铜陵学院学报
銅陵學院學報
동릉학원학보
JOURNAL OF TONGLING COLLEGE
2014年
5期
102-104
,共3页
电价预测%小波分解%支持向量机%参数自适应调整
電價預測%小波分解%支持嚮量機%參數自適應調整
전개예측%소파분해%지지향량궤%삼수자괄응조정
electricity price forecasting%wavelet decomposition%support vector machine%parameter adaptive adjustment
电价预测对于发电商、供电企业以及市场监管者都具有重要的意义。提出一种小波自适应支持向量机预测模型，先将电价时间序列作小波分解得到低频和高频分量，再采用自适应调整法，自动地为支持向量机选择较好的参数对电价小波分量逐一预测，最后通过小波重构得到电价最终预测结果。实例证明前述方法得到的预测精度高于BP、RBF、SVM等传统预测模型。
電價預測對于髮電商、供電企業以及市場鑑管者都具有重要的意義。提齣一種小波自適應支持嚮量機預測模型，先將電價時間序列作小波分解得到低頻和高頻分量，再採用自適應調整法，自動地為支持嚮量機選擇較好的參數對電價小波分量逐一預測，最後通過小波重構得到電價最終預測結果。實例證明前述方法得到的預測精度高于BP、RBF、SVM等傳統預測模型。
전개예측대우발전상、공전기업이급시장감관자도구유중요적의의。제출일충소파자괄응지지향량궤예측모형，선장전개시간서렬작소파분해득도저빈화고빈분량，재채용자괄응조정법，자동지위지지향량궤선택교호적삼수대전개소파분량축일예측，최후통과소파중구득도전개최종예측결과。실예증명전술방법득도적예측정도고우BP、RBF、SVM등전통예측모형。
Electricity price forecasting is of important significance for electricity generators, power supply enterprises and market regulator. A wavelet adaptive support vector machine forecasting model is proposed in the paper. Firstly, the electricity price time series are decomposed to low frequency and high frequency wavelet components, then the adaptive adjustment method are adopted to select pa-rameters automatically for support vector machine to forecast electricity price wavelet components one by one, and the final prediction re-sult is achieved by wavelet reconstruction. The example proves that the proposed method behaves a higher prediction accuracy than tradi-tional forecasting models such as BP network.
