| 基于成分预测模型的矿石烧结配料专家优化方法 |
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| 引用本文： | 向齐良,吴敏,侯奔,向婕.基于成分预测模型的矿石烧结配料专家优化方法[J].山东工业大学学报,2005,35(4):43-46. |
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| 作者姓名： | 向齐良 吴敏 侯奔 向婕 |
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| 作者单位： | [1]中南大学信息科学与工程学院,湖南长沙410083 [2]韶关钢铁集团有限公司,广东韶关512123 |
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| 基金项目： | 国家杰出青年科学基金项目（60425310）;教育部青年教师奖项目（教人[2002]5号） |
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| 摘 要： | 配料是烧结的前期工序，如何获得各种铁矿石和非铁原料的配比是烧结配料的关键问题，针对桌钢铁企业烧结配料的特点，建立了基于数学模型和神经网络的成分预测模型，构筑了用于配比调整的专家规则，提出了配比优化与计算算法，通过数学模型、神经网络和专家规则的有机结合，实现了烧结配料的优化与控制。
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| 关 键 词： | 烧结过程 配料过程 数学模型 神经网络 专家规则 优化算法 |
| 文章编号： | 1672-3961（2005）04-0043-04 |
| 收稿时间： | 2005-02-15 |
An expert optimization method based on ingredient prediction models for the blending and sintering of iron ore |
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| Xiang JiLiang;Wu Min;Hou Ben;Xiang Jie.An expert optimization method based on ingredient prediction models for the blending and sintering of iron ore[J].Journal of Shandong University of Technology,2005,35(4):43-46. |
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| Authors: | Xiang JiLiang;Wu Min;Hou Ben;Xiang Jie |
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| Abstract: | Blending is the process prior to sintering. It is important to determine the percentages of different kinds of iron ore and nonmetallic material to be blended. For the characteristics of the blending and sintering in an iron and steel enterprise, ingredient prediction models based on mathematical models and neural networks are established, expert rules used to adjust the percentages is constructed, and a percentages optimization and computational algorithm is proposed. Combining the mathematical models, neural networks and expert rules can implement the optimization and control of the blending and sintering. |
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| Keywords: | sintering process blending process mathematical models neural networks expert rules optimization algorithm |
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