基于最小二乘支持向量机对偶优化问题的核偏最小二乘

提出了一种基于对偶优化的核最小二乘(KPLS)方法,把KPLS用最小二乘支持向量机的形式表示.推导了KPLS对偶优化形式的公式,且使其具有最小二乘支持向量机的风格.在初始空间中构造优化问题,应用核技术在特征空间中解对偶问题,这种解与非线性的KPLS具有相似性.实验验证了这种方法的效果,表明了该方法的有效性和优越性.     

PLS-SVM模型在LF精炼炉温度预报中的应用

通过对LF精炼炉炼钢工艺的研究,结合目前比较先进的统计方法,总结出将PLS(偏最小二乘)和SVM(支持向量机)相结合的方法并应用于LF精炼炉温度预报。实际应用中取得了很好的预报结果。     

SVM在齿轮小样本故障诊断中的应用

将SVM的分类算法应用于齿轮小样本故障诊断中。选取识别能力好的时域无量纲指标和频域中的9段频谱融合作为支持向量机的特征矢量,对齿轮的三种典型故障进行分类,结果表明:SVM在解决小样本情况下的机械故障诊断的分类问题中具有良好的应用前景。     

基于小波分析的LS-SVM—ARIMA组合模型的黄金价格预测

黄金作为一种特殊的金融商品,其价格受国际原油、美元汇率、通货膨胀等多种因素的影响,波动性强。使用单一模型进行黄金价格预测通常效果不佳,只有充分考虑价格变化的各个方面才能更加准确地预测黄金价格。应用小波分析将黄金价格分解为4个不同变化趋势,应用LS-SVM与ARIMA模型对不同变化趋势进行建模预测,并重构黄金价格组合预测的结果。实证结果表明,该组合模型预测精度比单一模型预测精度高。     

基于LS-SVM的氧化铝粉流量软测量建模

针对电解铝厂生产过程中氧化铝输送流量无法在线精确计量问题,应用最小二乘支持向量机回归估计方法,建立了氧化铝输送中氧化铝粉流量的软测量模型,并采用实际数据进行仿真.仿真结果表明,该预测模型的估计值与实际分析值吻合较好,从而验证了软测量技术对氧化铝粉流量准确估算的有效性.     

基于支持向量机的连铸板坯表面温度预测

提出了一种最小二乘支持向量机的连铸板坯表面温度预测新模型.以中间罐温度、拉速、二冷水量等主要工艺因素为输入,连铸坯表面温度为输出,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.以现场采集的连铸生产工艺数据为样本对模型进行学习训练,用训练好的模型预测在一定工艺条件下板坯的表面温度.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,而且性能优于标准支持向量机预测模型.     

基于LS-SVM的粘结NdFeB永磁体磁性能预测

基于粘结NdFeB永磁体制备工艺优化实验,建立了一个最小二乘支持向量机(LS- SVM)算法模型用于工艺参数的优化.以粘结剂含量、固化温度、固化时间以及单位压制力大小四个工艺参数为影响因数,以剩余磁感应强度Br、矫顽力Hcj;和最大磁能积(BH)m为影响对象,通过最小二乘支持向量机算法模型建立起影响因素与影响对象之间的复杂的非线形关系.针对多影响对象,提出了一种γ和σ选择算法;以均匀设计试验结果为样本进行训练,用训练好的模型进行预测.结果表明,LS - SVM模型的实验结果与预测结果吻合良好,二者相对误差很小,对比ANN模型预测结果,LS - SVM模型具有更高的精度和运算速度,具有很好的实用性.     

