A method to simplify the calculation in the process of measuring graph similarity is proposed, where lots of redundant operations are avoided in order to quickly obtain the initial tickets matrixIn this proposal, the ...
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ISBN:
(纸本)9783319483535
A method to simplify the calculation in the process of measuring graph similarity is proposed, where lots of redundant operations are avoided in order to quickly obtain the initial tickets matrixIn this proposal, the element value of the initial tickets matrix is assigned to 1.when it is positive in corresponding position of the paths matrix at the first timeThe proposed method calculates the initial tickets matrix value based on the positive value in the paths matrix in a forward and backward wayAn example is provided to illustrate that the method is feasible and effective.
Compared with traditional VANET(Vehicular Ad-Hoc Networks) routing techniques, geographic routing has been proven to be more fittable for highly mobile scenes. Traditional routings use greedy modes or fixed forwarding...
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Compared with traditional VANET(Vehicular Ad-Hoc Networks) routing techniques, geographic routing has been proven to be more fittable for highly mobile scenes. Traditional routings use greedy modes or fixed forwarding paths to sent packets. But, the dynamic features of VANET such as fast changed topology, vehicles density and radio obstacles, could cause local maximum and sparse connectivity. Due to the characteristics of wireless channel, while there are too many packets transmit through a path, the delay and the number of packets loss will both increase clearly. We propose DMPR, a Dynamic Multipath Routing, combined with node location and digital map. The proposed DMPR detects transmission delay of different paths every once in a period of time, and dynamically determine the transmission ratio of each path. We execute NS2 simulation to exhibit that DMPR routing protocol significantly outperform three well known VANET ones in terms of the average packet delivery ratio and end-to-end delay.
Traditional Collaborative Filtering has been one of the most widely used recommender systems, unfortunately it suffers from cold-start and data sparsity problems. With the development of social networks, more recommen...
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ISBN:
(纸本)9781467375931
Traditional Collaborative Filtering has been one of the most widely used recommender systems, unfortunately it suffers from cold-start and data sparsity problems. With the development of social networks, more recommendation systems are trying to generate more eligible recommendation through excavating users' potential preferences using their social relationships. Almost all social recommender systems employ only positive inter-user relations such as friendship or trust information. However, incorporating negative relations in recommendation has not been investigated thoroughly in literature. In this paper, we propose a novel model-based method which takes advantage of both positive and negative inter-user relations. We apply matrix factorization techniques and utilize both rating and trust information to learn users' reasonable latent preference. We also incorporate two regularization terms to take distrust information into consideration. Our experiments on real-world and open datasets demonstrate the superiority of our model over the other state-of-the-art methods.
With the development of high-throughput microarray chip technology, there are a large number of microarray expression data, which have few samples compared to the genes of high dimensions. And in recent years, more an...
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In order to avoid the defect of lip identification about one single picture and enhance the accuracy of the recognition, this paper applies the dynamic lip identification and puts forward the method to calibrate the f...
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A genome-wide association study (GWAS) typically involves detecting epistatic interactions of multiple genetic variants on the susceptibility of complex human diseases. As the most abundant source of genetic variation...
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A genome-wide association study (GWAS) typically involves detecting epistatic interactions of multiple genetic variants on the susceptibility of complex human diseases. As the most abundant source of genetic variation in human genome, the number of single nucleotide polymorphisms (SNPs) reaches millions in public datasets and SNP data collected from thousands of individuals in case-control studies may shed light on our understanding of epistatic interactions. Various methods have been proposed in previous literature for identifying genetic interactions, but they are infeasible for GWAS as biology data is too large, we here propose a method ‘epistasis group based on Bayesian inference’ (EGBI). EGBI applies a Bayesian marker partition model to investigate observed case-control data and computes the posterior distribution of each epistasis group that is associated with the disease via Markov chain Monte Carlo (MCMC). When applied to both simulated data and WTCCC type 1.diabetes data, EGBI successfully identified many known susceptible genes including CTLA4 and MHC and performed more powerfully than its competitors.
Ant colony algorithm is a more effective way of solving traveling salesman problem (TSP). Ant colony algorithm adopts the distributed parallel computing mechanism;and it is easy to combine with other methods. Furtherm...
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In this paper, a differential evolution (DE) algorithm combined with Lévy flight is proposed to solve the reliability redundancy allocation problems. The Lévy flight is incorporated to enhance the ability of...
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Policy iteration,which evaluates and improves the control policy iteratively,is a reinforcement learning *** evaluation with the least-squares method can draw more useful information from the empirical data and theref...
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Policy iteration,which evaluates and improves the control policy iteratively,is a reinforcement learning *** evaluation with the least-squares method can draw more useful information from the empirical data and therefore improve the data ***,most existing online least-squares policy iteration methods only use each sample just once,resulting in the low utilization *** the goal of improving the utilization efficiency,we propose an experience replay for least-squares policy iteration(ERLSPI)and prove its *** method combines online least-squares policy iteration method with experience replay,stores the samples which are generated online,and reuses these samples with least-squares method to update the control *** apply the ERLSPI method for the inverted pendulum system,a typical benchmark *** experimental results show that the method can effectively take advantage of the previous experience and knowledge,improve the empirical utilization efficiency,and accelerate the convergence speed.
In this paper, we proposed a new image fusion scheme on spatial domain. The interest of the scheme is its real time. The framework contains two steps: saliency detection and coefficient selection based on the principl...
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