期刊文献+
任意字段
题名或关键词
题名
关键词
摘要
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息
共找到736篇文章
< 1 2 … 37 >
每页显示 20 50 100
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
显示方式：
Parallel Expectation-Maximization Algorithm for Large Databases 认领 引用
1
作者 黄浩 宋瀚涛 陆玉昌 《Journal of Beijing Institute of Technology》 EI CAS 2006年第4期420-424,共5页
A new parallel expectation-maximization （EM） algorithm is proposed for large databases. The purpose of the algorithm is to accelerate the operation of the EM algorithm. As a well-known algorithm for estimation in ge... A new parallel expectation-maximization （EM） algorithm is proposed for large databases. The purpose of the algorithm is to accelerate the operation of the EM algorithm. As a well-known algorithm for estimation in generic statistical problems, the EM algorithm has been widely used in many domains. But it often requires significant computational resources. So it is needed to develop more elaborate methods to adapt the databases to a large number of records or large dimensionality. The parallel EM algorithm is based on partial Esteps which has the standard convergence guarantee of EM. The algorithm utilizes fully the advantage of parallel computation. It was confirmed that the algorithm obtains about 2.6 speedups in contrast with the standard EM algorithm through its application to large databases. The running time will decrease near linearly when the number of processors increasing. 展开更多
关键词 expectation-maximization （EM） algorithm incremental EM lazy EM parallel EM
暂未订购 下载PDF
Mining Initial Nodes with BSIS Model and BS-G Algorithm on Social Networks for Influence Maximization 认领 引用
2
作者 Xiaoheng Deng Dejuan Cao +2 位作者 Yan Pan Hailan Shen Fang Long 《国际计算机前沿大会会议论文集》 EI 2017年第2期33-35,共3页
Influence maximization is the problem to identify and find a set of the most influential nodes, whose aggregated influence in the network is maximized. This research is of great application value for advertising,viral... Influence maximization is the problem to identify and find a set of the most influential nodes, whose aggregated influence in the network is maximized. This research is of great application value for advertising,viral marketing and public opinion monitoring. However, we always ignore the tendency of nodes' behaviors and sentiment in the researches of influence maximization. On general, users' sentiment determines users behaviors, and users' behaviors reflect the influence between users in social network. In this paper, we design a training model of sentimental words to expand the existing sentimental dictionary with the marked-commentdata set, and propose an influence spread model considering both the tendency of users' behaviors and sentiment named as BSIS (Behavior and Sentiment Influence Spread) to depict and compute the influence between nodes. We also propose an algorithm for influence maximization named as BS-G (BSIS with Greedy Algorithm) to select the initial node. In the experiments, we use two real social network data sets on the Hadoop and Spark distributed cluster platform for experiments, and the experiment results show that BSIS model and BS-G algorithm on big data platform have better influence spread effects and higher quality of the selection of seed node comparing with the approaches with traditional IC, LT and CDNF models. 展开更多
关键词 Social networks Influence maximization Behavior tendency Sentiment tendency Greedy algorithm
暂未订购 下载PDF
AN ITERATIVE ALGORITHM FOR MAXIMAL MONOTONE MULTIVALUED OPERATOR EQUATIONS 认领 引用 被引量：1
3
作者 Xiao Jinsheng Sun Lelin 《Acta Mathematica Scientia》 SCIE 2001年第2期152-158,共7页
A proximal iterative algorithm for the mulitivalue operator equation 0∈T(x)is presented,where T is a maximal monotone operator.It is an improvement of the proximal point algorithm as well know.The convergence of the ... A proximal iterative algorithm for the mulitivalue operator equation 0∈T(x)is presented,where T is a maximal monotone operator.It is an improvement of the proximal point algorithm as well know.The convergence of the algorithm is discussed and all example is given. 展开更多
关键词 Iterative algorithm maximal monotone operator multivalued operator
暂未订购 下载PDF
Application of k-person and k-task maximal efficiency assignment algorithm to water piping repair 认领 引用
4
作者 Su-juan ZHENG Xiu-ming YU Li-qing CAO 《Water Science and Engineering》 CAS 2009年第2期98-104,共7页
Solving the absent assignment problem of the shortest time limit in a weighted bipartite graph with the minimal weighted k-matching algorithm is unsuitable for situations in which large numbers of problems need to be ... Solving the absent assignment problem of the shortest time limit in a weighted bipartite graph with the minimal weighted k-matching algorithm is unsuitable for situations in which large numbers of problems need to be addressed by large numbers of parties. This paper simplifies the algorithm of searching for the even alternating path that contains a maximal element using the minimal weighted k-matching theorem and intercept graph. A program for solving the maximal efficiency assignment problem was compiled. As a case study, the program was used to solve the assignment problem of water piping repair in the case of a large number of companies and broken pipes, and the validity of the program was verified. 展开更多
关键词 graph theory maximal efficiency assignment problem minimal weighted k-matching algorithm intercept graph even alternating path water piping repair
暂未订购 下载PDF
MODIFIED APPROXIMATE PROXIMAL POINT ALGORITHMS FOR FINDING ROOTS OF MAXIMAL MONOTONE OPERATORS 认领 引用
5
作者 曾六川 《Applied Mathematics(A Journal of Chinese Universities)》 2004年第3期293-301,共9页
In order to find roots of maximal monotone operators, this paper introduces and studies the modified approximate proximal point algorithm with an error sequence {e k} such that || ek || \leqslant hk || xk - [(x)ilde]k... In order to find roots of maximal monotone operators, this paper introduces and studies the modified approximate proximal point algorithm with an error sequence {e k} such that || ek || \leqslant hk || xk - [(x)ilde]k ||\left\| { e^k } ight\| \leqslant \eta _k \left\| { x^k - ilde x^k } ight\| with ?k = 0￥ ( hk - 1 ) < + ￥\sum\limits_{k = 0}^\infty {\left( {\eta _k - 1} ight)} and infk \geqslant 0 hk = m\geqslant 1\mathop {\inf }\limits_{k \geqslant 0} \eta _k = \mu \geqslant 1 . Here, the restrictions on {η k} are very different from the ones on {η k}, given by He et al (Science in China Ser. A, 2002, 32 (11): 1026–1032.) that supk \geqslant 0 hk = v < 1\mathop {\sup }\limits_{k \geqslant 0} \eta _k = v . Moreover, the characteristic conditions of the convergence of the modified approximate proximal point algorithm are presented by virtue of the new technique very different from the ones given by He et al. 展开更多
关键词 modified approximate proximal point algorithm maximal monotone operator convergence
暂未订购 下载PDF
Influence Maximization for Cascade Model with Diffusion Decay in Social Networks 认领 引用
6
作者 Zhijian Zhang Hong Wu +2 位作者 Kun Yue Jin Li Weiyi Liu 《国际计算机前沿大会会议论文集》 EI 2016年第1期106-108,共3页
Maximizing the spread of influence is to select a set of seeds with specified size to maximize the spread of influence under a certain diffusion model in a social network. In the actual spread process, the activated p... Maximizing the spread of influence is to select a set of seeds with specified size to maximize the spread of influence under a certain diffusion model in a social network. In the actual spread process, the activated probability of node increases with its newly increasing activated neighbors, which also decreases with time. In this paper, we focus on the problem that selects k seeds based on the cascade model with diffusion decay to maximize the spread of influence in social networks. First, we extend the independent cascade model to incorporate the diffusion decay factor, called as the cascade model with diffusion decay and abbreviated as CMDD. Then, we discuss the objective function of maximizing the spread of influence under the CMDD, which is NP-hard. We further prove the monotonicity and submodularity of this objective function. Finally, we use the greedy algorithm to approximate the optimal result with the ration of 1 ? 1/e. 展开更多
关键词 Social networks Influence maximization Cascade model Diffusion decay Submodularity Greedy algorithm
暂未订购 下载PDF
基于麻雀搜索算法优化TPA-LSTM的火电厂NOx排放预测 认领 引用 被引量：5
7
作者 金秀章 张瑾 陈佳政 《控制工程》 CSCD 北大核心 2026年第6期1035-1043,共9页
针对燃煤机组状态多变导致选择性催化还原(selective catalytic reduction,SCR)入口NOx浓度大范围波动的问题,提出了一种基于麻雀搜索算法(sparrow search algorithm,SSA)优化时序模式注意力机制长短期记忆(temporal pattern attenti... 针对燃煤机组状态多变导致选择性催化还原(selective catalytic reduction,SCR)入口NOx浓度大范围波动的问题,提出了一种基于麻雀搜索算法(sparrow search algorithm,SSA)优化时序模式注意力机制长短期记忆(temporal pattern attention mechanism long short-term memory,TPA-LSTM)神经网络的预测模型。首先,通过NOx生成机理分析出与其相关的辅助变量;然后,利用套索(least absolute shrinkage and selection operator,LASSO)算法筛选出与其相关度最高的几组辅助变量,通过最大信息系数(maximal information coefficient,MIC)计算各辅助变量与NOx浓度之间的延迟时间,使用包含辅助变量和迟延时间的信息作为模型的输入;最后,通过SSA优化TPA-LSTM神经网络的超参数,建立NOx排放TPA-LSTM神经网络预测模型。仿真结果表明,加入TPA机制的LSTM神经网络预测模型的性能明显优于传统的LSTM神经网络,证明了所提模型的有效性。 展开更多
关键词 麻雀搜索算法 时序模式注意力机制 辅助变量 套索算法 最大信息系数
暂未订购 下载PDF
步进随机振动下电连接器微动磨损试验及性能退化模型 认领 引用 被引量：1
8
作者 骆燕燕 祁侨绅 +1 位作者 王永鹏 武雄伟 《北京航空航天大学学报》 EI CAS CSCD 北大核心 2026年第7期2293-2302,共10页
针对电连接器工作时受步进随机振动作用,产生微动磨损而接触性能降低的问题,开展步进应力随机振动试验,采用电容层析成像(ECT)技术检测微动磨损过程中电连接器接触件间磨屑特征值,通过接触电阻与磨屑特征值研究步进应力随机振动条件下... 针对电连接器工作时受步进随机振动作用,产生微动磨损而接触性能降低的问题,开展步进应力随机振动试验,采用电容层析成像(ECT)技术检测微动磨损过程中电连接器接触件间磨屑特征值,通过接触电阻与磨屑特征值研究步进应力随机振动条件下接触件的磨损程度及接触性能的退化规律。引入具有鲁棒性好、可以表征非线性关系的最大互信息系数(MIC)进行磨屑特征值与接触电阻的相关性分析,通过MIC筛选降维以提高模型预测精度。结果表明:步进应力随机振动下磨屑特征值、磨屑特征值总量和接触电阻均呈阶梯状变化趋势;通过MIC计算发现磨屑特征值总量与接触电阻强相关;能谱分析的结果与试验结果相吻合;采用MIC筛选优化的CHIOElman的性能退化模型的平均绝对误差百分比小于4%。 展开更多
关键词 电连接器 电容层析成像 微动磨损 最大互信息系数 冠状病毒群体免疫优化算法
暂未订购 下载PDF
基于双高斯分布混合的可解释自适应鲁棒神经网络建模方法 认领 引用
9
作者 刘鑫 李琪琪 代伟 《自动化学报》 EI CAS CSCD 北大核心 2026年第3期463-480,共18页
工业过程数据常常受到混合噪声干扰,传统基于单一重尾分布的鲁棒建模方法在处理混合噪声问题时,在准确性与可解释性方面均存在一定局限.基于此,提出一种混合双高斯分布的可解释鲁棒自适应建模方法.该方法首先采用随机配置算法构建基础... 工业过程数据常常受到混合噪声干扰,传统基于单一重尾分布的鲁棒建模方法在处理混合噪声问题时,在准确性与可解释性方面均存在一定局限.基于此,提出一种混合双高斯分布的可解释鲁棒自适应建模方法.该方法首先采用随机配置算法构建基础的随机配置网络学习模型,确定模型的隐含层节点数、输入权重和偏置;其次为保证模型对混合噪声的鲁棒性,构建双高斯分布(一大一小方差)加权组合而成的噪声表征模型;随后利用期望最大化算法自适应迭代学习随机配置网络输出权值和混合高斯模型噪声参数,最终形成基于双高斯分布混合鲁棒建模方法.该方法具有以下优势:噪声模型能够通过参数自适应学习逼近实际混合噪声特性,其中大方差高斯分量负责对异常噪声进行粗调,小方差高斯分量则用于精细拟合主体噪声,从而增强模型的可解释性;在网络模型输出权值估计过程中,通过为每个输出数据点自适应分配惩罚权重,保障模型的鲁棒性能.为验证所提方法的有效性,分别在函数仿真、基准数据集和工业实例上设计多组对比实验,结果均表明所提方法具备良好的可靠性与实用性. 展开更多
关键词 随机配置网络 双高斯分布混合 鲁棒建模方法 期望最大化算法
暂未订购 下载PDF
基于模糊最大覆盖模型的无人机应急配送中心选址研究 认领 引用
10
作者 万莉莉 徐舒梦 +2 位作者 黄嘉慧 张庆阳 袁振宇 《交通运输系统工程与信息》 EI CSCD 北大核心 2026年第3期166-175,共10页
针对突发灾害救援中物资需求及无人机覆盖半径的不确定问题,本文提出一种基于模糊理论的无人机应急配送中心选址优化方法。基于地理数据,利用k-means算法识别需求点及候选设施位置。采用三角与梯形模糊数刻画参数不确定性,引入可信度约... 针对突发灾害救援中物资需求及无人机覆盖半径的不确定问题,本文提出一种基于模糊理论的无人机应急配送中心选址优化方法。基于地理数据,利用k-means算法识别需求点及候选设施位置。采用三角与梯形模糊数刻画参数不确定性,引入可信度约束,构建以覆盖需求量最大、总成本最小和空间公平性最优为目标的模糊最大覆盖选址模型(FMCLP)。设计嵌入模糊模拟的混合模拟退火算法,利用蒙特卡洛采样处理模糊参数,通过局部搜索与自适应冷却机制实现全局寻优。以南京市江宁区为例进行对比实验和灵敏度分析。结果表明:相较于经典确定性模型,该方案在同等设施规模下覆盖需求量提升82个单位,总成本降低6.14万元,最大未覆盖距离缩减7.63 km,且在设施失效时具有更优的鲁棒性;确定覆盖需求量、总成本与公平性的最优权重组合为(0.7,0.2,0.1),并识别出区域核心枢纽设施。研究结果验证了模型在复杂不确定环境下的适用性,可为城市无人机应急物流网络规划提供科学决策依据。 展开更多
关键词 航空运输 设施选址 模糊最大覆盖模型 无人机(UAV) 应急物流 模拟退火算法
暂未订购 下载PDF
基于EM算法的幂-均匀混合分布参数估计 认领 引用
11
作者 赵志文 苑洋 杨凯 《沈阳师范大学学报（自然科学版）》 CAS 2026年第1期81-89,共9页
对于有偏态长尾和均匀分散混合特征的数据来说,单一的幂分布或均匀分布很难对此类数据进行拟合,因而构建幂-均匀混合分布,该混合分布的期望、方差等数字特征与单一的幂分布或均匀分布不同,能够较好地刻画偏态长尾与均匀分散共存这一数... 对于有偏态长尾和均匀分散混合特征的数据来说,单一的幂分布或均匀分布很难对此类数据进行拟合,因而构建幂-均匀混合分布,该混合分布的期望、方差等数字特征与单一的幂分布或均匀分布不同,能够较好地刻画偏态长尾与均匀分散共存这一数据特征。基于期望极大化(expectation-maximization,EM)算法,利用极大似然估计方法对模型参数进行估计,并通过数值模拟实验验证了有限样本下估计方法的可行性。此外,将此混合模型应用在实际数据的建模拟合中,与单一分布的拟合效果进行比较,结果显示所提出的混合模型具有更小的拟合偏差。 展开更多
关键词 幂分布 均匀分布 混合模型 极大似然估计 期望极大化算法
暂未订购 下载PDF
基于TAN-EM的在役桥梁事故风险致因分析 认领 引用
12
作者 申建红 郭明慧 +1 位作者 王涵 王硕 《哈尔滨商业大学学报（自然科学版）》 CAS 2026年第4期480-488,共9页
随着我国桥梁逐步进入老龄化阶段,在役桥梁发生事故的频率不断上升,识别关键风险因素,确保我国在役桥梁的运营安全,对于我国交通基础设施建设具有重要意义.收集了1999~2024年发生的149例在役桥梁事故数据,以客观数据为研究基础,减少了... 随着我国桥梁逐步进入老龄化阶段,在役桥梁发生事故的频率不断上升,识别关键风险因素,确保我国在役桥梁的运营安全,对于我国交通基础设施建设具有重要意义.收集了1999~2024年发生的149例在役桥梁事故数据,以客观数据为研究基础,减少了专家打分造成的主观性.对数据进行处理与风险因素识别.构建了树增强朴素贝叶斯网络(Tree-Augmented Naive Bayes,TAN)模型,突破传统朴素贝叶斯的强独立性假设,显著提升风险识别精度.引入EM(Expectation-Maximization Algorithm,EM)算法进行参数估计并对模型进行优化,解决缺失数据下参数估计偏差问题.利用贝叶斯网络正向推理及反向推理功能,对各类事故的风险因素进行分析,从中挖掘影响在役桥梁事故的关键风险因素,为桥梁安全管理和维护提供科学依据. 展开更多
关键词 在役桥梁事故 风险致因 树增强朴素贝叶斯网络 EM算法 机器学习 桥梁安全
暂未订购 下载PDF
基于简化概率选择框架的双足机器人模仿学习 认领 引用
13
作者 薛雯 赵硕 李永强 《浙江大学学报（工学版）》 EI CAS CSCD 北大核心 2026年第5期1071-1081,共11页
专家数据未显式满足马尔可夫性质会限制模仿学习方法的有效性,为此提出基于简化概率选择框架的分层模仿学习方法.通过保留选项变量并去除终止变量,构建紧凑的策略建模框架.在优化过程中,结合期望最大化算法进行隐变量建模,引入拉格朗日... 专家数据未显式满足马尔可夫性质会限制模仿学习方法的有效性,为此提出基于简化概率选择框架的分层模仿学习方法.通过保留选项变量并去除终止变量,构建紧凑的策略建模框架.在优化过程中,结合期望最大化算法进行隐变量建模,引入拉格朗日乘子法进行约束条件处理(如策略归一性).在多个典型连续动作控制任务中开展仿真实验,对比不同模仿学习方法的训练性能.结果表明,所提方法在非马尔可夫条件下训练过程更稳定、策略收敛性更佳.将该模仿学习模型应用于双足机器人仿真,实现了机器人稳定的前向行走,验证了简化概率选择框架的可行性与有效性. 展开更多