基于KPLS与SVM的热连轧板凸度预测

热连轧作为典型的流程工业过程,具有多变量、强耦合、过程非线性的特点,轧制机理非常复杂。针对传统方法难以获得准确的数学模型从而导致板形质量预测精度较低的问题,采用基于数据驱动的核偏最小二乘 (KPLS) 方法以有效处理工艺参数和质量指标之间的非线性关系,以此为基础,建立了基于KPLS结合支持向量机(SVM)的板凸度预测模型,并采用粒子群优化算法 (PSO) 优化支持向量机参数,进一步提高热连轧板凸度预测精度。预测结果表明,96.86%的板凸度预测值绝对误差小于5.5 μm,整体具有较高的预测精度,对实现板形质量精确控制、提高热轧产品质量具有重要意义。     

钢铁企业副产煤气预测及优化调度

针对钢铁企业副产煤气系统产消量频繁波动,不平衡现象比较严重,供需之间的平衡程度对钢铁企业的生产成本、能源消耗情况影响较大,并且钢铁企业中工序、设备繁多,每道工序都涉及多种能源介质的问题,利用HP滤波、支持向量机分类（SVC）、最小二乘支持向量机(LSSVM)和Elman神经网络的特性建立了SVC-HP-ENN-LSSVM模型,并根据用能设备的能源利用特点和预测结果对副产煤气进行优化调度。模型应用表明：所建预测模型对煤气系统的预测平均相对误差小于4%,满足工业生产需要。根据预测结果进行的优化调度解决了煤气系统的不平衡问题,应用于钢铁企业典型工况,主工序可降低10%左右能耗,应用其自备电厂（一年按照330天计算）,可多产蒸汽约104148 t,节能约9998208 kg标煤。     

基于多群体遗传算法的非线性最小二乘估计

由于非线性模型参数估计理论广泛使用的传统牛顿类算法对初值的敏感性,以及简单遗传算法易陷入局部最优的问题,提出了一种多群体遗传算法,它采用多个群体执行遗传算法搜索解,并且能根据各个群体在较少迭代次数中找到的最优解动态调整参数域,提高了遗传算法的性能及搜索到的解是全局最优解的可靠性.实验结果表明:新的算法是一种有效的非线性系统模型参数估计方法.     

地下工程监控时间序列分析方法及应用

根据现场位移监测提出1种工程预测方法。利用现场测量的围岩或支护的位移对未来位移发展趋势作出定量预测。在预测位移的基础上,应用数值方法可以预测支护围岩压力、应力及安全度随时间发展的趋势。这种预测方法可用于岩石工程安全监控、支护设计、施工效果评价及预测。     

高炉煤气发生量时间序列预测模型的开发

采用时间序列预测模型建模方法,包括时间序列模型阶次判定、参数估计、模型检验,对莱钢高炉煤气总发生量进行预测。结果表明,模型预测准确,平均误差为1.8748%,对煤气发生量的短期趋势预报有一定参考价值,能够为制定合理的煤气使用计划提供依据,可提高钢铁企业节能降耗水平。     

Operational Monitoring of Daily Crop Water Requirements at the Regional Scale with Time Series of Satellite Data

This work presents a simple, cost-effective, and operational approach to monitor crop water requirements at the regional scale for water management and monitoring purposes. The recommended Food and Agricultural Organization of the United Nations methodology (FAO-56) calculates crop evapotranspiration using crop-specific coefficients (Kc), which vary according to the crop type, health, and phenological stage. This approach, though widely applied for irrigation planning, cannot always match the appropriate crop coefficient with the actual crop phenological stage and health condition, especially in anomalous situations. Previous research demonstrated that crop coefficients and spectral vegetation indexes are correlated. Recent studies have used this relationship with high-resolution satellite data from different sensors to provide information to irrigation advisory services. However, high-resolution data are not feasible for an operational and routine monitoring of water consumption and needs. This paper tests the usefulness of time series of coarse resolution satellite data such as those collected by the moderate-resolution imaging spectroradiometer (MODIS) sensor, to monitor crop coefficients temporal and spatial variability and therefore crop water needs at the regional scale taking advantage of the peculiar characteristics offered by MODIS in terms of high temporal resolution and preprocessed products availability. The outlined methodology takes into account the actual growing stage of the crops and nearly real-time vegetation variations, overcoming some limitations of the traditional FAO approach while preserving the maximum operability. The analysis was carried out in the South Milan agricultural area on data referring to 2003 and 2004. The results agreed with those of other studies and proved to be able to account for the anomalous conditions of the summer in 2003. These results were then compared with those obtained using the traditional FAO crop coefficient curves built with data collected during field campaigns in the same years in rice fields. Constraints, limitations, and possible uses are discussed.     

