Results 11 to 20 of about 480 (135)
Gaoya dianqi, 2008 考虑到气象因子条件对绝缘子的等值附盐密度影响复杂,难以建立精确数学模型等问题,提出了一种最小二乘支持向量机的绝缘子在一定的气象因子条件下的等值附盐密度预测新模型。以温度、湿度、风速等主要气象因子为输入,绝缘子等值附盐密度为输出,通过最小二乘支持向量机模型,拟合输入与输出之间的复杂非线性函数关系。以现场采集的气候数据为样本对模型进行学习训练,用训练好模型预测绝缘子在一定气候条件下的等值附盐密度。实践表明该方法具有建模速度快、预测精度高、操作简便等优点,不仅克服了常规的BP预测模型的不足 ...
舒服华, 张望祥
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Gaoya dianqi, 2015 为了快速、准确地对高压断路器发生的故障进行分析和诊断,确定故障的性质、类别和部位,提出了一种高压断路器故障诊断的新方法。首先对高压断路器分合闸线圈电流进行分析,提取电流和时间特征量形成特征向量,然后用遗传算法对最小二乘支持向量机（least square support vector machine,LS-SVM）参数进行优化,最后,将特征向量输入到优化后的最小二乘支持向量机中进行故障识别、分类。试验表明,该方法可以准确地识别断路器的多种故障类型,为断路器故障定位和状态检修提供了依据 ...
张卫正, 李永丽, 姚创
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Gaoya dianqi, 2013 污秽等级评定方法是绝缘子泄漏电流在线监测系统的重要研究内容,等值附盐密度是确定污秽等级的唯一依据,而泄漏电流与绝缘子表面污秽状况密切相关。笔者采用最小二乘支持向量机（LS-SVM）方法,建立以泄漏电流有效值、泄漏电流峰值、脉冲电流次数、环境湿度、温度5个变量作为输入参数,ESDD作为输出参数的智能预测模型。实验结果表明,该方法有效、模型预测精度高,能实现绝缘子表面污秽程度在线评估。
史丽萍, 祝艳华, 朱宁坦
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Study on Multi-Objective Optimization of High-Efficiency and Low-NOx Emissions of Power Station Boilers Based on Least Squares Support Vector Machines [PDF]
, 2023 Aiming at the multi-objective optimization of boiler combustion system, on the basis of the established prediction model of boiler combustion system, the weighted-particle swarm algorithm and the multi-objective particle swarm optimization (MOPSO ...
GAN Yunhua +5 more
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Prediction and Comparison of Ash Fusion Temperatures Based on BP Neural Network and Least Squares Support Vector Machine [PDF]
, 2022 To predict the slagging on heating surface of coal-fired boilers, BP neural network (BPNN) and least squares support vector machine (LSSVM) prediction models were established to predict ash fusion temperature, deformation temperature (DT) and softening ...
LIU Yanpeng, SHI Hao, XIAO Haiping
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Zhejiang Daxue xuebao. Lixue ban, 2022 房价预测、共享单车出租数量预测、空气污染情况预测等常涉及矛盾方程组求解，对其数值求解方法研究具有重要的理论意义与应用价值。当矛盾方程组规模过大时，用传统的最小二乘法求解，不仅计算量大，而且由于误差积累使最终结果的准确性不高。鉴于此，采用机器学习中的最小二乘支持向量机（least squares support vector machine，LS-SVM）算法求解大规模矛盾方程组，并分别针对线性、非线性、单变量、多变量矛盾方程组进行了数值求解。数值结果表明，数据类型和数据量的变化对结果的影响不大 ...
ZHENGSupei(郑素佩) +3 more
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Forecasting the All-Weather Short-Term Metro Passenger Flow Based on Seasonal and Nonlinear LSSVM [PDF]
, 2021 Accurate metro ridership prediction can guide passengers in efficiently selecting their departure time and simultaneously help traffic operators develop a passenger organization strategy.
Huang, Xin +4 more
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Classifier of silicon content in hot metal based on support vector machines(基于支持向量机的高炉铁水硅含量多类别分类)
Zhejiang Daxue xuebao. Lixue ban, 2007 支持向量机是基于统计学习理论发展而来的一种机器学习算法，本文介绍了非线性软间隔分类机、最小二乘分类机和加权最小二乘分类机的算法.以山东莱钢1号高炉在线采集数据作为应用案例，使用C-均值算法对[Si]做聚类分析将其分成5类，改进M-ary分类方法实现对铁水硅质量分数[Si]的多类别分类，并对各分类机的性能作出评价.
JIANLing(渐令) +2 more
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Semiparametric estimation of SVM in frameable RKHS(标架型RKHS中的SVM的半参数估计)
Zhejiang Daxue xuebao. Lixue ban, 2008 在基于标架型的再生核希尔伯特空间中，研究了SVM算法下，解的对偶形式和原形式之间的关系，进而将SVM算法与最小二乘法相结合，讨论了支持向量机的半参数估计.
ZHOUDe-qiang(周德强)
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Study on upper limb joint angle prediction method based on sEMG
Xibei Gongye Daxue Xuebao, 2022 Aiming at the problems of insufficient human-computer interaction and human-machine coupling in the rehabilitation training process, a prediction model of upper limb joint angle is proposed and verified by experiments.
KONG Dezhi +3 more
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