On-line Inference of Sintering Quality via Neural Networks
-
摘要: 針對燒結過程生產實際,運用神經網絡中的BP學習算法設計了分類器,用于在線推斷燒結礦的質量。為了加快BP學習算法的收斂速度,采用了自適應變步長學習算法。實驗結果表明,由此建立的燒結過程神經網絡質量預報模型,預報正確率高,具有很好的泛化能力。
-
關鍵詞:
- 燒結 /
- 神經網絡 /
- 模式識別/自適應變步長
Abstract: Presents a new method of on-line inference of sintering quality. Neural networks to build the sinternig quality inference model are used. To speed the learning, a fast BP learning algorithm with adaptive variable step size via linear reinforcement is presented.The experiment result is satisftory, and this method may be used widely in other complicated production proasses. -
點擊查看大圖
計量
- 文章訪問數: 215
- HTML全文瀏覽量: 104
- PDF下載量: 5
- 被引次數: 0
下載:
