For the adaptability of DDS (Data Distribution Service) to the demand of communication support for shipboard command and control system, this paper presents a series of evaluation criteria and methods to evaluate the ...
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It is really a challenging task to find the original video clip of a distorted duplicate among a large scale database efficiently since there are numerous variations between the original video and its copies. The diff...
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The key finding in the DNA double helix model is the specific pairing or binding between nucleotides A-T and C-G, and the pairing rules are the molecule basis of genetic code. Unfortunately, no such rules have been di...
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In order to distinguish and extract the topic information from other interferential information on the BBC news website for the study in social computing, the BBC News Hunter was proposed in this paper. The whole syst...
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A discrete artificial bee colony algorithm (DABC) is proposed for solving the permutation flow shop scheduling problem (PFSSP) with minimum makespan criterion. Firstly, the NEH heuristic was combined the random initia...
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ISBN:
(纸本)9781509035595
A discrete artificial bee colony algorithm (DABC) is proposed for solving the permutation flow shop scheduling problem (PFSSP) with minimum makespan criterion. Firstly, the NEH heuristic was combined the random initialization to the population for quality and diversity. Secondly, a new individual enhancement scheme is proposed to combine the swap, insert, inverse and adjacent exchange operation. Third, the fast local search is used to enhancing the individuals. Fourth, the pair-wise based local search is used to enhance the global optimal solution and escape from local minimum. Lastly, simulations and comparisons based on PFSSP benchmarks are carried out, which show that our algorithm is effectively and efficiently for solving the PFSSP.
Nowadays, discrete manufacturing enterprises are forced to reduce energy consumption owing to high energy cost, growing production demands, and environmental problems. An accurate energy consumption model is needed ur...
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Trust, as a major part of human interactions, plays an important role in helping users collect reliable infor-mation and make decisions. However, in reality, user-specified trust relations are often very sparse and fo...
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Trust, as a major part of human interactions, plays an important role in helping users collect reliable infor-mation and make decisions. However, in reality, user-specified trust relations are often very sparse and follow a power law distribution; hence inferring unknown trust relations attracts increasing attention in recent years. Social theories are frameworks of empirical evidence used to study and interpret social phenomena from a sociological perspective, while social networks reflect the correlations of users in real world; hence, making the principle, rules, ideas and methods of social theories into the analysis of social networks brings new opportunities for trust prediction. In this paper, we investigate how to exploit homophily and social status in trust prediction by modeling social theories. We first give several methods to compute homophily coe？cient and status coe？cient, then provide a principled way to model trust prediction mathe-matically, and propose a novel framework, hsTrust, which incorporates homophily theory and status theory. Experimental results on real-world datasets demonstrate the effectiveness of the proposed framework. Further experiments are conducted to understand the importance of homophily theory and status theory in trust prediction.
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