The present work is concerned with determining the viscosity,diffusion,thermal diffusion factor and thermal conductivity of five equimolar binary gas mixtures including:CF4-He,CF4-Ne,CF4-Ar,CF4-Kr,CF4-Xe from the prin...The present work is concerned with determining the viscosity,diffusion,thermal diffusion factor and thermal conductivity of five equimolar binary gas mixtures including:CF4-He,CF4-Ne,CF4-Ar,CF4-Kr,CF4-Xe from the principle of corresponding states of viscosity by the inversion technique.The Lennard-Jones (12-6) model potential is used as the initial model potential.The calculated interaction potential energies obtained from the inversion procedure is employed to reproduce the viscosities,diffusions,thermal diffusion factors,and thermal conductivities.The accuracies of the calculated viscosity and diffusion coefficients were 1% and 4%,respectively.展开更多
It is necessary for mine countermeasure systems to recognise the model of a water mine before destroying because the destroying measures to be taken must be determined according to mine model. In this paper, an immune...It is necessary for mine countermeasure systems to recognise the model of a water mine before destroying because the destroying measures to be taken must be determined according to mine model. In this paper, an immune neural network (INN) along with water mine model recognition system based on multi-agent system is proposed. A modified clonal selection algorithm for constructing such an INN is presented based on clonal selection principle. The INN is a two-layer Boolean network whose number of outputs is adaptable according to the task and the affinity threshold. Adjusting the affinity threshold can easily control different recognition precision, and the affinity threshold also can control the capability of noise tolerance.展开更多
The intelligent vehicle network uses advanced information technology to establish an efficient integrated vehicle transport system, which has received great attention in industry and academia, lnternet of Vehicles （...The intelligent vehicle network uses advanced information technology to establish an efficient integrated vehicle transport system, which has received great attention in industry and academia, lnternet of Vehicles （loV） in an urban environment is operated in a wireless environment with high bit error rate and interference. In addition, the wireless link between vehicles is likely to be lost. All of this makes it an important challenge to provide reliable mobile routing in an urban traffic environment. In this paper, a reliable routing algorithm with network coding （RR_ NC） is proposed to solve the above problems. A routing node sequence is discovered in IoV from source to destination by multi-metric ant colony optimization algorithm （MACO）, and then clusters are formed around every node in the sequence. By adding linear encoding into the transmission of data between vehicle＇s clusters, the RR_NC provides much more reliable transmission and can recover the original message in the event of disorder and loss of message. Simulations are taken under different scenarios, and the results prove that this novel algorithm can deliver the information more reliably between vehicles in real-time with lower data loss and communication overhead.展开更多
基金Research Committees of Shiraz University and Shiraz University of Technology for supporting this project and making computer facilities available
文摘The present work is concerned with determining the viscosity,diffusion,thermal diffusion factor and thermal conductivity of five equimolar binary gas mixtures including:CF4-He,CF4-Ne,CF4-Ar,CF4-Kr,CF4-Xe from the principle of corresponding states of viscosity by the inversion technique.The Lennard-Jones (12-6) model potential is used as the initial model potential.The calculated interaction potential energies obtained from the inversion procedure is employed to reproduce the viscosities,diffusions,thermal diffusion factors,and thermal conductivities.The accuracies of the calculated viscosity and diffusion coefficients were 1% and 4%,respectively.
文摘It is necessary for mine countermeasure systems to recognise the model of a water mine before destroying because the destroying measures to be taken must be determined according to mine model. In this paper, an immune neural network (INN) along with water mine model recognition system based on multi-agent system is proposed. A modified clonal selection algorithm for constructing such an INN is presented based on clonal selection principle. The INN is a two-layer Boolean network whose number of outputs is adaptable according to the task and the affinity threshold. Adjusting the affinity threshold can easily control different recognition precision, and the affinity threshold also can control the capability of noise tolerance.
基金supported by the Science and Technology Development Fund(No.037/2015/A1),Macao SAR,China
文摘The intelligent vehicle network uses advanced information technology to establish an efficient integrated vehicle transport system, which has received great attention in industry and academia, lnternet of Vehicles （loV） in an urban environment is operated in a wireless environment with high bit error rate and interference. In addition, the wireless link between vehicles is likely to be lost. All of this makes it an important challenge to provide reliable mobile routing in an urban traffic environment. In this paper, a reliable routing algorithm with network coding （RR_ NC） is proposed to solve the above problems. A routing node sequence is discovered in IoV from source to destination by multi-metric ant colony optimization algorithm （MACO）, and then clusters are formed around every node in the sequence. By adding linear encoding into the transmission of data between vehicle＇s clusters, the RR_NC provides much more reliable transmission and can recover the original message in the event of disorder and loss of message. Simulations are taken under different scenarios, and the results prove that this novel algorithm can deliver the information more reliably between vehicles in real-time with lower data loss and communication overhead.
