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Functionality evaluation of system of systems architecture based on extended influence diagrams 被引量:1
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作者 ZHANG Mengmeng CHEN Honghui +2 位作者 ZHANG Xiaoxue LUO Aimin LIU Junxian 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2018年第3期510-518,共9页
System of systems architecture(SoSA) has received increasing emphasis by scholars since Zachman ignited its flame in 1987. Given its complexity and abstractness, it is critical to validate and evaluate SoSA to ensur... System of systems architecture(SoSA) has received increasing emphasis by scholars since Zachman ignited its flame in 1987. Given its complexity and abstractness, it is critical to validate and evaluate SoSA to ensure requirements have been met.Multiple qualities are discussed in the literature of SoSA evaluation, while research on functionality is scarce. In order to assess SoSA functionality, an extended influence diagram(EID) is developed in this paper. Meanwhile, a simulation method is proposed to elicit the conditional probabilities in EID through designing and executing SoSA. An illustrative anti-missile architecture case is introduced for EID development, architecture design, and simulation. 展开更多
关键词 system of systems architecture(SoSA) functionality evaluation extended influence diagram(EID) anti-missile architecture SIMULATION
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Improved clonal selection algorithm optimizing Neural Network for solving terminal anti-missile collaborative intercepting assistant decision-making model
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作者 Jinke Xiao Weimin Li Xinrong Xiao 《International Journal of Modeling, Simulation, and Scientific Computing》 EI 2017年第3期210-226,共17页
Programming terminal high-low collaborative intercepting strategy scientifically and constructing assistant decision-making model with self-determination and intellectualization is onekey problem to enhance operationa... Programming terminal high-low collaborative intercepting strategy scientifically and constructing assistant decision-making model with self-determination and intellectualization is onekey problem to enhance operational efficiency.Assistant decision-making model has been constructed after analysis on collaborative intercepting principle;then Improved Clonal Selection Algorithm Optimizing Neural Network(ICLONALGNN)is designed to solve the terminal anti-missile collaborative intercepting assistant decision-making model through introducing crossover operator to increase population diversity,introducing modified combination operator to make use of the information before crossover and mutation,introducing population update operator into traditional CLONALG to optimize Neural Network parameters.Experimental simulation confirms the superiority and practicability of the assistant decision-making model solved by ICLONALG-NN. 展开更多
关键词 Terminal anti-missile system collaborative intercepting assistant decisionmaking clonal selection algorithm neural network
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