Accurate forecasting of wind velocity can improve the economic dispatch and safe operation of the power system. Support vector machine (SVM) has been proved to be an efficient approach for forecasting. According to th...Accurate forecasting of wind velocity can improve the economic dispatch and safe operation of the power system. Support vector machine (SVM) has been proved to be an efficient approach for forecasting. According to the analysis with support vector machine method, the drawback of determining the parameters only by experts' experience should be improved. After a detailed description of the methodology of SVM and simulated annealing, an improved algorithm was proposed for the automatic optimization of parameters using SVM method. An example has proved that the proposed method can efficiently select the parameters of the SVM method. And by optimizing the parameters, the forecasting accuracy of the max wind velocity increases by 34.45%, which indicates that the new SASVM model improves the forecasting accuracy.展开更多
直流电源蓄电池组在运行过程中会产生大量的数据,这些数据具有时间序列长、维度高、非线性等特点。如何有效处理和分析这些庞大而复杂的数据并提取出有价值的信息,是容量预测面临的一个重要挑战。基于此,提出改进支持向量机下直流电源...直流电源蓄电池组在运行过程中会产生大量的数据,这些数据具有时间序列长、维度高、非线性等特点。如何有效处理和分析这些庞大而复杂的数据并提取出有价值的信息,是容量预测面临的一个重要挑战。基于此,提出改进支持向量机下直流电源蓄电池组容量预测方法。综合考虑直流电源蓄电池组放电深度、剩余电量(State Of Charge,SOC)变化量、平均充电电流和充电时间,采集直流电源蓄电池组运行参数。同时,引入模拟退火算法精确选取支持向量机参数,结合遗传算法构建基于改进支持向量机的直流电源蓄电池组容量预测模型。实验结果表明,研究方法能够显著提升直流电源蓄电池组容量预测的精度和收敛性能,确保预测结果的准确性。展开更多
为提高卫星星座网络受到攻击后的抗毁性及工作能力,提出了一种模拟退火狼群算法。该算法利用主客观权重法结合综合逼近理想排序法(TOPSIS:Technique for Order Preference by Similarity to Ideal Solution)对网络中的节点进行重要度评...为提高卫星星座网络受到攻击后的抗毁性及工作能力,提出了一种模拟退火狼群算法。该算法利用主客观权重法结合综合逼近理想排序法(TOPSIS:Technique for Order Preference by Similarity to Ideal Solution)对网络中的节点进行重要度评估,并按照节点重要度排序依次攻击。以网络连通度与网络连通效率为优化目标,卫星星座网络通信限制为约束条件,采用运动算子的思想实现狼群自适应步长的游走、召唤和围攻。使用通过优化得出的加边方案对网络结构进行优化。实验表明,与其他优化算法相比,该算法具有优越性,解决了卫星星座网络在受到攻击后工作能力下降的问题,提高了其受到攻击后的抗毁性。展开更多
基金Project(71071052) supported by the National Natural Science Foundation of ChinaProject(JB2011097) supported by the Fundamental Research Funds for the Central Universities of China
文摘Accurate forecasting of wind velocity can improve the economic dispatch and safe operation of the power system. Support vector machine (SVM) has been proved to be an efficient approach for forecasting. According to the analysis with support vector machine method, the drawback of determining the parameters only by experts' experience should be improved. After a detailed description of the methodology of SVM and simulated annealing, an improved algorithm was proposed for the automatic optimization of parameters using SVM method. An example has proved that the proposed method can efficiently select the parameters of the SVM method. And by optimizing the parameters, the forecasting accuracy of the max wind velocity increases by 34.45%, which indicates that the new SASVM model improves the forecasting accuracy.
文摘直流电源蓄电池组在运行过程中会产生大量的数据,这些数据具有时间序列长、维度高、非线性等特点。如何有效处理和分析这些庞大而复杂的数据并提取出有价值的信息,是容量预测面临的一个重要挑战。基于此,提出改进支持向量机下直流电源蓄电池组容量预测方法。综合考虑直流电源蓄电池组放电深度、剩余电量(State Of Charge,SOC)变化量、平均充电电流和充电时间,采集直流电源蓄电池组运行参数。同时,引入模拟退火算法精确选取支持向量机参数,结合遗传算法构建基于改进支持向量机的直流电源蓄电池组容量预测模型。实验结果表明,研究方法能够显著提升直流电源蓄电池组容量预测的精度和收敛性能,确保预测结果的准确性。
文摘为提高卫星星座网络受到攻击后的抗毁性及工作能力,提出了一种模拟退火狼群算法。该算法利用主客观权重法结合综合逼近理想排序法(TOPSIS:Technique for Order Preference by Similarity to Ideal Solution)对网络中的节点进行重要度评估,并按照节点重要度排序依次攻击。以网络连通度与网络连通效率为优化目标,卫星星座网络通信限制为约束条件,采用运动算子的思想实现狼群自适应步长的游走、召唤和围攻。使用通过优化得出的加边方案对网络结构进行优化。实验表明,与其他优化算法相比,该算法具有优越性,解决了卫星星座网络在受到攻击后工作能力下降的问题,提高了其受到攻击后的抗毁性。
