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Power Quality Disturbance Classification Method Based on Wavelet Transform and SVM Multi-class Algorithms 被引量:1
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作者 Xiao Fei 《Energy and Power Engineering》 2013年第4期561-565,共5页
The accurate identification and classification of various power quality disturbances are keys to ensuring high-quality electrical energy. In this study, the statistical characteristics of the disturbance signal of wav... The accurate identification and classification of various power quality disturbances are keys to ensuring high-quality electrical energy. In this study, the statistical characteristics of the disturbance signal of wavelet transform coefficients and wavelet transform energy distribution constitute feature vectors. These vectors are then trained and tested using SVM multi-class algorithms. Experimental results demonstrate that the SVM multi-class algorithms, which use the Gaussian radial basis function, exponential radial basis function, and hyperbolic tangent function as basis functions, are suitable methods for power quality disturbance classification. 展开更多
关键词 Power Quality DISTURBANCE classification WAVELET TRANSFORM SVM MULTI-class algorithmS
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Study and Implementation of Web Mining Classification Algorithm Based on Building Tree of Detection Class Threshold
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作者 陈俊杰 宋瀚涛 陆玉昌 《Journal of Beijing Institute of Technology》 EI CAS 2005年第2期126-129,共4页
A new classification algorithm for web mining is proposed on the basis of general classification algorithm for data mining in order to implement personalized information services. The building tree method of detecting... A new classification algorithm for web mining is proposed on the basis of general classification algorithm for data mining in order to implement personalized information services. The building tree method of detecting class threshold is used for construction of decision tree according to the concept of user expectation so as to find classification rules in different layers. Compared with the traditional C4.5 algorithm, the disadvantage of excessive adaptation in C4.5 has been improved so that classification results not only have much higher accuracy but also statistic meaning. 展开更多
关键词 data mining classification algorithm class threshold induced concept
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CRITERIA OF FINITE ELEMFNT ALGORITHM FOR A CLASS OF PARABOLIC EQUATION
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作者 欧阳华江 肖丁 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 1989年第12期1179-1185,共7页
In finite element analysis of transient temperature field, it is quite notorious that the numerical solution may quite likely oscillate and/or exceed the reasonable scope, which violates the natural law of heat conduc... In finite element analysis of transient temperature field, it is quite notorious that the numerical solution may quite likely oscillate and/or exceed the reasonable scope, which violates the natural law of heat conduction. For this reason, we put forward the concept of lime monotony and spatial monotony, and then derive several sufficient conditions for nionotonic solutions in lime dimension for 3-D passive heal conduction equations with a group of finite difference schemes. For some special boundary conditions and regular element meshes, the lower and upper bounds for can be obtained from those conditions so that reasonable numerical solutions are guaranteed. Spatial monotony is also discussed. Finally, the lumped mass method is analyzed.We creatively give several new criteria for the finite element solutions of a class of parabolic equation represented by heal conduction equation. 展开更多
关键词 CRITERIA OF FINITE ELEMFNT algorithm FOR A class OF PARABOLIC EQUATION
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ON ITERATIVE ALGORITHMS FOR A CLASS OF NONLINEAR VARIATIONAL INEQUALITIES
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作者 M. A. Moor 《Analysis in Theory and Applications》 1995年第3期95-105,共11页
In this paper we use the auxiliary principle technique to suggest and analyze novel and innovative iterative algorithms for a class of nonlinear variational inequalities. Several special cases, which can be obtained f... In this paper we use the auxiliary principle technique to suggest and analyze novel and innovative iterative algorithms for a class of nonlinear variational inequalities. Several special cases, which can be obtained from our main results, are also discussed. 展开更多
关键词 ON ITERATIVE algorithmS FOR A class OF NONLINEAR VARIATIONAL INEQUALITIES
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Application of Dijkstra Algorithm to Proposed Tramway of a Potential World Class University
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作者 M. C. Agarana N. C. Omoregbe M. O. Ogunpeju 《Applied Mathematics》 2016年第6期496-503,共8页
Nowadays, the development of “smart cities” with a high level of quality of life is becoming a prior challenge to be addressed. In this paper, promoting the model shift in railway transportation using tram network t... Nowadays, the development of “smart cities” with a high level of quality of life is becoming a prior challenge to be addressed. In this paper, promoting the model shift in railway transportation using tram network towards more reliable, greener and in general more sustainable transportation modes in a potential world class university is proposed. “Smart mobility” in a smart city will significantly contribute to achieving the goal of a university becoming a world class university. In order to have a regular and reliable rail system on campus, we optimize the route among major stations on campus, using shortest path problem Dijkstra algorithm in conjunction with a computer software called LINDO to arrive at the optimal route. In particular, it is observed that the shortest path from the main entrance gate (Canaan land entrance gate) to the Electrical Engineering Department is of distance 0.805 km. 展开更多
关键词 Potential World class University OPTIMIZATION Dijkstra algorithm Shortest Path Tramway
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A GASVM Algorithm for Predicting Protein Structure Classes
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作者 Longlong Liu Mingjiao Ma Tingting Zhao 《Journal of Computer and Communications》 2016年第15期46-53,共8页
The research methods of protein structure prediction mainly focus on finding effective features of protein sequences and developing suitable machine learning algorithms. But few people consider the importance of weigh... The research methods of protein structure prediction mainly focus on finding effective features of protein sequences and developing suitable machine learning algorithms. But few people consider the importance of weights of features in classification. We propose the GASVM algorithm (classification accuracy of support vector machine is regarded as the fitness value of genetic algorithm) to optimize the coefficients of these 16 features (5 features are proposed first time) in the classification, and further develop a new feature vector. Finally, based on the new feature vector, this paper uses support vector machine and 10-fold cross-validation to classify the protein structure of 3 low similarity datasets (25PDB, 1189, FC699). Experimental results show that the overall classification accuracy of the new method is better than other methods. 展开更多
关键词 Protein Structural classes Protein Secondary Structure Genetic algorithm Support Vector Machine
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基于遗传神经网络的入侵检测系统ONE-CLASS分类器设计
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作者 戴月 陈波 吴坚 《微计算机信息》 2011年第7期194-195,71,共3页
为适应高速网络中的数据处理速度,设计了将识别出的正常数据抛弃的入侵检测系统one-class分类器。检测模块采用GA与BP相结合的智能算法。该算法利用神经网络自身具有并行性、鲁棒性等特点,可以大大减少分类器的计算时间。
关键词 入侵检测系统分类器 遗传算法 BP神经网络
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Learning Bayesian networks using genetic algorithm 被引量:3
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作者 Chen Fei Wang Xiufeng Rao Yimei 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2007年第1期142-147,共6页
A new method to evaluate the fitness of the Bayesian networks according to the observed data is provided. The main advantage of this criterion is that it is suitable for both the complete and incomplete cases while th... A new method to evaluate the fitness of the Bayesian networks according to the observed data is provided. The main advantage of this criterion is that it is suitable for both the complete and incomplete cases while the others not. Moreover it facilitates the computation greatly. In order to reduce the search space, the notation of equivalent class proposed by David Chickering is adopted. Instead of using the method directly, the novel criterion, variable ordering, and equivalent class are combined,moreover the proposed mthod avoids some problems caused by the previous one. Later, the genetic algorithm which allows global convergence, lack in the most of the methods searching for Bayesian network is applied to search for a good model in thisspace. To speed up the convergence, the genetic algorithm is combined with the greedy algorithm. Finally, the simulation shows the validity of the proposed approach. 展开更多
关键词 Bayesian networks Genetic algorithm Structure learning Equivalent class
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基于EPC Class-1 Gen-2标准的防冲突算法与改进 被引量:1
