PET熔体输送系统中熔体温度自动控制方案

在热媒温度控制系统中以熔体温度作为主参数,组成串极调节系统。投入运行后,熔体温度稳定,调节阀动作平稳,效果良好。     

Determination of temporal information granules to improve forecasting in fuzzy time series

Partitioning the universe of discourse and determining intervals containing useful temporal information and coming with better interpretability are critical for forecasting in fuzzy time series. In the existing literature, researchers seldom consider the effect of time variable when they partition the universe of discourse. As a result, and there is a lack of interpretability of the resulting temporal intervals. In this paper, we take the temporal information into account to partition the universe of discourse into intervals with unequal length. As a result, the performance improves forecasting quality. First, time variable is involved in partitioning the universe through Gath–Geva clustering-based time series segmentation and obtain the prototypes of data, then determine suitable intervals according to the prototypes by means of information granules. An effective method of partitioning and determining intervals is proposed. We show that these intervals carry well-defined semantics. To verify the effectiveness of the approach, we apply the proposed method to forecast enrollment of students of Alabama University and the Taiwan Stock Exchange Capitalization Weighted Stock Index. The experimental results show that the partitioning with temporal information can greatly improve accuracy of forecasting. Furthermore, the proposed method is not sensitive to its parameters.     

Semantic weak signal tracing

The weak signal concept according to Ansoff has the aim to advance strategic early warning. It enables to predict the appearance of events in advance that are relevant for an organization. An example is to predict the appearance of a new and relevant technology for a research organization. Existing approaches detect weak signals based on an environmental scanning procedure that considers textual information from the internet. This is because about 80% of all data in the internet are textual information. The texts are processed by a specific clustering approach where clusters that represent weak signals are identified. In contrast to these related approaches, we propose a new methodology that investigates a sequence of clusters measured at successive points in time. This enables to trace the development of weak signals over time and thus, it enables to identify relevant weak signal developments for organization’s decision making in strategic early warning environment.     

FREQUENCY DOMAIN TESTS OF MULTIVARIATE GAUSSIANITY AND LINEARITY

A stationary multivariate time series { X _t } is defined as linear if it can be written in the form X _t = ∑^∞ _{j =−∞} A _j e _{t − j} where A _j are square matrices and e _t are independent and identically distributed random vectors. If the e _t } are normally distributed, then { X _t is a multivariate Gaussian linear process. This paper is concerned with the testing of departures of a vector stationary process from multivariate Gaussianity and linearity using the bispectral approach. First the definition and properties of cumulants of random matrices are used to obtain the expressions for the higher-order cumulant and spectral vectors of a linear vector process as defined above. Then it is shown that linearity of a vector process implies constancy of the modulus square of its normalized higher-order spectra whereas the component of such a vector process does not necessarily have a linear representation. Finally, statistics for the testing of multivariate Gaussianity and linearity are proposed.     

啮合同向双螺杆挤出机的相似放大

首先给出啮合同向双螺杆挤出机熔体输送段相似放大方法中所用到的参量表达式,然后从混合、热平衡和综合这两方面分别进行相似放大,并分析各自的优缺点。利用W＆P公司ZSK系列混合机的设计特点和技术数据,分析了相似放大设计在实际中的应用。对大型同向双螺杆挤出机提出相似放大的准则,应是螺杆线速度保持恒定。     

新型螺杆挤出机熔体输送理论的研究

介绍了一种新型嵌套式螺杆挤出机。对熔体输送段进行了深入分析，把内螺杆的运动等效为螺杆轴的反向拖曳和螺棱的正向推力置换两部分作用，建立了对应的物理模型和数学模型，并得到了解析解。重点讨论了沿螺槽方向的流动和横向流动，并与普通单螺杆挤出机作对比，得到了螺杆和机筒同时旋转情况下的体积流率。结果表明，所建模型的解析解和文献中的实验数据较为吻合，当螺杆和机筒同时旋转时，熔体输送段的体积流率大大增加，横向流动和平行平板模型类似。     

挤出机头的热平衡分析及计算

建立了挤出机头的热开衡方程，并进行了分析和讨论。列出了方程中各个热通量计算公式，为挤出机头控制系统的设计提供了依据。     

改性木粉/PVC复合材料的研究进展

概述了PVC木塑复合材料的发展和背景与性能。简述了木质材料的性质和木粉改性的方法,如物理方法和化学方法。介绍了木塑复合材料的生产流程、成型方法(模压成型、挤出成型、注射成型及其成型设备,讨论了对工艺参数的一些要求。指出目前国内PVC木塑复合材料发展存在的一些问题,并指明了PVC木塑复合材料的应用前景。     

Parameter Estimation for Periodically Stationary Time Series

Abstract. The innovations algorithm can be used to obtain parameter estimates for periodically stationary time series models. In this paper, we compute the asymptotic distribution for these estimates in the case, where the innovations have a finite fourth moment. These asymptotic results are useful to determine which model parameters are significant. In the process, we also develop asymptotics for the Yule–Walker estimates.     

Nonlinear time series forecasting with Bayesian neural networks

The Bayesian learning provides a natural way to model the nonlinear structure as the artificial neural networks due to their capability to cope with the model complexity. In this paper, an evolutionary Monte Carlo (MC) algorithm is proposed to train the Bayesian neural networks (BNNs) for the time series forecasting. This approach called as Genetic MC is based on Gaussian approximation with recursive hyperparameter. Genetic MC integrates MC simulations with the genetic algorithms and the fuzzy membership functions. In the implementations, Genetic MC is compared with the traditional neural networks and time series techniques in terms of their forecasting performances over the weekly sales of a Finance Magazine.