关键词 双足机器人 模仿学习 隐变量建模 期望最大化算法 拉格朗日优化
暂未订购 下载PDF
Novel method for extraction of ship target with overlaps in SAR image via EM algorithm 认领 引用 被引量：2
14
作者 CAO Rui WANG Yong 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第4期874-887,共14页
The quality of synthetic aperture radar(SAR)image degrades in the case of multiple imaging projection planes(IPPs)and multiple overlapping ship targets,and then the performance of target classification and recognition... The quality of synthetic aperture radar(SAR)image degrades in the case of multiple imaging projection planes(IPPs)and multiple overlapping ship targets,and then the performance of target classification and recognition can be influenced.For addressing this issue,a method for extracting ship targets with overlaps via the expectation maximization(EM)algorithm is pro-posed.First,the scatterers of ship targets are obtained via the target detection technique.Then,the EM algorithm is applied to extract the scatterers of a single ship target with a single IPP.Afterwards,a novel image amplitude estimation approach is pro-posed,with which the radar image of a single target with a sin-gle IPP can be generated.The proposed method can accom-plish IPP selection and targets separation in the image domain,which can improve the image quality and reserve the target information most possibly.Results of simulated and real mea-sured data demonstrate the effectiveness of the proposed method. 展开更多
关键词 expectation maximization(EM)algorithm image processing imaging projection plane(IPP) overlapping ship tar-get synthetic aperture radar(SAR)
暂未订购 下载PDF
Parameter Estimation of RBF-AR Model Based on the EM-EKF Algorithm 认领 引用 被引量：6
15
作者 Yanhui Xi Hui Peng Hong Mo 《自动化学报》 EI CAS CSCD 北大核心 2017年第9期1636-1643,共8页
RBF-AR （radial basis function network-based autoregressive） model is reconstructed as a new type of general radial basis function （RBF） neural network, which has additional linear output weight layer in comparison... RBF-AR （radial basis function network-based autoregressive） model is reconstructed as a new type of general radial basis function （RBF） neural network, which has additional linear output weight layer in comparison with the traditional three-layer RBF network. The extended Kalman filter （EKF） algorithm for RBF training has low filtering accuracy and divergence because of unknown prior knowledge, such as noise covariance and initial states. To overcome the drawback, the expectation maximization （EM） algorithm is used to estimate the covariance matrices of noises and the initial states. The proposed method, called the EM-EKF （expectation-maximization extended Kalman filter） algorithm, which combines the expectation maximization, extended Kalman filtering and smoothing process, is developed to estimate the parameters of the RBF-AR model, the initial conditions and the noise variances simultaneously. It is shown by the simulation tests that the EM-EKF method for the reconstructed RBF-AR network provides better results than structured nonlinear parameter optimization method （SNPOM） and the EKF, especially in low SNR （signal noise ratio）. Moreover, the EM-EKF method can accurately estimate the noise variance. F test indicates there is significant difference between results obtained by the SNPOM and the EM-EKF. 展开更多
