Based on Particle Filter, Gravity Gradient-Terrain aided position technology is proposed in this paper. With the sensitivity of gravity gradient to terrain, the gravity gradient reference map can be computed from the ...
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In this paper, we proposed a susceptible-infected model with variant infection rates because different individuals have different resistance to diseases in different periods of real epidemic events. We consider two ca...
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Electric power, potable water, telecommunications, natural gas, and transportation are examples of critical infrastructures, the intrinsic feature of which are suitable for network analysis. This paper proposes a meth...
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The performance of the 'current' statistical model algorithm gets worse when there is a sudden maneuver. To solve this problem, an improved algorithm is presented. This algorithm is implemented through a pair ...
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The performance of the 'current' statistical model algorithm gets worse when there is a sudden maneuver. To solve this problem, an improved algorithm is presented. This algorithm is implemented through a pair of parallel adaptive filters together with information fusion technique. By introducing the state information of targets, the output of the fuzzy system can adjust the predicted covariance of the filter adaptively. The simulation results show that the proposed algorithm has better performance when there is a sudden maneuver.
The paper proposes a novel memory-based collab.rative filtering algorithm-Multi-lab.l Probabilistic Latent Semantic Analysis based Collab.rative Filtering, which improves the quality of recommendations by reducing the...
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The paper proposes a novel memory-based collab.rative filtering algorithm-Multi-lab.l Probabilistic Latent Semantic Analysis based Collab.rative Filtering, which improves the quality of recommendations by reducing the dimension of the user-rating-data matrix by multi-lab.l probabilistic latent semantic analysis when the matrix is extremely sparse. Firstly, it confines the set of latent variables of probability latent semantic analysis to the set of multi-lab.l of items to make latent variables have meanings of corresponding lab.ls. Then it learns the probabilistic distribution of latent variables, i.e., the model of use's interest, to compress the user-rating-data matrix. Finally, it computes the similarity between different users based on the above learned model and makes recommendations. Compared to memory-based collab.rative filtering algorithms, the proposed algorithm decreases the mean absolute error 4 percents averagely on test dataset by reducing the dimension of the user-rating-data matrix. The proposed algorithm makes the recommendation system understandable and obtains competitive recommendations compared to the filtering algorithm which reduces the dimension of the user-rating-data matrix by probabilistic latent semantic analysis.
This paper presents a new affine registration approach for planar point pattern matching. A process of parameter space clustering is implemented to confirm a one-to-one mapping between the maximal subsets of feature p...
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A new path planning method for UAV in static workspace is presented. The method can find a nearly optimal path in short time which satisfies the UAV kinematic constraints. The method makes use of the skeletons to cons...
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By researching the Brushlet domain coefficients of texture images, we found that the distribution of the magnitudes of Brushlet domain coefficients roughly meet rayleigh distribution. And there are correlations betwee...
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In this paper, a multi-agent social evolutionary algorithm is proposed for multiobjective optimization problems. It completes the search process by the agent evolution. MOMASEA (multi-agent social evolutionary algorit...
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Traditional path planning methods are too slow to meet the real-time requirement in practical applications. In order to solve this problem, an idea of path net was proposed in this paper. The path planning procedure i...
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