摘要
Multi-living agent system （MLAS） is a new concept in the field of complex system research, which is peculiarly suitable for the design and analysis of a complex information system in a serious confrontation and tight constraint environment. However, the universal method to quantitatively measure the living degree of an MLAS remains uncertain, which is critical to the self-organizing process. Therefore, a novel analytic hierarchy process （AHP） based method with dependent pairwise comparison matrix （PCM） for the evaluation of living degree of the MLAS is proposed, which eliminates the shortcoming of fixed PCM in traditional process. Furthermore, to avoid the annoying procedure of the consistency validation, the PCMs are appropriately reconstructed. Through an illustration of the netted radar system, the calculation detail is explicitly presented. Altogether, the advanced evaluation method successfully accomplishes the preset objective and promotes the development of the MLAS theory and AHP as well.
Multi-living agent system （MLAS） is a new concept in the field of complex system research, which is peculiarly suitable for the design and analysis of a complex information system in a serious confrontation and tight constraint environment. However, the universal method to quantitatively measure the living degree of an MLAS remains uncertain, which is critical to the self-organizing process. Therefore, a novel analytic hierarchy process （AHP） based method with dependent pairwise comparison matrix （PCM） for the evaluation of living degree of the MLAS is proposed, which eliminates the shortcoming of fixed PCM in traditional process. Furthermore, to avoid the annoying procedure of the consistency validation, the PCMs are appropriately reconstructed. Through an illustration of the netted radar system, the calculation detail is explicitly presented. Altogether, the advanced evaluation method successfully accomplishes the preset objective and promotes the development of the MLAS theory and AHP as well.
基金
supported by the National Natural Science Foundation of China(61172176)
作者简介
Shengheng Liu was born in 1987. He was admitted to the graduate school direct to the Ph.D, program from the B.S. degree, by passing the M.S. degree without qualification examination in Beijing Institute of Technology in 2010. His research interests include radar signal processing and complex information system theory. E-mail： henry@bit.edu.cnCorresponding author.Tao Shah was born in 1969. He received his Ph.D. degree from Beijing Institute of Technology in 2004, and now he is an associate professor. His research interests are radar signal processing and complex information system theory. E-mail： shantao@bit.edu.cnRan Tao was born in 1964. He received his Ph.D. degree from Harbin Institute of Technology in 1993. In 2001, he was a senior visiting scholar in the University of Michigan, Ann Arbor. And now he is a professor in Beijing Institute of Technology, His research interests include signal processing and complex information system theory. E-mail： rantao@bit.edu.cnYue Wang was born in 1932. He is an academician of both Chinese Academy of Science and Chinese Academy of Engineering. He was the president of Beijing Institute of Technology from 1993 to 1999. His research interests are radar signal processing, complex system theory and information countermeasure.