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作者 张瑞子 南琳 +1 位作者 胡琨元 田景贺 《计算机工程》 CAS CSCD 北大核心 2009年第2期24-26,共3页
针对RFID读写器识别多标签过程中出现的冲突问题,研究并实现了EPC Class-1 Gen-2标准中的防冲突算法,即时隙随机算法(SR算法),同时针对SR算法的不足提出改进算法。改进算法采用不避让冲突时隙的处理方式,降低了由时隙的随机选取所导致... 针对RFID读写器识别多标签过程中出现的冲突问题,研究并实现了EPC Class-1 Gen-2标准中的防冲突算法,即时隙随机算法(SR算法),同时针对SR算法的不足提出改进算法。改进算法采用不避让冲突时隙的处理方式,降低了由时隙的随机选取所导致的标签间冲突的概率。实验结果证明,改进后的算法在通信次数和吞吐率方面均优于原算法,有效提高标签识别效率。 展开更多
关键词 防冲突 EPC class-1 Gen-2标准 ALOHA算法 标签识别
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融合连续域蚁群算法One-Class SVM的电力离群用户检测
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作者 郭玮 《国外电子测量技术》 2020年第6期148-154,共7页
连续域蚁群优化算法是蚁群优化算法的主要研究方向。通过分析蚁群觅食过程中的位置分布与食物来源之间的关系,提出了蚁群一类支持向量机(One-Class SVM)算法。在此算法的基础上,设计了一种电力离群用户检测算法,给出了算法的求解形式,... 连续域蚁群优化算法是蚁群优化算法的主要研究方向。通过分析蚁群觅食过程中的位置分布与食物来源之间的关系,提出了蚁群一类支持向量机(One-Class SVM)算法。在此算法的基础上,设计了一种电力离群用户检测算法,给出了算法的求解形式,根据高维用电负荷数据的特点,提出了一种基于改进One-Class SVM算法的电力离群用户检测方法,同时采用蚁群算法对支持向量机的训练参数进行优化,可以在样本分布不均匀、样本分布未知的环境下有效识别电力离群用户,并对其他算法的测试结果进行了比较和分析,以验证所提出算法的正确性和有效性。 展开更多
关键词 蚁群算法 ONE-class SVM 离群检测 电力离群
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AUTOMATIC FAST CLASSIFICATION OF PRODUCT-IMAGES WITH CLASS-SPECIFIC DESCRIPTOR 被引量:1
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作者 Jia Shijie Kong Xiangwei Jin Guang 《Journal of Electronics(China)》 2010年第6期808-814,共7页
To achieve online automatic classification of product is a great need of e-commerce de-velopment. By analyzing the characteristics of product images, we proposed a fast supervised image classifier which is based on cl... To achieve online automatic classification of product is a great need of e-commerce de-velopment. By analyzing the characteristics of product images, we proposed a fast supervised image classifier which is based on class-specific Pyramid Histogram Of Words (PHOW) descriptor and Im-age-to-Class distance (PHOW/I2C). In the training phase, the local features are densely sampled and represented as soft-voting PHOW descriptors, and then the class-specific descriptors are built with the means and variances of distribution of each visual word in each labelled class. For online testing, the normalized chi-square distance is calculated between the descriptor of query image and each class-specific descriptor. The class label corresponding to the least I2C distance is taken as the final winner. Experiments demonstrate the effectiveness and quickness of our method in the tasks of product clas-sification. 展开更多
关键词 class-specific descriptor Fast classification algorithm Product image
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基于Bagging算法构造强分类器的one class SVM导线舞动预测应用 被引量:6
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作者 程永锋 汉京善 +2 位作者 刘彬 李鹏 姬昆鹏 《振动与冲击》 EI CSCD 北大核心 2020年第9期152-158,共7页
考虑到传统物理分析方法无法解决导线舞动的预测问题,综合运用机器学习算法,对已有的舞动历史数据进行筛选和预处理,并挖掘有效信息,利用one class SVM算法解决舞动数据中负样本缺失问题,采用集成学习算法中Bagging算法建立分类器学习方... 考虑到传统物理分析方法无法解决导线舞动的预测问题,综合运用机器学习算法,对已有的舞动历史数据进行筛选和预处理,并挖掘有效信息,利用one class SVM算法解决舞动数据中负样本缺失问题,采用集成学习算法中Bagging算法建立分类器学习方法,实现了数据的随机抽样,分成不同组数据集进行相互独立的训练,避免对舞动数据过拟合,提升机器学习算法的抗噪声能力以及泛化能力,采用k折交叉验证算法进行模型的验证,并利用F1-score描述导线舞动预警模型的性能,验证了该方法在舞动预测方面的有效性。 展开更多
