针对不均衡数据分类问题中原有过采样方法在生成样本分布上存在的不足,文章提出改进合成样本分布的加权过采样方法——WKSMOTE(Weighted SMOTE for WKMeans preprocess)。首先,应用聚类算法中的WKMeans算法对原数据集进行预处理,进而划...针对不均衡数据分类问题中原有过采样方法在生成样本分布上存在的不足,文章提出改进合成样本分布的加权过采样方法——WKSMOTE(Weighted SMOTE for WKMeans preprocess)。首先,应用聚类算法中的WKMeans算法对原数据集进行预处理,进而划分少数类样本,使每个样本生成不同数量的新样本;然后,应用SMOTE算法合成新样本,增强决策边界;最后,将过采样后的均衡数据集在随机森林分类器中进行训练。实验结果表明,WKSMOTE方法对不均衡数据集的整体分类性能有一定的提升,验证了方法的有效性。展开更多
【目的】电控离子选择渗透(electrochemically switched ion permselectivity, ESIP)是一种新型的离子选择性膜分离技术,已成功应用于低浓度目标离子的高效、连续、选择性分离。然而,离子在膜内传质不符合Nernst-Planck理论,建立ESIP离...【目的】电控离子选择渗透(electrochemically switched ion permselectivity, ESIP)是一种新型的离子选择性膜分离技术,已成功应用于低浓度目标离子的高效、连续、选择性分离。然而,离子在膜内传质不符合Nernst-Planck理论,建立ESIP离子传质模型有助于人们理解ESIP分离过程。【方法】在ESIP膜分离系统中,为研究离子在膜上双脉冲电势与极室槽电压耦合动态场中的传质行为,提出了修正的Nernst-Planck模型。根据唐南(Donnan)平衡以及电中性假设等,建立了ESIP膜分离过程的离子传递稳态模型。通过数值模拟考察了电流密度、膜厚、膜内离子活性位点浓度对膜分离系统中离子浓度和电阻分布的影响。【结果】在原料侧扩散层和膜相内,膜厚和离子活性位点浓度对离子浓度分布影响较大,降低膜厚、提高离子活性位点浓度是提高离子传质的主要方式。在高电流密度、低膜厚和高离子活性位点浓度下,原料侧扩散层电阻在整体电阻中占主导作用,通过增加流体流速或减小腔室厚度以提高离子传质速率。在低电流密度、较高膜厚下,Donnan层电阻占主导作用,通过增加膜的离子活性位点来提高离子传质速率。【结论】在高电流密度、低膜厚和高离子活性位点浓度下,减弱扩散层电阻(增加流体流速、减少腔室厚度)是实现ESIP性能优化的主要途径。展开更多
Improving the prediction accuracy of wind power is an effective means to reduce the impact of wind power on power grid.Therefore,we proposed an improved African vulture optimization algorithm(AVOA)to realize the predi...Improving the prediction accuracy of wind power is an effective means to reduce the impact of wind power on power grid.Therefore,we proposed an improved African vulture optimization algorithm(AVOA)to realize the prediction model of multi-objective optimization least squares support vector machine(LSSVM).Firstly,the original wind power time series was decomposed into a certain number of intrinsic modal components(IMFs)using variational modal decomposition(VMD).Secondly,random numbers in population initialization were replaced by Tent chaotic mapping,multi-objective LSSVM optimization was introduced by AVOA improved by elitist non-dominated sorting and crowding operator,and then each component was predicted.Finally,Tent multi-objective AVOA-LSSVM(TMOALSSVM)method was used to sum each component to obtain the final prediction result.The simulation results show that the improved AVOA based on Tent chaotic mapping,the improved non-dominated sorting algorithm with elite strategy,and the improved crowding operator are the optimal models for single-objective and multi-objective prediction.Among them,TMOALSSVM model has the smallest average error of stroke power values in four seasons,which are 0.0694,0.0545 and 0.0211,respectively.The average value of DS statistics in the four seasons is 0.9902,and the statistical value is the largest.The proposed model effectively predicts four seasons of wind power values on lateral and longitudinal precision,and faster and more accurately finds the optimal solution on the current solution space sets,which proves that the method has a certain scientific significance in the development of wind power prediction technology.展开更多
