme, R., and Beckmann, M. 2014. Artificial neural network modelling approach for a biomass gasification process in fixed bed gasifiers. Energy Convers. Manage. 87:1210–1223.
  • Huang, M. X., and Liu, D. 2012. Characteristic and composition of municipal solid waste in Sichuan province. Environ. Monit. China 12:121–123.
  • Sun, P-F., Li, X-D., and Chi, Y. E. A. 2006. The study on prediction of lower heat value of MSW. Energy Environ. 5:39–43.
  • He, S., Zhu, S. Y., and Yu, L. Q. 2008. Characteristics analysis and treatment countermeasure of domestic waste in Suzhou city. Environ. Sanit. Eng. 16:62–66.
  • Shu, H. Y., Lu, H. C., Fan, H. J., Chang, M. C., and Chen, J. C. 2006. Prediction for energy content of Taiwan municipal solid waste using multilayer perceptron neural networks. J. Air Waste Manage. Assoc. 56:852–858.
  • Tian, W. D., Wei, X. L., Wu, D. Y., Li, J., and Sheng, H. Z. 2001. Analysis of ingredient and heating value of municipal solid waste. J. Environ. Sci.-China 13:87–91.
  • Wang, K. Y. 2007. Study on Calculating Model of Heating Value of Municipal Solid Waste. Wuhan city: Huazhong University of Science and Technology.
  • Zhou, H., Meng, A. H., Long, Y. Q., Li, Q. H., and Zhang, Y. G. 2014. An overview of characteristics of municipal solid waste fuel in China: Physical, chemical composition and heating value. Renewable Sustainable Energy Rev. 36:107–122.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.