关键词 Expectation maximization （EM） algorithm, extended Kalman filtering （EKF） and smoothing, radial basis function（RBF） neural network, RBF-AR model
暂未订购 下载PDF
基于伽马过程的异总体退化数据分析 认领 引用
16
作者 宋锴 《数理统计与管理》 CSSCI 北大核心 2026年第3期518-526,共9页
在工程实践中,生产批次、工作环境等因素可能会导致所收集的退化数据具有异总体特性。本文建立了一种基于伽马过程的随机效应模型来分析异总体退化数据,其中,随机效应参数服从混合伽马分布。在此基础上,给出了产品可靠性函数的显式表达... 在工程实践中,生产批次、工作环境等因素可能会导致所收集的退化数据具有异总体特性。本文建立了一种基于伽马过程的随机效应模型来分析异总体退化数据,其中,随机效应参数服从混合伽马分布。在此基础上,给出了产品可靠性函数的显式表达式,并提出了基于期望最大化算法的参数估计方法。随后,开展了模拟研究,并将所提模型与方法应用于疲劳裂纹数据。结果表明,该模型表现良好,且估计方法是有效的。 展开更多
关键词 期望最大化算法 伽马过程 异总体 随机效应 可靠性
暂未订购 下载PDF
Deterministic streaming algorithms for non-monotone submodular maximization 认领 引用
17
作者 Xiaoming SUN Jialin ZHANG Shuo ZHANG 《Frontiers of Computer Science》 SCIE EI CSCD 2025年第6期103-114,共12页
Submodular maximization is a significant area of interest in combinatorial optimization.It has various real-world applications.In recent years,streaming algorithms for submodular maximization have gained attention,all... Submodular maximization is a significant area of interest in combinatorial optimization.It has various real-world applications.In recent years,streaming algorithms for submodular maximization have gained attention,allowing realtime processing of large data sets by examining each piece of data only once.However,most of the current state-of-the-art algorithms are only applicable to monotone submodular maximization.There are still significant gaps in the approximation ratios between monotone and non-monotone objective functions.In this paper,we propose a streaming algorithm framework for non-monotone submodular maximization and use this framework to design deterministic streaming algorithms for the d-knapsack constraint and the knapsack constraint.Our 1-pass streaming algorithm for the d-knapsack constraint has a 1/4(d+1)-∈approximation ratio,using O(BlogB/∈)memory,and O(logB/∈)query time per element,where B=MIN(n,b)is the maximum number of elements that the knapsack can store.As a special case of the d-knapsack constraint,we have the 1-pass streaming algorithm with a 1/8-∈approximation ratio to the knapsack constraint.To our knowledge,there is currently no streaming algorithm for this constraint when the objective function is non-monotone,even when d=1.In addition,we propose a multi-pass streaming algorithm with 1/6-∈approximation,which stores O(B)elements. 展开更多
关键词 submodular maximization streaming algorithms cardinality constraint knapsack constraint
暂未订购 下载PDF
新能源基地直流外送系统多时间尺度鲁棒协同优化调度 认领 引用
18
作者 王启玺 韩自奋 +1 位作者 刘克权 董海鹰 《综合智慧能源》 CAS 2026年第4期47-59,共13页
针对风电、光伏出力不稳定给直流外送系统带来的调度问题,提出一种融合多时间尺度优化及自适应鲁棒优化的风光火储直协同优化调度方法。以经济效益、环境效益、系统效益及灵活性等综合效益最大化为目标,以功率平衡、储能荷电状态等为约... 针对风电、光伏出力不稳定给直流外送系统带来的调度问题,提出一种融合多时间尺度优化及自适应鲁棒优化的风光火储直协同优化调度方法。以经济效益、环境效益、系统效益及灵活性等综合效益最大化为目标,以功率平衡、储能荷电状态等为约束,建立风光火储直的两阶段协同优化调度模型。在日前计划阶段,建立目标函数及约束条件,采用非支配排序遗传算法Ⅱ求解该多目标问题。在日内滚动优化阶段,通过构建描述风光出力不确定性的偏差集合,采用min-max鲁棒优化及列与约束生成算法进行求解,实现极端情况下外送功率能够满足中长期直流外送计划。仿真表明,所提策略在场景4下综合成本最低,较场景1降低约7%;中长期外送功率波动幅度降低30%以上;日内滚动优化后,外送功率跟踪误差在2%以内,鲁棒优化模型在最坏情景下仍能获得满足硬性约束的全局最优解。策略在新能源基地直流外送系统中可以实现综合效益最大化的目标,确保实时外送功率能够紧密跟踪中长期外送计划,且所述鲁棒优化模型在考虑最坏情景的不确定性场景时,仍能获得满足硬性约束的全局最优解。 展开更多
