| 高炉异常炉况的模糊预测模型 |
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| 引用本文： | 李启会,刘祥官.高炉异常炉况的模糊预测模型[J].中国冶金,2007,17(4):34-34. |
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| 作者姓名： | 李启会 刘祥官 |
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| 作者单位： | 1.嘉兴学院数学系，浙江 嘉兴 314001；2.浙江大学数学系，浙江 杭州 310027 |
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| 基金项目： | 国家科技成果推广计划;国家重点基础研究发展计划(973计划) |
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| 摘 要： | 将神经网络和模糊数学理论相结合，建立了一种新型的炉况预报模型，利用模糊神经网络的并行处理特性进行模糊推理。模糊神经网络的并行数学计算过程取代了专家系统中传统的参数处理，具有更高的推理效率；且神经网络的学习能力实现了隶属函数和模糊规则的自学习，从而满足了高炉专家系统知识库的动态特征，有效提高了炉况预报模型的自适应能力。最后，应用莱钢1号高炉在线采集的数据动态模拟了高炉炉况的变化趋势。
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| 关 键 词： | 炉况 模糊化 模糊推理 模拟 预报 |
| 文章编号： | 1006-9356（2007）04-0034-04 |
| 修稿时间： | 2006-12-29 |
Fuzzy Forecasting Model for Abnormal BF State |
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| LI Qi-hui,LIU Xiang-guan.Fuzzy Forecasting Model for Abnormal BF State[J].China Metallurgy,2007,17(4):34-34. |
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| Authors: | LI Qi-hui LIU Xiang-guan |
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| Affiliation: | 1. Department of Mathematics，Jiaxing University, Jiaxing 314001, Zhejiang,China；
2. Department of Mathematics, Zhejiang University, Hangzhou 310027, Zhejiang,China |
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| Abstract: | Based on fuzzy theory and neutral net, a new fuzzy forecasting model for abnormal BF state was developed to fuzzily reason with parallel computation of fuzzy neutral net system, which replaces fuzzy inference and the traditional computation of parameters of expert system. The self learning of fuzzy membership function and fuzzy rules is realized by fuzzy NN system, and then, dynamical character of BF expert system is achieved and self adaptation ability of the model forecasting abnormal BF state is improved. BF state is simulated using the data collected online from No. 1 BF at Laiwu Iron and Steel Co Ltd. |
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| Keywords: | BF state fuzzifization fuzzy inference I simulation forecasting |
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