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This paper presents a kernel-based extreme learning machine (KELM) modeling method for speed decision making of autonomous land vehicles (ALVs) on rural roads. The model is obtained offline via the KELM algorithm using a small number of typical samples collected by an ALV platform on rural roads from experienced drivers. Compared with other typical machine learning algorithms such as support vector...
In this letter, we consider the problem of direction detection in deterministic interference and partially homogeneous noise. The target echoes, reflected by a distributed target, all come from the same direction. However, the signal steering vector is only known to lie in a subspace of dimension greater than one. The interference belongs to a subspace linearly independent of the signal subspace....
This paper proposes an online calculation method of theoretical power losses for high-voltage(HV) distribution system based on rapid modeling and data quality analysis in order to improve the timeliness, accuracy and efficiency of the important task. At first the power grid structure model can be rapidly formed according to the basis data library transferred from the original PSD-BPA format file....
Intrusion Detection is an indispensable component of Network Security. Because exists the problems of the high false positives rate and low detection efficiency in the current intrusion detection system, in this paper, we propose a hybrid intrusion detection model and improve intrusion detection system analyzer, applying the Data fusion and data mining techniques to intrusion detection systems. We...
Marine current is a typical spatio-temporal process. Through numerical simulation and model calculation, a large amount of 3D data fields of marine phenomenon is obtained, spatio-temporal model can effectively store, organize, manage and improve the spatial and temporal semantics of geographic objects. It can more accurately reproduce history, track changes, and predict the future. Temporal database...
Nowadays, there are increasing amount of data fields of tide and tidal current gained from ocean dynamical environment real-time stereo monitoring platform, model calculation and numerical simulation. Collaborative visualization of these data fields on the internet is becoming increasingly important for the utility of data. In this paper, we summarize the characters of tide and tidal current data...
Intermediate online targeted advertising (IOTA) is a new business model for online targeted advertising. Posting the right banner advertisement to the right web user at the right time is what advertisements allocation does in IOTA business model. This research uses probability theory to build a theoretical model based on Bayesian network to optimize advertisements allocation. The Bayesian network...
Forecasting method using neural networks has been advocated as an alternative to traditional statistical forecasting in recent years. The paper built a feed-forward neural network model to forecast the values of governmentpsilas financial educational fund (GFEF) in year 2010. On the basis of data processing, the structure of neural networks was given. The algorithm that adopted as a learning phase...
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