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高考分数线是广大考生和家长关注的问题,准确预测高考分数线对填报志愿和决策分析都是必要的。本文采用变权重组合预测模型预测重庆市文科二批次高考分数线,该模型通过把单项预测模型进行组合分析,以误差平方和最小为准则,求出最优加权组合系数,建立组合预测模型。通过实例分析,表明其预测精度高于各单项模型预测值,在分数预测中有一定的应用价值。 相似文献
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变权重组合预测模型的研究 总被引：24，自引：0，他引：24
变权重组合预测模型的研究周传世，刘永清（广东商学院）（华南理工大学）１引言组合预测的研究是现在预测方法领域中研究得最为活跃的一个领域之一，但在变权重组合预测方面的研究还没有多大的进展。变权重组合预测模型的建立与应用是提高预测模型的拟合精度和预测精度、... 相似文献
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【目的/意义】自然界中时间序列信号具有非线性、非稳定变化的特点。对时间序列信号实现准确预测,不
仅能够提高风电机组的输出功率,并且有助于调控风电场的运行维护,保障电力系统的安全运行。【方法/过程】本
文基于集合经验模式分解和变分模态分解两种时间序列分解的方法,并将其与RBF神经网络相结合提出RBF直
接预测模型和EEMD-RBF 和VMD-RBF 两种组合预测模型。利用某风电场的原始风速时间序列信息,通过
MATLAB 软件进行编程,进行案例分析。【结果/结论】预测结果表明组合预测模型优于RBF 直接预测模型,且
VMD-RBF组合预测模型的预测结果最为精确。 相似文献
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选取2002-2010年宁波市港口集装箱吞吐量数据,分别建立灰色预测模型与三次指数平滑模型,在两种模型基础上进行加权组合,建立科学的组合预测模型,并对"十二五"规划期间2011-2015年宁波港集装箱吞吐量进行预测。分析结果表明:组合模型的高精度预测可以对今后一个时期宁波港口发展和改革的战略以及可持续发展的建港提供思路。 相似文献
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组合预测方法中的权重算法及应用 总被引：10，自引：0，他引：10
系统地分析了组合预测模型的权重确定方法,并估计各种权重的理论精度,以此指导其应用。文章还首次提出用主成分分析确定组合模型权重的方法,最后以短期(1年)负荷预测为例,检验各种权重下组合预测模型的精度。 相似文献
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【目的/意义】针对多组时间序列的海量数据集和以预测为目标的信息分析方法，提出了基于数据挖掘技术 的预测模型，在大数据环境下，提高了预测精度，以期在其他领域的信息分析和情报预测能有所借鉴。【方法/过程】 以集装箱海运价格预测为例，提出集装箱海运价格预测模型，设计自适应的网格搜索策略，高效准确地确定数据挖 掘算法中的超参数组合，提出基于时间序列留出法的评估方法，降低了集装箱运价这种多组时间序列数据集在数 据挖掘结果上的泛化误差，针对海量运价信息，对GBDT算法进行并行计算设计和预排序后的损失函数迭代计算 优化策略，提高了算法在大数据环境下的计算效率。【结果/结论】模型和算法运行结果仿真显示：对于传统的时间 序列问题，基于数据挖掘方法的预测模型取得了比传统时间序列方法更优的结果。 相似文献
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组合预测理论与建模技术对于信息不完备的复杂经济系统有一定的实用性,鉴于房地产价格的复杂性和非线性的特征,利用成都房地产价格的历史数据,分别采用改进的灰色预测模型、RBF神经网络模型建立了成都房地产价格的单项预测模型,并对单项预测模型的优缺点进行了比较分析。采用标准差法进行权重分配,将两个模型进行组合,建立了成都房地产价格的组合预测模型。运用该模型对成都未来5年的房地产价格进行了预测。 相似文献
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该文对原始AIS轨迹数据进行了重建、压缩和预测。首先是数据重建,将部分原始数据的位置信息可视化,筛选异常值,之后分别利用了三次样条插值和埃尔米特型插值构建丢失数据及异常点。其次是数据压缩,主要运用Douglas-Peucker算法,结合压缩质量和压缩率,选取最优的压缩阈值。最后是数据预测,该文主要运用了时间序列分析中的指数平滑模型、ARIMA模型分别预测。 相似文献
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《Journal of The Franklin Institute》2019,356(16):9344-9363
In the present study, a novel technique is suggested for the adaptive non-linear model predictive control based on the fuzzy approach in three stages. In the presented approach, in the first stage, the prediction and control horizons are obtained from a fuzzy system in each control step. Another fuzzy system is employed to determine the weight factors before the optimization stage of developing new controller. The proposed controller gives the parameters of the model predictive control (MPC) in each control step in order to improve the performance of nonlinear systems. The proposed control scheme is compared with the traditional MPC and Generic Model Control for controlling MED-TVC process. The performances of the three proposed controllers have been investigated in the absence and presence of disturbance in order to evaluate the stability and robustness of the proposed controllers. The results reveal that the novel adaptive controller based on fuzzy approach performs better than the two other controllers in set-point tracking and disturbance rejection with lower IAE criteria. In addition, the average computational time for the adaptive MPC exhibits a decline of 34% in comparison with the traditional MPC. 相似文献
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【目的/意义】网络社会充斥大量负面网络舆情,负面网络舆情风险分级和研判对提高网络治理能力和网络
社会治理成效意义重大。【方法/过程】构建负面网络舆情风险指标体系,并采用熵权法计算风险指标权重;基于加
权GRA模型计算灰色加权信息关联度,在此基础上,运用k-means聚类算法构建负面网络舆情风险分级方案,据此
对负面网络舆情进行风险预测。【结果/结论】实证分析结果表明,所建负面网络舆情风险分级模型客观性强、可靠
度高,可为负面网络舆情风险精准响应提供有效决策依据。【创新/局限】以信息关联为视角,为负面网络舆情风险
分级与预测提供了新的研究框架,但典型案例数据库有待继续完善。 相似文献