关键词 导线舞动 机器学习 ONE class SVM 集成学习 BAGGING算法 F1-score
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阶级、结构与《资本论》范畴学——马克思工资理论探析 被引量:1
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作者 许光伟 《河北经贸大学学报》 CSSCI 北大核心 2024年第3期20-30,共11页
《资本论》工资由主体论所规定:工资不仅是外在的壳——工资形式,也是内在的瓤——针对资本的批判,突出阶级关系当事人对于工艺者的系统支配性。《资本论》范畴学取决于经济理论的两面性:“资本的政治经济学”和“劳动的政治经济学”。... 《资本论》工资由主体论所规定:工资不仅是外在的壳——工资形式,也是内在的瓤——针对资本的批判,突出阶级关系当事人对于工艺者的系统支配性。《资本论》范畴学取决于经济理论的两面性:“资本的政治经济学”和“劳动的政治经济学”。工资既是资本的经济结果,也是资本的统治前提。马克思抓住“资本工资”这个论证中心,工资一般的理解维度据此定格为“阶级—统治—剥削—拜物教”这一模式。由于马克思的理论努力,《资本论》实质性提出了“马克思主义的工资范畴学”,作为两重统一的规定性:算法工资(主体范畴)与雇佣工资(经济范畴)的统一以及阶级工资(劳动力社会价格)与市场工资(劳动力市场价格)的统一。《资本论》工资的系统实现论从中得以确认。一旦从资产者的权利意识的束缚中走出,“工资拜物教”即被瓦解,围绕生活资料安排的系统规划将替代对工资收入水平的单一追求。 展开更多
关键词 马克思工资理论 主体 阶级 算法工资 雇佣工资
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基于因素空间理论的扫类连环多分类算法
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作者 曾繁慧 王莹 +1 位作者 汪培庄 孙慧 《辽宁工程技术大学学报(自然科学版)》 CAS 北大核心 2024年第1期111-118,共8页
为解决多分类问题,基于因素空间理论中因素显隐的思想,在扫类连环分类算法基础上,定义类别的合并,提出因素显隐的合并扫类连环分类方法,给出算法步骤,并用数值算例进行分析;定义类别的两两组合,提出因素显隐的两两扫类连环分类方法,给... 为解决多分类问题,基于因素空间理论中因素显隐的思想,在扫类连环分类算法基础上,定义类别的合并,提出因素显隐的合并扫类连环分类方法,给出算法步骤,并用数值算例进行分析;定义类别的两两组合,提出因素显隐的两两扫类连环分类方法,给出算法步骤,并用数值算例进行分析。提出采用因素显隐的差额绝对值方法解决两个算法执行过程中出现的决策类别分不开的问题;对UCI数据集中3个实例与支持向量机作了算法对比分析,研究结果表明:提出的合并扫类连环分类方法、两两扫类连环分类方法实现了因素显隐,分类算法的精确度优于支持向量机。多分类学习的因素显隐研究结论拓展了因素空间的理论及应用研究。 展开更多
关键词 因素空间 因素显隐 扫类连环分类算法 合并扫类连环分类算法 两两扫类连环分类算法 差额绝对值法
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基于改进人工蜂群算法的高校自动排课问题的研究
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作者 赵广复 李凯 《长江信息通信》 2024年第7期162-164,168,共4页
为了解决人工蜂群算法在排课问题上无法跳出局部最优的问题,提出一种基于混沌算法的混合人工蜂群算法(HABC算法)。HABC算法在寻优过程中重视食物源对蜂群的影响,增加邻近区域内对新食物的最优求解,利用两个进化因子来加快算法寻优的速度... 为了解决人工蜂群算法在排课问题上无法跳出局部最优的问题,提出一种基于混沌算法的混合人工蜂群算法(HABC算法)。HABC算法在寻优过程中重视食物源对蜂群的影响,增加邻近区域内对新食物的最优求解,利用两个进化因子来加快算法寻优的速度,在观察蜂后期利用混沌算法防止陷入局部最优。根据高校实际排课约束情况,构建数学模型。应用结果表明,混合人工蜂群算法与传统的人工蜂群算法相比,在相同条件下进行自动排课测试,HABC算法在寻优性能和收敛速度上都有显著的优势。 展开更多
关键词 人工蜂群算法 排课 混沌算法 HABC算法
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L^p CONTINUITY OF HRMANDER SYMBOL OPERATORS OpS_(0,0) ~m AND NUMERICAL ALGORITHM
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作者 杨奇祥 《Acta Mathematica Scientia》 SCIE CSCD 2011年第4期1517-1534,共18页
If we use Littlewood-Paley decomposition, there is no pseudo-orthogonality for Ho¨rmander symbol operators OpS m 0 , 0 , which is different to the case S m ρ,δ (0 ≤δ 〈 ρ≤ 1). In this paper, we use a spec... If we use Littlewood-Paley decomposition, there is no pseudo-orthogonality for Ho¨rmander symbol operators OpS m 0 , 0 , which is different to the case S m ρ,δ (0 ≤δ 〈 ρ≤ 1). In this paper, we use a special numerical algorithm based on wavelets to study the L p continuity of non infinite smooth operators OpS m 0 , 0 ; in fact, we apply first special wavelets to symbol to get special basic operators, then we regroup all the special basic operators at given scale and prove that such scale operator’s continuity decreases very fast, we sum such scale operators and a symbol operator can be approached by very good compact operators. By correlation of basic operators, we get very exact pseudo-orthogonality and also L 2 → L 2 continuity for scale operators. By considering the influence region of scale operator, we get H 1 (= F 0 , 2 1 ) → L 1 continuity and L ∞→ BMO continuity. By interpolation theorem, we get also L p (= F 0 , 2 p ) → L p continuity for 1 〈 p 〈 ∞ . Our results are sharp for F 0 , 2 p → L p continuity when 1 ≤ p ≤ 2, that is to say, we find out the exact order of derivations for which the symbols can ensure the resulting operators to be bounded on these spaces. 展开更多
