The Analysis of Knowledge Transfer Network Characteristic Based on Small-world Network Model
Bo Yang, XU Shenghua
Abstract
Bo Yang, XU Shenghua
Abstract
By analysising Small-world Network Model and its algorithm, we adopt agent adaptability modeling method of Complex Adaptive System and use Multi-Agent development language Netlogo to build simulation model based on Knowledge Transfer Network of Small-world. We use the average path length of Small-world Network Characteristic and clustering coefficient to stand for AC frequency and aggregation degree between network organizations' network nodes. Operating simulation model means Knowledge Transfer Network has evident Small-world Network Characteristic and confirms that under the condition of Small-world, the efficiency of Agent behavior and organization Knowledge Transfer can reach an upper high standard. It can offer theory director to construct adaptive knowledge communication between network organizations and changeable network construction.
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By analysising Small-world Network Model and its algorithm, we adopt agent adaptability modeling method of Complex Adaptive System and use Multi-Agent development language Netlogo to build simulation model based on Knowledge Transfer Network of Small-world. We use the average path length of Small-world Network Characteristic and clustering coefficient to stand for AC frequency and aggregation degree between network organizations' network nodes. Operating simulation model means Knowledge Transfer Network has evident Small-world Network Characteristic and confirms that under the condition of Small-world, the efficiency of Agent behavior and organization Knowledge Transfer can reach an upper high standard. It can offer theory director to construct adaptive knowledge communication between network organizations and changeable network construction.
Key concepts: Average path length, Small-world network, Computer science, NetLogo, Adaptability, Clustering coefficient, Knowledge transfer, Construct (python library)