摘要翻译：
电力市场的参与者非常关注市场价格的演变。各种技术已经被开发出来用于价格预测。支持向量机（Support Vector Machine，简称SVM）在市场价格预测中表现出了良好的性能。提出了两种基于支持向量机的市场竞价策略形成方法。一种是基于价格预测的准确性，以此来定义被拒绝的风险。另一种则考虑到生产者自己出价的影响。与投标有关的风险是通过参数设置来控制的。数值算例验证了所提方法的有效性。
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英文标题：
《Bidding Strategy with Forecast Technology Based on Support Vector
  Machine in Electrcity Market》
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作者：
C. Gao, E. Bompard, R. Napoli, Q. Wan
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最新提交年份：
2007
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：General Finance        一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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一级分类：Physics        物理学
二级分类：Data Analysis, Statistics and Probability        数据分析、统计与概率
分类描述：Methods, software and hardware for physics data analysis: data processing and storage; measurement methodology; statistical and mathematical aspects such as parametrization and uncertainties.
物理数据分析的方法、软硬件：数据处理与存储；测量方法；统计和数学方面，如参数化和不确定性。
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英文摘要：
  The participants of the electricity market concern very much the market price evolution. Various technologies have been developed for price forecast. SVM (Support Vector Machine) has shown its good performance in market price forecast. Two approaches for forming the market bidding strategies based on SVM are proposed. One is based on the price forecast accuracy, with which the being rejected risk is defined. The other takes into account the impact of the producer's own bid. The risks associated with the bidding are controlled by the parameters setting. The proposed approaches have been tested on a numerical example.
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PDF链接：
https://arxiv.org/pdf/0709.3710