This paper proposes a novel method for breast cancer diagnosis using the features generated by genetic programming (GP). We developed a new individual combination pattern (Composite individual genetic programming) whi...
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This paper presents an efficient technique for processing of 3D meshed surfaces via spherical wavelets. More specifically, an input 3D mesh is firstly transformed into a spherical vector signal by a fast low distortio...
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This paper presents an efficient technique for processing of 3D meshed surfaces via spherical wavelets. More specifically, an input 3D mesh is firstly transformed into a spherical vector signal by a fast low distortion spherical parameterization approach based on symmetry analysis of 3D meshes. This signal is then sampled on the sphere with the help of an adaptive sampling scheme. Finally, the sampled signal is transformed into the wavelet domain according to spherical wavelet transform where many 3D mesh processing operations can be implemented such as smoothing, enhancement, compression, and so on. Our main contribution lies in incorporating a fast low distortion spherical parameterization approach and an adaptive sampling scheme into the frame for pro- cessing 3D meshed surfaces by spherical wavelets, which can handle surfaces with complex shapes. A number of experimental ex- amples demonstrate that our algorithm is robust and efficient.
An imbalanced data classification algorithm named as SBoost is proposed. SBoost regards the decision tree as a weak classifier. Only the instances that their prediction value is more than the threshold are updated wit...
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An imbalanced data classification algorithm named as SBoost is proposed. SBoost regards the decision tree as a weak classifier. Only the instances that their prediction value is more than the threshold are updated with their weights in every iteration. At the beginning of each iteration, SBoost makes use of data generation method to add synthetic minority class instances in order to balance training information. After the sub-classifier is formed, the algorithm deletes the synthetic instances that are not correctly classified. This paper puts forwards the theoretical analysis of training error bound. The experimental results show that SBoost has advantages on imbalanced data classification problem.
The speech interaction in-vehicle was mainly realized by the speech recognition. The human-machine interaction around was usually disturbed by the noise, and the speech received by the receiver was not the original pu...
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In this paper, we introduce a hybrid optimization algorithm with the Branch-and-Bound Method and the Ant Colony Optimization to solve the multi-chromosomal reversal median problem. We convert the large-scale genome in...
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ISBN:
(纸本)9783037853245
In this paper, we introduce a hybrid optimization algorithm with the Branch-and-Bound Method and the Ant Colony Optimization to solve the multi-chromosomal reversal median problem. We convert the large-scale genome into TSP maps at first. Then we use a hybrid optimization algorithm with the Branch-and-Bound Method and the Ant Colony Optimization to solve the problem. In our improved algorithm, we increase the search speed by implement multi-branch parallel search of ACO. Our extensive experiments on simulated datasets show that this median solver is efficient.
In this paper, we outline the problem of multi-join ordering query optimization in the semantic web scenario, also known as SPARQL BGP (Basic Graph Pattern) reordering optimization. Unlike most previous researches, we...
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In this paper, we outline the problem of multi-join ordering query optimization in the semantic web scenario, also known as SPARQL BGP (Basic Graph Pattern) reordering optimization. Unlike most previous researches, we concentrate on more general SPARQL query forms and devote ourselves to the problem of searching for the optimal query plan within a more complete search space-bushy plan space. We model the BGP reordering optimization as a genetic evolution problem and implement a genetic algorithm on the open-source Jena ARQ System. With carefully design of the chromosome encoding scheme and the cost model, the final experimental results show that our method outperforms the common heuristics method and is comparable with some other state-of-the-art optimization methods w.r.t. the output quality.
To accurately and actively provide users with their potentially interested information or services is the main task of a recommender system. Collaborative filtering is one of the most widely adopted recommender method...
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To accurately and actively provide users with their potentially interested information or services is the main task of a recommender system. Collaborative filtering is one of the most widely adopted recommender methods, whereas it is suffering the issue of sparse rating data that will severely degenerate the quality of recommendations. To address this issue, the article proposes a novel method, named the FTRA (Fusing Trust and Ratings), trying to improve the performance of collaborative filtering recommendation by means of elaborately integrating twofold sparse information, i.e., the conventional rating data given by users and the social trust network among the same users. The performance of FTRA is rigorously validated by comparing it with six representative methods on a real-world dataset. The experimental results show that the FTRA outperforms all other competitors in terms of both precision and recall. More importantly, our work suggests that the strategy of augmenting sparse rating data by fusing trust networks does significantly improve the quality of conventional collaborative filtering recommendation, and its quality could be further improved by means of designing more effective integrating schemes.
A performance evaluation model, weighted AUC (wAUC), is proposed to determine a better way to measure the imbalanced data learning classifiers. When computing the weighted area under the ROC curve, weights vary with t...
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OWL Ontologies may change continually to meet user's dynamic request and it may damage the integrity of the ontology. Thus, it is in urgent to propose an effective strategy to maintain the integrity of the continu...
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Multi-objective decision-making problems have been widely applied to business, financial investment, transportation, optimal routing design, environment protection, and military strategies. In this paper, we give a no...
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