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The conventional interacting multiple model (IMM) algorithm will increase the computational load when applying a large number of models, meanwhile, it cannot yield accurate estimation results with a small number of models. Furthermore, the unknown target acceleration is regarded as an additional process noise to the target model, and its time-varying variance is hard to be approximated. The paper proposes a fuzzy-logic adaptive variable structure multiple model (FAVSMM) algorithm for tracking a high maneuvering target. The algorithm can optimize the model parameters using the model probability and construct an optimal model set quickly, and the fuzzy-logic IMM algorithm included in the FAVSMM algorithm is adopted for states estimation. The simulation results show that the proposed algorithm can match well with the actual target trajectory with less computational complexity and better accuracy. 相似文献
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We use the principle of minimum cross entropy (MCE) to build a non-parametric adaptive algorithm for smoothing the log-transformed periodogram, and construct an optimal estimate for the spectral density function of a process. We show that this estimate minimizes the cross-entropy with the log-transformed spectral density function of the process. The method is non-parametric and performs very well for the case of processes having rapidly changing spectra that exhibits a variable order of smoothness. The algorithm is locally based on linearly approximating the information present in the process, and uses this approximation to allow the bandwidth of the spectral window in the smoothed log-periodogram to vary. We extend the algorithm empirically for better application to processes having mixed, narrow-band spectra. Comparisons with other currently used procedures are performed through the means of simulated examples. 相似文献
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提出基于空间平滑技术的高阶累积量空间谱估计。在经典的空间谱估计中,均利用信号的二阶统计量,并且假设噪声是白噪声。在实际应用场合,噪声通常是色噪声,这时采用高阶统计量可以获得比二阶矩更理想的性能。本文利用空间平滑技术对单一的高阶累积量算法进行改进。新算法具有同时测向能力、测向精度高、超分辨能力,能在低信噪比环境中取得好的性能。计算机仿真证明了该方法的有效性。 相似文献
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《Journal of The Franklin Institute》2022,359(16):8497-8521
In order to improve the response speed and control precision of the braking system with parameters uncertainty and nonlinear friction, a braking-by-wire system based on the electromagnetic direct-drive valve and a novel cascade control algorithm was proposed in this paper. An electromagnetic linear actuator directly drives the valve spool and rapidly adjusts the pressure of braking wheel cylinders. A dynamic model of electromagnetic direct-drive valve considering improved LuGre dynamic friction is established. A novel cascade control algorithm with an outside loop pressure fuzzy controller and an inside loop electromagnetic direct-drive valve position controller was proposed. An adaptive integral robust inside loop controller is designed by combining friction compensation adaptive control law, linear feedback, and integral robust control. The uncertainty parameters and the friction state are estimated online. The stability of the cascade controller is proved by the Lyapunov method. Then a multi-objective opitimizemization design method of control parameters is proposed, which combines a multi-objective game theory and a technique for order preference by similarity to ideal solution (TOPSIS) based on entropy weight. The results show that the pressurization time of cascade control is less than 0.09 s under the 15 MPa step target signal. The control precision is improved effectively by the cascade controller under the ARTEMIS condition. 相似文献
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针对阵列信号中部分自适应信号处理问题,提出了一种新的基于平滑阵列的降维方法. 该方法将全阵列平滑处理,通过分割成相互重叠的子阵达到降维的目的. 该波束形成器使用了两级加权的结构. 根据方向图相乘原理,天线方向图是两级加权矢量独立产生的方向图的乘积,此波束形成器可以等效为一种空域滤波器的级联形式. 通过大量的计算机仿真验证了此方法的有效性和优越性. 相似文献