@article{(Open Science Index):https://publications.waset.org/pdf/5716,
	  title     = {Combining Fuzzy Logic and Neural Networks in Modeling Landfill Gas Production},
	  author    = {Mohamed Abdallah and  Mostafa Warith and  Roberto Narbaitz and  Emil Petriu and  Kevin Kennedy},
	  country	= {},
	  institution	= {},
	  abstract     = {Heterogeneity of solid waste characteristics as well as the complex processes taking place within the landfill ecosystem motivated the implementation of soft computing methodologies such as artificial neural networks (ANN), fuzzy logic (FL), and their combination. The present work uses a hybrid ANN-FL model that employs knowledge-based FL to describe the process qualitatively and implements the learning algorithm of ANN to optimize model parameters. The model was developed to simulate and predict the landfill gas production at a given time based on operational parameters. The experimental data used were compiled from lab-scale experiment that involved various operating scenarios. The developed model was validated and statistically analyzed using F-test, linear regression between actual and predicted data, and mean squared error measures. Overall, the simulated landfill gas production rates demonstrated reasonable agreement with actual data. The discussion focused on the effect of the size of training datasets and number of training epochs.
},
	    journal   = {International Journal of Civil and Environmental Engineering},
	  volume    = {5},
	  number    = {6},
	  year      = {2011},
	  pages     = {273 - 279},
	  ee        = {https://publications.waset.org/pdf/5716},
	  url   	= {https://publications.waset.org/vol/54},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 54, 2011},
	}