A Lengthy Look at the Daily Grind: Time Series Analysis of Events, Mood, Stress, and Satisfaction.

The present study investigated processes by which job stress and satisfaction unfold over time by examining the relations between daily stressful events, mood, and these variables. Using a Web-based daily survey of stressor events, perceived strain, mood, and job satisfaction completed by 14 university workers, 1,060 occasions of data were collected. Transfer function analysis, a multivariate version of time series analysis, was used to examine the data for relationships among the measured variables after factoring out the contaminating influences of serial dependency. Results revealed a contrast effect in which a stressful event associated positively with higher strain on the same day and associated negatively with strain on the following day. Perceived strain increased over the course of a semester for a majority of participants, suggesting that effects of stress build over time. Finally, the data were consistent with the notion that job satisfaction is a distal outcome that is mediated by perceived strain. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

红河州霜降天气年变化趋势预报模式研究

利用红河州12个市县1980～2008 年霜降观测资料和MICAPS 常规资料以及1950～ 2008 赤道中太平洋海温距平资料,运用数理方法分析霜降天气发生的大气环流背景和时空变化规律.结果表明,红河州是云南省霜(或霜冻)天气的多发地区之一,年平均有霜日迭37.5 d,地域分布上由北向南减少,时间分布上主要发生在冬春季节.随着地球变暖的加剧,霜出现频率呈逐渐减少的趋势.应用灰相关度分析方法,通过统计分析,找出气象因子与霜出现频率间的灰关联程度的变化关系,建立了预报方程模式,为开展红河州霜降天气趋势预报工作提供可靠的依据.     

基于改进Shannon伪近邻法研究易滑地层位移变形时序

合理地运用科学的理论方法,研究计算滑移地层的滑移规律并进行有效的预测,一直是亟待解决的岩土工程问题.通过基于Shannon伪近邻法时序分析理论研究易滑岩层变形破坏的演变机理;通过边坡演变的动力学方程组,建立相空间重构,得出显示边坡系统动态特性延迟时间与关联维数的计算公式,并时边坡变形破坏过程进行了实例分析,得到最佳嵌入维数取值,提取和恢复边坡系统原有的规律.在古树屋滑坡位移的外推预测中,模型计算相对误差都控制在2%以内,计算结果接近于实测位移值.工程实践表明,基于该模型的时序预测方法,在边坡位移初始变形和等速变形阶段,能保证95%以上的拟合控制精度.     

地下矿生产日报CAD动态监视与管理系统

本文利用CAD技术建立了地下矿生产日报动态监视系统。该系统采用CAD技术形象直观地监视地下矿生产动态;应用多级模糊层次综合评价模型和灰色预测模型及时利用生产日报信息,迅速评价当天生产总体效果和准确预测未来生产发展状况。     

小流域暴雨洪水计算方法的探讨

结合尾矿库的特点，通过分析水利、市政部门的暴雨洪水计算公式，提出了尾矿库小流域暴雨洪水计算方法。     

两种模型在滚齿机传动误差中预报精度的比较

通过计算机模拟误差补偿,从计算预报误差的时间和精度上对两种模型作了比较。指出滚齿机展成链传动误差预报模型应该是时变参数模型,并提出了提高时变参数模型的预报速度,以便实现误差补偿与控制的措施,得到的结论对传动误差的补偿与控制有实际意义。     

Influence of Loss Model on Design Discharge of Homogeneous Plane

By applying the kinematic wave method to a homogeneous, rectangular overland plane, the influence of the constant and proportional-loss models on the design discharge are examined. The examination shows that with the use of the proportional-loss model, there is no partial-area effect and the design discharge is governed by the full-area contribution. On the other hand, with the use of the constant-loss model, there is no partial-area effect if the loss rate is small. For larger loss rates, there is a partial-area effect; and for this case, the design is complicated, since there is a need to search for the critical storm that governs the partial-area effect. The characteristic of the critical storm is that its rate of decrease in rainfall intensity with duration equals the corresponding rate of increase in the contributing area. The preceding findings are consistent with the design concept in the rational method that uses the proportional-loss model, and the results from earlier studies that used the constant-loss model.