Recurrent Neural Networks for Moisture Content Prediction in Seed Corn Dryer Buildings

D. Elliott, Russell E. Valentine
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引用次数: 4

Abstract

Conditioning seed corn is a short, yet crucial, portion of the seed production process. Seed corn must be conditioned prior to removing the seed from the cob to prevent damage, requiring constant monitoring by farmers. This paper evaluates the use of an echo state network for the prediction of seed moisture content and compares it against an Elman network. The results are determined to be good enough for inclusion into a commercially available dryer monitoring system.
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循环神经网络用于种子玉米干燥机厂房水分预测
玉米种子的调理是种子生产过程中一个短暂但至关重要的部分。玉米种子在从玉米芯上取下种子之前必须进行条件处理,以防止损坏,这需要农民不断地监测。本文评价了回声状态网络在种子含水量预测中的应用,并将其与Elman网络进行了比较。结果被确定为足够好,以纳入商用干燥机监测系统。
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