电控离子交换(Electrochemically switched ion exchange,ESIX)系统内对电极具有保持溶液电中性、增强提锂效果且使系统形成闭合回路的关键作用。在ESIX技术盐湖提锂过程中人们主要关注锂离子捕获电极,关于对电极的研究较少。而本文研...电控离子交换(Electrochemically switched ion exchange,ESIX)系统内对电极具有保持溶液电中性、增强提锂效果且使系统形成闭合回路的关键作用。在ESIX技术盐湖提锂过程中人们主要关注锂离子捕获电极,关于对电极的研究较少。而本文研究了不同类型对电极对ESIX系统提锂性能的影响。分别采用聚吡咯/导电炭黑/聚偏二氟乙烯(PPy/C/PVDF)、活性炭/导电炭黑/聚偏二氟乙烯(AC/C/PVDF)和石墨板电极作为ESIX系统中锰酸锂/导电炭黑/聚偏二氟乙烯(LiMn_(2)O_(4)/C/PVDF)提锂膜电极的对电极,考察了这3种ESIX系统在氯化物型高镁锂比模拟卤水(Mg/Li~50)中的提锂性能。结果表明,当PPy/C/PVDF作为对电极时可有效吸附卤水中Cl^(-),且ESIX系统提锂性能最优,Li^(+)吸附量为13.9 mg/g;当PPy/C/PVDF电极湿膜厚度增加至1 mm时,ESIX系统对Li^(+)的提取率可达44.2%,Li^(+)/Mg^(2+)分离因子可达56.82。因此,针对不同的阴离子型盐湖卤水设计匹配的对电极对ESIX技术在盐湖提锂领域的发展具有重要的理论指导意义。展开更多
文摘针对不均衡数据分类问题中原有过采样方法在生成样本分布上存在的不足,文章提出改进合成样本分布的加权过采样方法——WKSMOTE(Weighted SMOTE for WKMeans preprocess)。首先,应用聚类算法中的WKMeans算法对原数据集进行预处理,进而划分少数类样本,使每个样本生成不同数量的新样本;然后,应用SMOTE算法合成新样本,增强决策边界;最后,将过采样后的均衡数据集在随机森林分类器中进行训练。实验结果表明,WKSMOTE方法对不均衡数据集的整体分类性能有一定的提升,验证了方法的有效性。
文摘【目的】电控离子选择渗透(electrochemically switched ion permselectivity, ESIP)是一种新型的离子选择性膜分离技术,已成功应用于低浓度目标离子的高效、连续、选择性分离。然而,离子在膜内传质不符合Nernst-Planck理论,建立ESIP离子传质模型有助于人们理解ESIP分离过程。【方法】在ESIP膜分离系统中,为研究离子在膜上双脉冲电势与极室槽电压耦合动态场中的传质行为,提出了修正的Nernst-Planck模型。根据唐南(Donnan)平衡以及电中性假设等,建立了ESIP膜分离过程的离子传递稳态模型。通过数值模拟考察了电流密度、膜厚、膜内离子活性位点浓度对膜分离系统中离子浓度和电阻分布的影响。【结果】在原料侧扩散层和膜相内,膜厚和离子活性位点浓度对离子浓度分布影响较大,降低膜厚、提高离子活性位点浓度是提高离子传质的主要方式。在高电流密度、低膜厚和高离子活性位点浓度下,原料侧扩散层电阻在整体电阻中占主导作用,通过增加流体流速或减小腔室厚度以提高离子传质速率。在低电流密度、较高膜厚下,Donnan层电阻占主导作用,通过增加膜的离子活性位点来提高离子传质速率。【结论】在高电流密度、低膜厚和高离子活性位点浓度下,减弱扩散层电阻(增加流体流速、减少腔室厚度)是实现ESIP性能优化的主要途径。
基金supported by National Natural Science Foundation of China(Nos.61662042,62062049)Science and Technology Plan of Gansu Province(Nos.21JR7RA288,21JR7RE174).
文摘Improving the prediction accuracy of wind power is an effective means to reduce the impact of wind power on power grid.Therefore,we proposed an improved African vulture optimization algorithm(AVOA)to realize the prediction model of multi-objective optimization least squares support vector machine(LSSVM).Firstly,the original wind power time series was decomposed into a certain number of intrinsic modal components(IMFs)using variational modal decomposition(VMD).Secondly,random numbers in population initialization were replaced by Tent chaotic mapping,multi-objective LSSVM optimization was introduced by AVOA improved by elitist non-dominated sorting and crowding operator,and then each component was predicted.Finally,Tent multi-objective AVOA-LSSVM(TMOALSSVM)method was used to sum each component to obtain the final prediction result.The simulation results show that the improved AVOA based on Tent chaotic mapping,the improved non-dominated sorting algorithm with elite strategy,and the improved crowding operator are the optimal models for single-objective and multi-objective prediction.Among them,TMOALSSVM model has the smallest average error of stroke power values in four seasons,which are 0.0694,0.0545 and 0.0211,respectively.The average value of DS statistics in the four seasons is 0.9902,and the statistical value is the largest.The proposed model effectively predicts four seasons of wind power values on lateral and longitudinal precision,and faster and more accurately finds the optimal solution on the current solution space sets,which proves that the method has a certain scientific significance in the development of wind power prediction technology.
