Moisture determination with an artificial neural network from microwave measurements on wheat

被引：0
|
作者：
Bartley, PG
McClendon, RW
Nelson, SO
Trabelsi, S
机构：
来源：
IMTC/97 - IEEE INSTRUMENTATION & MEASUREMENT TECHNOLOGY CONFERENCE: SENSING, PROCESSING, NETWORKING, PROCEEDINGS VOLS 1 AND 2 | 1997年
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中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
An Artificial Neural Network (ANN) was used to determine the moisture content of hard red winter wheat. The ANN was trained to recognize moisture content in the range from 10.6% to 19.2% (wet basis) from transmission coefficient measurements on samples of wheat placed between two radiating elements. The measurements were made at 8 microwave frequencies (10 to 18 GHz) on wheat samples of varying bulk densities (0.72 to 0.88 g/cm(3)) at 24 degrees C. The trained network predicted moisture content (%) with a mean absolute error of 0.135.
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页码：1238 / 1241
页数：4
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