The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Replication can improve reliability and availability of files by creating lots of replicas for files. But an overly large number of replicas spend a lot of storage resources, and have an adverse effect on network performance. In order to save and make the best use of storage resource, this paper presents a replica deletion strategy based on gray prediction theory and cost, to delete the useless replicas...
Referring to the Taylor formula, a regression model of VBmax (maximum width of the flank wear land in the central portion of the active cutting edge) is assigned for the exponential form. Turning Hastelloy X alloy experiments was designed based on the quadratic rotary combination design technique. By identifying regression coefficient using genetic algorithm toolbox in MALAB7.1, a tool wear prediction...
Traffic prediction is of significant importance for telecommunication network planning and network optimization. In this paper, the traffic series from a certain mobile network in Heilongjiang province in China is studied. The characteristics in respect of both trend and periodicity are explored with autocorrelation function. Based on the characteristics exhibited in the traffic series, multiplicative...
The dynamic travel time prediction is important contents of The intelligent Transportation System. Dynamic travel time is updating the travel time by the prediction model on the same path or segment of the journey. Different forecasting models are corresponded to different methods, and different methods are corresponded to different prediction accuracy. Contrast to the existing methods, such as historical...
A new model is introduced in this paper to construct the input-output relation in the prediction and control problem of non-analytic systems. The historical input-output data of general system is de-noised with wavelet transformation and SVM, and the input-output variables which can reflect the features of the system are determined with correlation analysis and sensitivity analysis. With the historical...
In this paper a prediction model based on grey systems theory is used for development predication of Yantai City's service industry. The analytical results demonstrate that the designed model has good prediction ability to address the development speed of service industry in Yantai City and this method can be adapted to other areas.
Prediction is a very important element of human intelligence and plays a major role in human behavior, perception, and learning. This paper presents the development of a mathematical model of the prediction mechanism in the context of a Bayes filter, which is the predominant schema used for integrating temporal data in the field of robot mapping and localization problems. We propose a generalized...
One of the most important goals of time series analysis is prediction basing on the analyzed information. But it is not easy to analyze the patterns, regularities and trends of non-stationary and/or chaos time series because their major characteristics are non-linear and vague. In this paper, we propose primary and secondary tuning procedures that can enhance the accuracy for designing fuzzy prediction...
In the task of robot localization, Bayes filters use two processes: the prediction step and the measurement-update step. Briefly, the state transition model is responsible for prediction, and the sensor model is responsible for measurement updates. This paper presents a new approach to the sensor model, called the predictive sensor model, which utilizes a prediction mechanism to improve the efficiency...
To improve the forecasting precision of electricity consumption, and content the demand of marketing, we establish the model by combining particle swarm optimization (PSO) with the improved grey theory. The method is simple, easy to do practice and its convergence rate is quick. It can find the overall optimal solution of problems in great probability, and can effectively overcome the shortage of...
This paper presents an study of a new hybrid method based on the greedy randomized adaptive search procedure(GRASP) and evolutionary strategies(ES) concepts for tuning the structure and parameters of an artificial neural network (ANN). It consists of an ANN trained and adjusted by this new method, which searches for the minimum number of (and their specific) relevant time lags for a correct time series...
In this paper, we study the problem of detecting slow-moving targets using space-time adaptive processing (STAP). The construction of the optimum weights at each range implies the estimation of the interference-plus-noise covariance matrix. This is typically done by straight averaging of snapshots at neighboring ranges. However, in most bistatic configurations, snapshot statistics are range dependent...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.