基于改进果蝇算法与最小二乘支持向量机的轧制力预测算法研究 |
| |
引用本文: | 杨景明,郭秋辰,孙浩,马明明,车海军,赵新秋. 基于改进果蝇算法与最小二乘支持向量机的轧制力预测算法研究[J]. 计量学报, 2016, 0(5): 505-508. DOI: 10.3969/j.issn.1000-1158.2016.05.11 |
| |
作者姓名: | 杨景明 郭秋辰 孙浩 马明明 车海军 赵新秋 |
| |
作者单位: | 1. 燕山大学工业计算机控制工程河北省重点实验室,河北 秦皇岛066004; 国家冷轧板带装备及工艺工程技术研究中心,河北 秦皇岛066004;2. 燕山大学工业计算机控制工程河北省重点实验室,河北 秦皇岛,066004 |
| |
基金项目: | 河北省高等学校创新团队领军人才培育计划(LJRC013);国家冷轧板带装备及工艺工程技术研究中心开放课题(2012005);河北省科技支撑计划(13211817) |
| |
摘 要: | 铝合金板材精轧过程中,轧制力是影响板材质量的重要因素。为了满足轧制现场的轧制力预报精度要求,采用改进果蝇算法(FOA)与最小二乘支持向量机(LSSVM)相结合进行轧制力预测。改进了果蝇算法的味道浓度判定函数和步长设定方法,采用了分组并行搜索的策略,进而提出一种基于改进FOA-LSSVM的轧制力智能预报方法。将该方法用于铝热连轧现场数据的仿真实验,结果表明样本预测误差在10%以内,其中84%的样本误差在5%以内,精度优于传统模型。
|
关 键 词: | 计量学 轧制力预测 最小二乘支持向量机 果蝇算法 |
Research on the Predictive AIgorithm of RoIIing Force Based on the Improved Fruit FIies Optimization AIgorithm with LSSVM |
| |
Abstract: | In the process of aluminum alloy plate finishing,rolling force is an important factor affecting the quality of plate. In order to meet the scene of the rolling forecast accuracy,improved fruit flies optimization algorithm( FOA)is combined with least square support vector machine( LSSVM)for rolling force prediction. The function of smell and the method of step length setting are improved. The grouping parallel search strategy is used. A new method based on the improved FOA-LSSVM is proposed for rolling force prediction. The method is used in simulation experiment of field data of aluminum strip,the results show that the prediction error data is in the range of ten percent,and eighty-four percent of these error data is in the range of five percent,the result shows that this method is better than the traditional model. |
| |
Keywords: | metrology rolling force prediction least squares support vector machine fruit flies optimization algorithm |
本文献已被 CNKI 万方数据 等数据库收录! |
|