关键词 新能源 直流外送系统 多时间尺度 综合效益最大化 非支配排序遗传算法Ⅱ 自适应鲁棒优化 列与约束生成算法
暂未订购 下载PDF
A utility-optimal backoff algorithm for wireless sensor networks 认领 引用
19
作者 廖盛斌 杨宗凯 +1 位作者 程文青 刘威 《Journal of Central South University》 SCIE EI CAS 2009年第4期635-639,共5页
A novel backoff algorithm in CSMA/CA-based medium access control (MAC) protocols for clustered sensor networks was proposed. The algorithm requires that all sensor nodes have the same value of contention window (CW) i... A novel backoff algorithm in CSMA/CA-based medium access control (MAC) protocols for clustered sensor networks was proposed. The algorithm requires that all sensor nodes have the same value of contention window (CW) in a cluster, which is revealed by formulating resource allocation as a network utility maximization problem. Then, by maximizing the total network utility with constrains of minimizing collision probability, the optimal value of CW (Wopt) can be computed according to the number of sensor nodes. The new backoff algorithm uses the common optimal value Wopt and leads to fewer collisions than binary exponential backoff algorithm. The simulation results show that the proposed algorithm outperforms standard 802.11 DCF and S-MAC in average collision times, packet delay, total energy consumption, and system throughput. 展开更多
关键词 wireless sensor networks network utility maximization backoff algorithm collision probability
暂未订购 下载PDF
AN ANT COLONY ALGORITHM FOR MINIMUM UNSATISFIABLE CORE EXTRACTION 认领 引用 被引量：1
20
作者 Zhang Jianmin Shen Shengyu Li Sikun 《Journal of Electronics(China)》 2008年第5期652-660,共9页
Explaining the causes of infeasibility of Boolean formulas has many practical applications in electronic design automation and formal verification of hardware.Furthermore,a minimum explanation of infeasibility that ex... Explaining the causes of infeasibility of Boolean formulas has many practical applications in electronic design automation and formal verification of hardware.Furthermore,a minimum explanation of infeasibility that excludes all irrelevant information is generally of interest.A smallest-cardinality unsatisfiable subset called a minimum unsatisfiable core can provide a succinct explanation of infea-sibility and is valuable for applications.However,little attention has been concentrated on extraction of minimum unsatisfiable core.In this paper,the relationship between maximal satisfiability and mini-mum unsatisfiability is presented and proved,then an efficient ant colony algorithm is proposed to derive an exact or nearly exact minimum unsatisfiable core based on the relationship.Finally,ex-perimental results on practical benchmarks compared with the best known approach are reported,and the results show that the ant colony algorithm strongly outperforms the best previous algorithm. 展开更多
关键词 Electronic Design Automation （EDA） Formal verification of hardware Minimum unsatisfiable core Ant colony algorithm Maximal satisfiable subformula
暂未订购 下载PDF
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
上一页 1 2 … 37 下一页 到第 页
在线咨询 使用帮助 返回顶部 意见反馈