| 能源需求的支持向量机预测 |
| |
| 引用本文： | 陈钢,高尚. 能源需求的支持向量机预测[J]. 科学技术与工程, 2008, 8(3): 757-759763 |
| |
| 作者姓名： | 陈钢 高尚 |
| |
| 作者单位： | 江苏索普集团,镇江,212006;江苏科技大学电子信息学院,镇江,212003 |
| |
| 摘 要： | 对灰色、神经网络和支持向量机的三个预测模型进行了研究,以某城市的1999-2006年能源需求为例,对能源需求进行了预测.经过比较,支持向量机的预测方法精度较高.
|
| 关 键 词： | 灰色系统 神经网络 支持向量机 能源 |
| 收稿时间： | 2007-10-24 |
| 修稿时间： | 2007-10-24 |
Energy Demand Forecast Based on Support Vector Machine |
| |
| CHEN Gang,GAO Shang. Energy Demand Forecast Based on Support Vector Machine[J]. Science Technology and Engineering, 2008, 8(3): 757-759763 |
| |
| Authors: | CHEN Gang GAO Shang |
| |
| Abstract: | The grey system forecasting model, neural network forecasting model and support vector machine forecasting model are proposed. Taking energy demand of a city from year of 1999 to 2006 as a study case, the forecasting results are got by three methods. From the forecasting results, the accuracy can conclude of the support vector machine forecasting method is higher. |
| |
| Keywords: | grey system neural network support vector machine combining forecasting energy |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《科学技术与工程》浏览原始摘要信息 |
|
点击此处可从《科学技术与工程》下载全文 |
|
