@article{(Open Science Index):https://publications.waset.org/pdf/13567,
	  title     = {Predicting Oil Content of Fresh Palm Fruit Using Transmission-Mode Ultrasonic Technique},
	  author    = {Sutthawee Suwannarat and  Thanate Khaorapapong and  Mitchai Chongcheawchamnan},
	  country	= {},
	  institution	= {},
	  abstract     = {In this paper, an ultrasonic technique is proposed to
predict oil content in a fresh palm fruit. This is accomplished by
measuring the attenuation based on ultrasonic transmission mode.
Several palm fruit samples with known oil content by Soxhlet
extraction (ISO9001:2008) were tested with our ultrasonic
measurement. Amplitude attenuation data results for all palm samples
were collected. The Feedforward Neural Networks (FNNs) are
applied to predict the oil content for the samples. The Root Mean
Square Error (RMSE) and Mean Absolute Error (MAE) of the FNN
model for predicting oil content percentage are 7.6186 and 5.2287
with the correlation coefficient (R) of 0.9193.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {5},
	  number    = {9},
	  year      = {2011},
	  pages     = {1073 - 1076},
	  ee        = {https://publications.waset.org/pdf/13567},
	  url   	= {https://publications.waset.org/vol/57},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 57, 2011},
	}