A method for checking the accuracy of prognostic models in the absence of experimental data for comparing the modeling results is presented. The developed neural network determines a technology class, which is compared with the results obtained using the fuzzy logic model. The model accuracy is determined by computing the root-mean-square error of the modeling and the correlation between the results obtained using the fuzzy logic model and the neural network.
相似文献We compare various extensions of the Bradley–Terry model and a hierarchical Poisson log-linear model in terms of their performance in predicting the outcome of soccer matches (win, draw, or loss). The parameters of the Bradley–Terry extensions are estimated by maximizing the log-likelihood, or an appropriately penalized version of it, while the posterior densities of the parameters of the hierarchical Poisson log-linear model are approximated using integrated nested Laplace approximations. The prediction performance of the various modeling approaches is assessed using a novel, context-specific framework for temporal validation that is found to deliver accurate estimates of the test error. The direct modeling of outcomes via the various Bradley–Terry extensions and the modeling of match scores using the hierarchical Poisson log-linear model demonstrate similar behavior in terms of predictive performance.
相似文献传统单变量灰色预测模型的指数结构形式制约了其对小样本振荡序列的模拟与预测能力, 对此, 通过包络线将振荡序列拓展为具有明确上界与下界的区间灰数序列, 还原影响因素不确定性条件下振荡序列的区间灰数形式; 在此基础上, 利用区间灰数建模方法实现对振荡序列取值范围的模拟与预测. 应用该方法较好地模拟了具有振荡特征的重庆市空气质量指数(AQI) 的变化规律, 所得研究成果为小样本振荡序列的模拟与预测提供了一种新的分析方法与建模手段.
相似文献采用机理与数据相结合的建模方法对永磁同步电动机进行分数阶时域和频域建模. 在分数阶时域建模方法中, 设计伪随机激励信号, 获取实时实验数据并采用输出误差辨识算法来获取分数阶阶次; 在分数阶频域建模方法中, 由实时实验数据绘制出电动机的对数频率特性曲线. 采用分数阶频域建模中经典Levy 辨识算法, 利用加权函数加以改进, 得到永磁同步电动机分数阶模型辨识结果. 最后通过对两种方法得到的结果进行对比表明了所提出模型的可靠性.
相似文献In recent years, the importance of computationally efficient surrogate models has been emphasized as the use of high-fidelity simulation models increases. However, high-dimensional models require a lot of samples for surrogate modeling. To reduce the computational burden in the surrogate modeling, we propose an integrated algorithm that incorporates accurate variable selection and surrogate modeling. One of the main strengths of the proposed method is that it requires less number of samples compared with conventional surrogate modeling methods by excluding dispensable variables while maintaining model accuracy. In the proposed method, the importance of selected variables is evaluated using the quality of the model approximated with the selected variables only. Nonparametric probabilistic regression is adopted as the modeling method to deal with inaccuracy caused by using selected variables during modeling. In particular, Gaussian process regression (GPR) is utilized for the modeling because it is suitable for exploiting its model performance indices in the variable selection criterion. Outstanding variables that result in distinctly superior model performance are finally selected as essential variables. The proposed algorithm utilizes a conservative selection criterion and appropriate sequential sampling to prevent incorrect variable selection and sample overuse. Performance of the proposed algorithm is verified with two test problems with challenging properties such as high dimension, nonlinearity, and the existence of interaction terms. A numerical study shows that the proposed algorithm is more effective as the fraction of dispensable variables is high.
相似文献Evolutionary polynomial regression (EPR) is extensively used in engineering for soil properties modeling. This grey-box technique uses evolutionary computing to produce simple, transparent and well-structured models in the form of polynomial equations that best explain the observed data. A key task is then to determine mathematical structures for modeling physical phenomena and to select the optimal EPR model. This requires an algorithm to search through the model structure space and successfully produce feasible solutions that honor a set of statistical metrics. The complexity of EPR models increases greatly, however, with the number of polynomial terms used to tune these models. In this paper, we propose an alternative EPR for modeling complex soil properties. We implement a dual search-based EPR with self-adaptive offspring creation as model structure search strategy and couple a compromise programming tool to select a model that is preferred statistically relative to models with different polynomial terms. We illustrate our method using real-world data to improve predictions of optimal moisture content and creep index for soils. Our results demonstrate that the models derived using the proposed methodology can predict soil properties with adequate accuracy, physical meaning and lower number of parameters and input variables.
相似文献System and software engineers use SysML models for the graphical modeling of the embedded systems. The SysML models are inadequate to express the discrete controllers with continuously evolving variables. The real-time constraints such as discrete and continuous dynamics are considered to be an important aspect in embedded systems. The lack of support of real-time aspect in SysML model can lead to inexplicit modeling of the embedded systems. The imprecise modeling could cause catastrophic results when an embedded system gets operational. In this paper, we propose hybrid automata-based semantics that supports the discrete and continuous behavior in upgraded SysML block diagram. The upgraded SysML block diagram is used for the modeling of the embedded system. Furthermore, we use model checker PRISM for the early design verification of upgraded SysML block diagram. Finally, we demonstrate the effectiveness of our proposed approach with the help of two case studies “temperature control system” and “water level control system”.
相似文献Practitioner summary: A 13.5?cm screen was preferred for making calls, whereas a 17.5?cm screen was best for web searching and gaming. An outward bi-fold screen concept with a 17.5?cm screen and Z-shape tri-fold screen concept with a 22.9?cm screen were preferred. Overall, the Z-shape concept was most preferred.
Abbreviations: SD: standard deviation; ANOVA: analysis of variance; H: Height; W: Width; T: Thickness 相似文献
The design of a vehicle frame is largely dependent on the loads applied on the suspension and heavy parts mounting points. These loads can either be estimated through full analytical multibody dynamic simulations, or from semi-analytical simulations in which tire and road sub-models are not included and external vehicle loads, recorded during field testing, are used as inputs to the wheel hubs. Several semi-analytical methods exist, with various modeling architectures, yet, it is unclear how one method over another improves frame loads prediction accuracy.
This study shows that a semi-analytical method that constrains the vehicle frame center of gravity movement along a recorded trajectory, using a control algorithm, leads to an accuracy within 1% for predicting frame loads, when compared to reference loads from a full analytical model. The control algorithm computes six degrees of freedom forces and moments applied at the vehicle center of gravity to closely follow the recorded vehicle trajectory. It is also shown that modeling the flexibility of the suspension arms and controlling wheel hub angular velocity both contribute in improving frame loads accuracy, while an acquisition frequency of 200 Hz appears to be sufficient to capture load dynamics for several maneuvers. Knowledge of these loads helps engineers perform appropriate dimensioning of vehicle structural components therefore ensuring their reliability under various driving conditions.
相似文献Computational modeling of visual saliency has become an important research problem in recent years, with applications in video quality estimation, video compression, object tracking, retargeting, summarization, and so on. While most visual saliency models for dynamic scenes operate on raw video, several models have been developed for use with compressed-domain information such as motion vectors and transform coefficients. This paper presents a comparative study of eleven such models as well as two high-performing pixel-domain saliency models on two eye-tracking datasets using several comparison metrics. The results indicate that highly accurate saliency estimation is possible based only on a partially decoded video bitstream. The strategies that have shown success in compressed-domain saliency modeling are highlighted, and certain challenges are identified as potential avenues for further improvement.
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