To realize the automatic detection of solar radio burst(SRB)intensity,detection based on a modified multifactor support vector machine(SVM)algorithm is proposed.First,the influence of SRB on global navigation satellit...To realize the automatic detection of solar radio burst(SRB)intensity,detection based on a modified multifactor support vector machine(SVM)algorithm is proposed.First,the influence of SRB on global navigation satellite system(GNSS)signals is analyzed.Feature vectors,which can reflect the SRB intensity of stations,are also extracted.SRB intensity is classified according to the solar radio flux,and different class labels correspond to different SRB intensity types.The training samples are composed of feature vectors and their corresponding class labels.Second,training samples are input into SVM classifiers to one-against-one training to obtain the optimal classification models.Finally,the optimal classification model is synthesized into a modified multifactor SVM classifier,which is used to automatically detect the SRB intensity of new data.Experimental results indicate that for historical SRB events,the average accuracy of SRB intensity detection is greater than 90%when the solar incident angle is higher than 20°.Compared with other methods,the proposed method considers many factors with higher accuracy and does not rely on radio telescopes,thereby saving cost.展开更多
以非侵入式负荷分解为基础,对用户异常用电行为进行研究。采用Kmeans聚类算法提取负荷状态特征;采用深度学习算法中的序列到序列翻译(sequence to sequence, seq2seq)模型,将电力用户用电总数据分解成单个电器的功耗数据;结合SVM算法对...以非侵入式负荷分解为基础,对用户异常用电行为进行研究。采用Kmeans聚类算法提取负荷状态特征;采用深度学习算法中的序列到序列翻译(sequence to sequence, seq2seq)模型,将电力用户用电总数据分解成单个电器的功耗数据;结合SVM算法对分解后多种家用电器用电数据进行异常检测。在UKDALE数据集实验结果表明,该模型不仅能提高分解准确度、降低分解误差,而且多个电器数据结合分析实现了用户异常行为检测。展开更多
为了提高生活污水处理工艺流程设计的效率,建立污水处理工艺数据库,用以保存从现实生活污水处理工艺流程抽象而来的数据样本。使用基于边界点的支持向量机(support vector machine classification algorithm based on boundary points,B...为了提高生活污水处理工艺流程设计的效率,建立污水处理工艺数据库,用以保存从现实生活污水处理工艺流程抽象而来的数据样本。使用基于边界点的支持向量机(support vector machine classification algorithm based on boundary points,BP-SVM)的工艺流程设计算法选择工艺,设置多个BP-SVM解决多分类问题,并使用遗传算法(genetic algorithm,GA)对BP-SVM参数进行参数寻优。结果表明:工艺流程设计算法给出了合适的方案,准确率达到94%,并且与其他算法相比消耗更小。证明了算法的可行性与有效性。展开更多
基金The National Key Research and Development Plan of China(No.2018YFB0505103)the National Natural Science Foundation of China(No.61873064)。
文摘To realize the automatic detection of solar radio burst(SRB)intensity,detection based on a modified multifactor support vector machine(SVM)algorithm is proposed.First,the influence of SRB on global navigation satellite system(GNSS)signals is analyzed.Feature vectors,which can reflect the SRB intensity of stations,are also extracted.SRB intensity is classified according to the solar radio flux,and different class labels correspond to different SRB intensity types.The training samples are composed of feature vectors and their corresponding class labels.Second,training samples are input into SVM classifiers to one-against-one training to obtain the optimal classification models.Finally,the optimal classification model is synthesized into a modified multifactor SVM classifier,which is used to automatically detect the SRB intensity of new data.Experimental results indicate that for historical SRB events,the average accuracy of SRB intensity detection is greater than 90%when the solar incident angle is higher than 20°.Compared with other methods,the proposed method considers many factors with higher accuracy and does not rely on radio telescopes,thereby saving cost.
文摘以非侵入式负荷分解为基础,对用户异常用电行为进行研究。采用Kmeans聚类算法提取负荷状态特征;采用深度学习算法中的序列到序列翻译(sequence to sequence, seq2seq)模型,将电力用户用电总数据分解成单个电器的功耗数据;结合SVM算法对分解后多种家用电器用电数据进行异常检测。在UKDALE数据集实验结果表明,该模型不仅能提高分解准确度、降低分解误差,而且多个电器数据结合分析实现了用户异常行为检测。
文摘为了提高生活污水处理工艺流程设计的效率,建立污水处理工艺数据库,用以保存从现实生活污水处理工艺流程抽象而来的数据样本。使用基于边界点的支持向量机(support vector machine classification algorithm based on boundary points,BP-SVM)的工艺流程设计算法选择工艺,设置多个BP-SVM解决多分类问题,并使用遗传算法(genetic algorithm,GA)对BP-SVM参数进行参数寻优。结果表明:工艺流程设计算法给出了合适的方案,准确率达到94%,并且与其他算法相比消耗更小。证明了算法的可行性与有效性。