关键词 Ho¨rmander symbol class wavelet and numerical algorithm basic operators and scale operators approximation by compact operator and operator’s continuity
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改进的采样算法与无监督聚类相结合的软件缺陷预测模型
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作者 石海鹤 周世文 +1 位作者 钟林辉 肖正兴 《江西师范大学学报(自然科学版)》 CAS 北大核心 2024年第3期301-310,共10页
该文首先在自适应综合过采样算法ADASYN(adaptive synthetic sampling)的基础上,考虑少数类内部不同密度簇之间的连接性问题,将与采样点距离为中等的点纳入新样本生成范围,改进得到T-ADASYN过采样优化算法,有效地增加了少数类内部不同... 该文首先在自适应综合过采样算法ADASYN(adaptive synthetic sampling)的基础上,考虑少数类内部不同密度簇之间的连接性问题,将与采样点距离为中等的点纳入新样本生成范围,改进得到T-ADASYN过采样优化算法,有效地增加了少数类内部不同密度簇的连接性,生成了分布更为均衡的数据集.然后使用基于连接的spectral clustering算法进行聚类预测操作,将过采样算法和无监督聚类相结合,提出一种新型实用的软件缺陷预测模型TA-SC(T-ADASYN+spectral clustering).以F-score为评价指标,spectral clustering为聚类模型进行验证.实验结果表明:改进的T-ADASYN过采样算法在公开的PROMISE数据集和NASA数据集上比常用的过采样算法均有6%的性能提升,且TA-SC模型在PROMISE和NASA 2个数据集上比常用聚类算法分别有3%和2%的性能提升. 展开更多
关键词 软件缺陷预测 类别不平衡 过采样算法 聚类算法 无监督学习
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面向不平衡类的联邦学习客户端智能选择算法
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作者 朱素霞 王云梦 +1 位作者 颜培森 孙广路 《哈尔滨理工大学学报》 CAS 北大核心 2024年第2期33-42,共10页
在联邦学习应用场景下,若客户端设备之间的数据呈现非独立同分布特征,甚至出现类不平衡的情况时,客户端本地模型的优化目标将偏离全局优化目标,从而给全局模型的性能带来巨大挑战。为解决这种数据异质性带来的挑战,通过积极选择合适的... 在联邦学习应用场景下,若客户端设备之间的数据呈现非独立同分布特征,甚至出现类不平衡的情况时,客户端本地模型的优化目标将偏离全局优化目标,从而给全局模型的性能带来巨大挑战。为解决这种数据异质性带来的挑战,通过积极选择合适的客户端子集以平衡数据分布将有助于提高模型的性能。因此,设计了一种面向不平衡类的联邦学习客户端智能选择算法—FedSIMT。该算法不借助任何辅助数据集,在保证客户端本地数据对服务器端不可见的隐私前提下,使用Tanimoto系数度量本地数据分布与目标分布之间的差异,采用强化学习领域中的组合多臂老虎机模型平衡客户端设备选择的开发和探索,在不同数据异质性类型下提高了全局模型的准确率和收敛速度。实验结果表明,该算法具有有效性。 展开更多
关键词 联邦学习 类不平衡 客户端选择算法 多臂老虎机
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基于单类支持向量机的组合导航容错算法
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作者 孙传波 王虹 +1 位作者 杨然 余国才 《电光与控制》 CSCD 北大核心 2024年第5期30-33,107,共5页
提出了一种基于单类支持向量机(OCSVM)的组合导航容错算法。针对组合导航系统中子系统出现故障会影响整个导航系统精度的问题,采用基于单类支持向量机的方法,对故障进行检测和隔离,并对容错性能进行分析。仿真结果表明:在应用基于单类... 提出了一种基于单类支持向量机(OCSVM)的组合导航容错算法。针对组合导航系统中子系统出现故障会影响整个导航系统精度的问题,采用基于单类支持向量机的方法,对故障进行检测和隔离,并对容错性能进行分析。仿真结果表明:在应用基于单类支持向量机的容错算法后,系统的故障检测模块可以有效地隔离故障数据,降低了多源组合导航系统的位置误差,其可靠性和稳定性也得到了提高。 展开更多
关键词 组合导航 容错算法 单类支持向量机
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多能微电网多场景多重不确定性鲁棒优化调度
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作者 陆霞 张萍 《舰船电子工程》 2024年第8期121-127,共7页
多能微电网中的不确定因素使得系统的运行调度面临严峻的挑战,同时传统的典型日或季节已无法满足当前的运行需求。论文通过拉丁超立方场景生成和k-均值聚类消减法,离散风光出力和负荷并生成多种场景和概率。依据相关变量的调节特性,在... 多能微电网中的不确定因素使得系统的运行调度面临严峻的挑战,同时传统的典型日或季节已无法满足当前的运行需求。论文通过拉丁超立方场景生成和k-均值聚类消减法,离散风光出力和负荷并生成多种场景和概率。依据相关变量的调节特性,在建模过程中充分考虑多场景下源荷和概率的不确定性,构建了电热氢多能微电网多场景多重不确定性鲁棒优化(Robust Optimization,RO)调度模型。通过不确定集合有效约束每一场景下的源荷出力和场景概率,结合C&CG算法、KKT等效条件和大M法解耦并提高求解速度,得到多场景多重不确定下的最恶劣场景的运行调度结果,结合算例验证了该模型的有效性。 展开更多
关键词 不确定性 RO调度 多能微电网 C&CG算法
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