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

ÖZVEREN U.

ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS, cilt.38, sa.19, ss.2906-2913, 2016 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 38 Sayı: 19
  • Basım Tarihi: 2016
  • Doi Numarası: 10.1080/15567036.2015.1107864
  • Dergi Adı: ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED)
  • Sayfa Sayıları: ss.2906-2913
  • Anahtar Kelimeler: Artificial neural network, lower heating value, municipal solid waste, nonlinear regression model, predictive model, NEURAL-NETWORK, ENERGY CONTENT, MODELS, COAL
  • Marmara Üniversitesi Adresli: Evet

Özet

The lower heating value is an important parameter to conduct the modeling of any fuel processing system. In this study, the relationship between the physical composition of municipal solid waste and its lower heating values was investigated using a Bayesian regularized artificial neural network (ANN) as an artificial intelligence approach. A new nonlinear regression model was also developed in this study. The artificial intelligence approach was compared using the developed and published correlations. The approach offers a high degree of correlation, and as a result, the ANN provides a useful tool for designing any thermolysis process for municipal solid waste.