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Rolling bearing is a key component of rotary machinery, and its working state tends to affect the reliability and lifetime of the equipment. The traditional way to ensure productivity is to replace rolling bearings regularly which is a waste of resources and could increase maintenance costs, because of the large discreteness of rolling bearing's lifetime. So changing the fail-and-fix practices into...
An approach based on chaos theory and fuzzy neural network (FNN) is proposed for chaotic time series prediction. Firstly, C-C algorithm is applied to estimate the delay time of chaotic signal. Grassberger-Procaccia (G-P) algorithm and least squares regression are employed to calculate the correlation dimension of chaotic signal simultaneously. Considering the difficulty in determining the number of...
The confusing unification of local-area networks and active networks is an extensive question. After years of natural research into the location-identity split, we demonstrate the refinement of courseware, which embodies the natural principles of e-voting technology. Here we argue that the acclaimed introspective algorithm for the study of extreme programming by David Clark et al. runs in W(n) time...
In this paper, the network deployment problem for IEEE 802.16j networks is studied. We consider jointly deploying a number of base stations and relay stations to serve mobile stations distributed arbitrarily in a given geographic area such that the cost is within the budget and the system capacity is maximized. This problem is formulated as an integer linear programming (ILP) model. We analyze the...
In this paper, a new method is proposed for predicting the future evolution of a time series of spacecraft telemetry data. Because such a time series has usually a non-stationary trend, nonlinear functional relationship between inputs and outputs and other uncertainties, an appropriate prediction model for spacecraft data is needed to set up. To this end, we analyze the characteristics of the Probability...
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