Abstract
Moisture is one of the most important factors affecting grain quality in storage. The grain must be dried as soon as possible after harvesting to lower moisture to a standard level. It is difficult to obtain satisfactory measurement effect on precision in capacitive grain's moisture measurement due to many influencing factors, such as temperature, species and weight. The data confusion method of Radial Basis Function nerve network is adopted with improved hardware of the measurement system. Tests show that the precision in moisture measurement of wheat has been improved. © 2012 IFIP Federation for Information Processing.
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Yang, L., Zheng, Y., Jiang, Z., & Ren, Z. (2012). Improvement of the capacitive grain moisture sensor. In IFIP Advances in Information and Communication Technology (Vol. 370 AICT, pp. 300–307). https://doi.org/10.1007/978-3-642-27275-2_34
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