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Grain Moisture Sensor Data Fusion Based on Improved Radial Basis Function Neural Network
[chapter]
2013
IFIP Advances in Information and Communication Technology
Difficulty was known to get satisfactory measurement effect on precision in capacitive grain's moisture measurement due to many influencing factors, such as temperature, species, compaction and so on. The data confusion method of Radial Basis Function (RBF) nerve network is adopted. With improved orthogonal optimal method, the RBF nerve network's weight factors can be obtained. This method can avoid artificially selected the number of hidden units, which can cause low learn precision or over
doi:10.1007/978-3-642-36137-1_13
fatcat:kmc3jvnswzbbtkpfqsvcazzpnu