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Polymer dynamic extrusion is a complicated MIMO nonlinear system with time-varying, and the melt temperature is one of key parameters to measure and control. In order to improve the predicting accuracy of melt temperature distribution under the influence of multi-variable coupling, a ridge regression method based on Gaussian RBF (GRBF-RR) is presented. The model fulfill the nonlinear mapping and reconstruction...
When GM (1, 1) model is applied to simulate a pure exponential sequence, the errors usually occur. There are many kinds of limitation to the development coefficient and the primary sequence. The characteristics of the discrete GM (1, 1) model are analogous to the GM (1, 1) model. It can be regarded as the precise form of the formal model. The paper studied the growth rate of the simulation values...
Present researches on fashion color prediction based on grey systems theory; introduce the research process, data processing method and the forecasting grey model (GM (1, 1)); discuss on the problems existing in the current researches, such as the data collecting, model optimization problems; provide the current analysis result on historical data by our team; finally, put forward the future suggestions...
This study employed a DE-SVM model that hybridized the differential evolution (DE) and support vector machines (SVM) to improve the classification accuracy for rainstorm forecasting. This optimization mechanism combined the DE to optimize the SVM parameter setting. Based on the European Centre for Medium-Range Weather Forecasts (ECMWF), Japan and T213 precipitation data from 2003 to 2006, using DE-SVM,...
This text analyzed the reason of generating error of GM (1, 1), from the integral calculus angle discrete GM (1, 1). A kind of method putting forward making use of Romberg integral calculus formula and quadratic interpolation method to construct the background value of the model, raised simulation and prediction precision of GM(1,1), and the actual example verify the feasibility and effectiveness...
We consider Intelligent vehicle highway systems (IVHS) consisting of automated highway systems on which intelligent vehicles organized in platoons drive to their destination, controlled by a hierarchical control framework. In this framework there are roadside controllers that manage single stretches of highways. A collection of highways is then supervised by so-called area controllers. We focus on...
In the application of neural network model for short term load prediction, main problems are over many training samples, long training time and low convergence speed. For representative training samples, an ant colony clustering model based on Elman neural network was proposed in this paper. First, historical load data were pre-processed by using ant colony clustering method. The clustered data were...
Groundwater level has random characters because of influences factors of natural and anthropogenic. Study random prediction model of groundwater level on the basis of groundwater physical process analysis is important to groundwater appraisal. The theory of supporting vector machine based on small-sample machine learning theory is introduced into dynamic prediction of groundwater level. A least square...
To settle the problem which the precision and generalization performance of forecast model is affected easily by input variable, the method which reconstructs the original input space of back-propagation neural network by principal component analysis that can eliminate the relevance of value is researched. The method can not only reduce duplicated information but also extract the leading factors....
Dynamic modelling using the traditional least squares method with noisy input/output data can yield biased and sometimes unstable model predictions. This is largely because the cost function employed by the traditional least squares method is based on the one-step-ahead prediction errors. In this paper, the model-predicted-output errors are used in estimating the model parameters. As the cost function...
The paper proposes a systematic robust multivariable control strategy based on combination of systematic triangularization technique and robust control strategies. Two design stages are required. In the first design stage, multivariable control problem is reduced into a series of scalar control problems via triangularization technique. For each specific scalar system, two advanced control strategies...
The purpose of this paper is twofold. On one hand, we propose a modification of the general Model Predictive Control (MPC) approach where a prespecified tracking error is tolerated. The introduction of error tolerance (ET) in the MPC optimization algorithm reduces considerably the average duration of each optimization step and makes the MPC computationally more efficient and attractive for industrial...
Forecasting weapon system cost accurately has great meaning in determining weapons' appropriate price, reducing the cost risk and raising the efficiency of equipment expense utilization. The least squares support vector machine (LSSVM) was applied to forecast weapon system cost, and the chaos optimization algorithm, which is regarded as a good optimization method, was used to optimize the penalty...
Parameterized computational imaging (PCI) allows for a continuous, portable and remote imaging of physiology without the continuous need of complex imaging systems. The method trades complex imaging equipment for computing power and potentially wireless measured parameters. The PCI algorithm uses a baseline image along with computational models to calculate physically measurable parameters. As the...
This paper presents a model for estimating the iron losses in the stator teeth tips of surface permanent magnet (SPM) machines with fractional-slot concentrated windings based on simplified semi-analytical solutions for the machine flux densities. This model is being developed for use in machine design optimization software that analyzes very large numbers of candidate designs. Tooth tip design details...
The edgewise open city in western China is fast growing in recent years, through the case study of typical city - Yining, the study draws the most important influence factor: GDP, investment in fixed assets, value of foreign trade and disposable income of urban residents. Then this paper analyses them and creates the combinatorial optimization model, utilizes the analytic approach of the weight to...
A hybrid algorithm based on Extremal Optimization (EO) with adaptive levy mutation and Differential Evolution (HEODE) was proposed in this paper. It applied the idea of combination mechanism of global and local search. In the process of the global search, DE is an evolutionary algorithm based on the difference in group that can quickly approach a approximate optimal solution. During the local search,...
A new fuzzy optimization neural network model is proposed based on the Levenberg-Marquardt (LM) algorithm on account of the disadvantages of slow convergence of traditional fuzzy optimization neural network model. In this new model, the gradient descent algorithm is replaced by the LM algorithm to obtain the minimum of output errors during network training, which changes the weights adjusting equations...
On the theory of GIS and Evaluation and management of groundwater, a network of hydro-geological information systems has been developed. Model base management subsystem is designed, in which parameter calculation model, mining prediction model, and groundwater resources management model are included. Groundwater resource management model is build and applied in practice in this paper. Groundwater...
Predictive control algorithm based on the step or impulse response of the object, using a rolling over method realizing process on-line optimization control. In the optimization process, it gets the feedback correction continuously through the comparison between the measured system output and prediction model output, it is able to overcome certain extent impact as a result of prediction model error...
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