A zone routing protocol based on the energy consumption speed of nodes in mobile Adhoc networks is presented. A route select parameter computed by residual lifetime of nodes and hop count of route is used to be select...
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A zone routing protocol based on the energy consumption speed of nodes in mobile Adhoc networks is presented. A route select parameter computed by residual lifetime of nodes and hop count of route is used to be selected the best route, the nodes that have more energy have more probability of chosen. The mechanism can balance the energy consumption of node and prolong network's life. Simulation result comparing with zone routing protocol in NS-2 shows EZRP has less number of death nodes, lower routing overhead, and longer lifetime of network.
This paper proposes a novel ACERDH method using histogram expansion. Considering the local properties of the histogram, when an appropriate range rather than a global location is selected, the contrast of the whole im...
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The memory scheme is one of the most widely employed techniques in Evolutionary Algorithms for solving dynamic optimization problems. The updating strategy is a key concern for the memory scheme. Unfortunately, the ex...
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The memory scheme is one of the most widely employed techniques in Evolutionary Algorithms for solving dynamic optimization problems. The updating strategy is a key concern for the memory scheme. Unfortunately, the existent memory updating strategies neglect the characteristics of the memory updating behaviors, and sometimes this could lead results against the original intention. In this paper, a novel updating strategy is proposed, which can adaptively update the memory according to the characteristics of the memory updating behaviors. Experiments are carried out in different kinds of dynamic environments, and the experimental results show that the proposed strategy is better than the traditional strategies.
Qualitative simulation is effective methods processing incomplete knowledge, how to represent qualitative knowledge and reduce spurious behaviors is its research emphasis. Contraposing the limitations of existing meth...
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The task of Aircraft Landing Scheduling (ALS) is to give a landing sequence and landing times for a given set of aircrafts where many constraints must be satisfied. ALS is an NP-hard problem with large-scale and multi...
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NURBS method is extensively used in the field of Geometric Modeling. Since the original NURBS method does not have time factor, it can not display the huge advantage in the dynamics field. In this article, inspired by...
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A novel method combined fuzzy c-means (FCM) and hierarchical agglomerative clustering (HAC) is presented to extract the qualitative states from reconstructed phase space by considering the dynamical relations of under...
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A novel method combined fuzzy c-means (FCM) and hierarchical agglomerative clustering (HAC) is presented to extract the qualitative states from reconstructed phase space by considering the dynamical relations of underlying nonlinear system. The qualitative state, in which all points have similar properties, is characterized by three measures, linear density, temporal reachability, and stable degree, which are defined as the criteria of merging subclasses. The time series sampled from a classic nonlinear system, Lorenz system, and electroencephalogram (EEG) signals are used to test this method. The results show that the qualitative states can be efficiently distinguished from these time series by the proposed method.
The main goal in proteomics is to describe the proteome in a comprehensive and accurate way, and enzymolysis is a key step in the process of large-scale proteomics experiments. For the same protein samples, using diff...
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In order to improve the performance of time series classification, we introduce a new approach of time series classification. The first step of the approach is to design a feature exaction model based on Trend and Sur...
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In order to improve the performance of time series classification, we introduce a new approach of time series classification. The first step of the approach is to design a feature exaction model based on Trend and Surprise Abstraction tree (TSA-tree). The second step of the approach is to combine the exacted global feature and 1 nearest neighbor to classify time series. The proposed approach is compared with a number of known classifiers by experiments in artificial and real-world data sets. The experimental results show it can reduce the error rates of time series classification, so it is highly competitive with previous approaches.
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