In this paper, we analyzed the blindness of traditional clustering algorithms, which select cluster head based on residual energy. Then we proposed the Dynamic Clustering Algorithm (DCA) in Mobile Wireless Sensor Netw...
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The circular spots appear as round local peaks/valleys in image space, and they reflect omnidirectional symmetry and Gaussian distribution characteristics. According to these observations, a novel rotating line scan o...
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intelligent household as an extension of smart grid in the user side highly integrates loads management and control. Home energy management system (HEMS) with automatic demand response (ADR) is a key part of intellige...
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ISBN:
(纸本)9781467371070
intelligent household as an extension of smart grid in the user side highly integrates loads management and control. Home energy management system (HEMS) with automatic demand response (ADR) is a key part of intelligent household, which is able to fit their electricity demand without changing the residents' habits too much. Furthermore HEMS schedule their power consumption to save energy, reduce emission, shift peak load and reduce the financial burden. The characteristics of various electrical devices were analyzed in this paper, and a mathematical model of ADR was established. Multi-objective kinetic-molecular theory optimization algorithm was used to optimize the solution of the ADR model. Implementation results showed that the KMTOA was more accurate and reliable than other algorithms for the complexities of model and data size considered in this study. Compared with some similar algorithms, the multi-objective kinetic-molecular theory optimization algorithm shows more advantages.
There has been a growing interest in alignment-free methods for whole genome comparison and phylogenomic studies. In this study, we propose an alignment-free method for phylogenetic tree construction using whole-prote...
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There has been a growing interest in alignment-free methods for whole genome comparison and phylogenomic studies. In this study, we propose an alignment-free method for phylogenetic tree construction using whole-proteome sequences. Based on the inter-amino-acid distances, we first convert the whole-proteome sequences into inter-amino-acid distance vectors, which are called observed inter-amino-acid distance profiles. Then, we propose to use conditional geometric distribution profiles (the distributions of sequences where the amino acids are placed randomly and independently) as the reference distribution profiles. Last the relative deviation between the observed and reference distribution profiles is used to define a simple metric that reflects the phylogenetic relationships between whole-proteome sequences of different organisms. We name our method inter-amino-acid distances and conditional geometric distribution profiles (IAGDP). We evaluate our method on two data sets: the benchmark dataset including 29 genomes used in previous published papers, and another one including 67 mammal genomes. Our results demonstrate that the new method is useful and efficient.
As an important global geometric quantity, edge betweennesses can reflect the impact of corresponding edges in the entire network, which have a very strong practical significance. However, edge betweenness ignores the...
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At present, the software's type forms present diversity, and how to automatically analyze the software's risk behaviors become an urgent problem. This paper used some software behavior crawlers and dynamic ana...
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The AGM postulates are for the belief revision (revision by a single belief), and the DP postulates are for the iterated revision (revision by a finite sequence of beliefs). Li (The Computer Journal 50:378–390, 2007)...
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In this paper, we proposed a first-order discrete time nonlinear dynamic model of congestion control system with TCP LogWestwood+ (TCPLog) connections and random early detection (RED) gateway in high-speed wireless ne...
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Deep learning has recently shown outstanding performance on feature extraction. In this paper, we go one step further and address the problem of object tracking using a combination of Convolutional Neural Networks and...
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Differential Evolution (DE) algorithm is a kind of intelligent algorithm based on natural evolution over the past few decades, which shows better optimization performance on some classical benchmark problems. However,...
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