In this paper, a modified particle swarm optimization(MPSO) algorithm is proposed to solve the reliability redundancy optimization problem. This algorithm modifies the strategy of generating new position of particles....
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In this paper, a modified particle swarm optimization(MPSO) algorithm is proposed to solve the reliability redundancy optimization problem. This algorithm modifies the strategy of generating new position of particles. For each generation solution, the flight velocity of particles is removed. Whereas the new position of each particle is generated by using difference strategy. Moreover, an adaptive parameter is used to ensure diversity of feasible solutions. Experimental results on four benchmark problems demonstrate that the proposed MPSO has better robustness, effectiveness and efficiency than other algorithms reported in literatures for solving the reliability redundancy optimization problem.
In this paper, we propose a novel method for real estate price prediction using web new media sentiments by incorporating human searching behaivor on the web. By combining online daily news' sentiments and Google ...
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In this paper, we propose a novel method for real estate price prediction using web new media sentiments by incorporating human searching behaivor on the web. By combining online daily news' sentiments and Google search engine query data, we construct a web news content and online search behavior-based integrated model for real estate prediction. Besides these factors, real estate price time series data are also considered into the model in order to improve the forecasting performance. Furthermore, we make a comparison between the integrated model and the baseline model without search engine query data. Experimental results indicate that the integrated model outperforms the non-integrated model, which suggests that online user searching behavior is of great value in enhancing the prediction performance. These findings imply that the proposed integrated model is effective and feasible for real estate market prediction.
The extensions for logic-based knowledge bases with integrity constraints are rather popular. We put forward an alternative criteria for analysis of integrity constraints in Web ontology language (OWL) ontology unde...
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The extensions for logic-based knowledge bases with integrity constraints are rather popular. We put forward an alternative criteria for analysis of integrity constraints in Web ontology language (OWL) ontology under the closed world assumption. According to this criteria, grounded circumscription is applied to define integrity constraints in OWL ontology and the satisfaction of the integrity constraints by minimizing extensions of the predicates in integrity con- straints. According to the semantics of integrity constraints, we provide a modified tableau algorithm which is sound and complete for deciding the consistency of an extended ontol- ogy. Finally, the integrity constraint validation is converted into the corresponding consistency of the extended ontology. Comparing our approach with existing integrity constraint validation approaches, we show that the results of our approach are more in accordance with user requirements than other approaches in certain cases.
This paper finds the most expressive segments of a shape category called similar and discriminative parts, which can distinguish the learned shape class from other groups. The proposed model chooses a computationally ...
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engineering systems have become quite complicated in recent days. The requirements of design are complex and it is hard to meet them by considering only one discipline. In this paper, we suggest a hybrid Multi-objecti...
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In this paper, a hybrid TS-DE algorithm based on Tabu search and differential evolution algorithm is proposed to solve the reliability redundancy optimization problem. A differential evolution algorithm is embedded in...
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In this paper, a hybrid TS-DE algorithm based on Tabu search and differential evolution algorithm is proposed to solve the reliability redundancy optimization problem. A differential evolution algorithm is embedded in Tabu search algorithm. TS is applied for searching solutions space, and DE is used for generating neighborhood solutions. The advantages of both algorithms are considered simultaneously. And an adaptive hybrid TS-DE approach is developed to solve three benchmark reliability redundancy allocation problems. By comparing with other algorithms reported in previous literatures, experimental results show that the proposed method is effective and efficient for solving the reliability redundancy optimization problem.
During an epidemic, the spatial, temporal and demographical patterns of disease transmission are determined by multiple factors. Besides the physiological properties of pathogenes and hosts, the social contacts of hos...
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ISBN:
(纸本)9781479943012
During an epidemic, the spatial, temporal and demographical patterns of disease transmission are determined by multiple factors. Besides the physiological properties of pathogenes and hosts, the social contacts of host population, which characterize individuals' reciprocal exposures of infection in view of demographical structures and various social activities, are also pivotal to understand and further predict the prevalence of infectious diseases. The means of measuring social contacts will dominate the extent how precisely we can forecast the dynamics of infections in the real world. Most current works focus their efforts on modeling the spatial patterns of static social contacts. In this work, we address the problem on how to characterize and measure dynamical social contacts during an epidemic from a novel perspective. We propose an epidemic-model-based tensor deconvolution framework to address this issue, in which the spatiotemporal patterns of social contacts are represented by the factors of tensors, which can be discovered by a tensor deconvolution procedure with an integration of epidemic models from rich types of data, mainly including heterogeneous outbreak surveillance, social-demographic census and physiological data from medical reports. Taking SIR model as a case study, the efficacy of the proposed method is theoretically analyzed and empirically validated through a set of rigorous experiments on both synthetic and real-world data.
The past decade has witnessed the rapid development of search engines, which has become an indispensable part of everyday life. However, people are no longer satisfied with accessing to ordinary information, and they ...
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The replication of the non-structure data from one data center to another is an urgent task in HBase. The paper studies the priority growth probability of the priority replication queue and proposed a dynamic priority...
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A superpixels based interactive image segmentation algorithm is proposed in this paper. Firstly the initial segmentation is obtained by MeanShift algorithm, and then a graph is built using pre-segmented regions as nod...
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ISBN:
(纸本)9781629932101
A superpixels based interactive image segmentation algorithm is proposed in this paper. Firstly the initial segmentation is obtained by MeanShift algorithm, and then a graph is built using pre-segmented regions as nodes, finally min-cut/maxflow algorithm is implemented for global solution. In this process, each region is represented by a color histogram and Bhattacharyya coefficient is chosen to calculate the similarity between any two regions. Extensive experiments are performed and the results show that the presented algorithm obtains much more satisfactory segmentation results with less user interaction and less comsuming time than MSRM algorithm.
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