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The problem of place recognition is central to robot navigation. The robot needs to be able to recognize or at least to be able to estimate the likelihood that it has been at a place before when it has returned to a previously visited place. We cast the place recognition problem as one of classifying among multiple linear regression models, and argue that new theory from sparse signal representation...
In this paper, we introduce a simple but novel model to detect abnormal event in surveillance video using sparse autoencoder and recurrent neuron network. In this model, we first train a sparse autoencoder to extract features and use a sequence of temporal continuous features to train a recurrent neuron network to predict the subsequent features. We classify the frame as normal and abnormal based...
In this paper, we present a novel subjective quality model for online adaptive movie streaming service. The proposed model considers the Quality of Experience (QoE) of streaming video viewing as a cumulative evaluation process of consecutive segments that compose a story line. Under bandwidth constraint, streaming client may select lower-quality segment, pause playback for re-buffering, or both. The...
Due to the mechanical failure data is cumulatively acquired and has uncertain features, the memory model for fault diagnosis is required to adapt with the information updating. In this paper, a dynamic memory model using one-class support vector (OCSVM) is proposed to extract and keep diagnostic information. The feature of each failure type is respectively processed by incremental learning algorithm...
In this paper, depending on the interrelation of condenser's operational parameters, the factors which affect the vacuum of condenser are analyzed. And a soft-sensing model for condenser vacuum is given by using Support Vector Regression (SVR), then the model is verified and parameters are discussed based on the data of the 300MW steam turbine unit, and the prognostication precision is compared with...
The main idea of multi-class support vector machines (SVMs) is described. a multi-class model for regenerative water heater fault diagnosis is presented combining the fuzzy logic and SVMs. The typical faults set of regenerative water heater is built after thoroughly analyzing the relationships between performance parameters and faults. Finally, the model is inspected and verified by an example in...
This research found the key affecting factors on e-learning training effect with the use of survey method and analytic hierarchy process (AHP). Through literature research and survey method, we got the factors that affect e-learning training effect from three aspects: organizational factors, E-learning training factors and personal characteristics factors. Then we designed a questionnaire on importance...
Distribution centers site selection has become a popular problem in recent years. Fine distribution centers site selection can ensure the supply and reduce the cost. By studying the methods proposed by other scholars, a mew method, KPCA (kernel principal component analysis) -SVRM (support vector regression machine) is proposed by this paper. The first step of this method is to apply KPCA to SVRM for...
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