Evolution Model Based On Individual Attributes Of Human Social Groups Network

In order to explore the specific rules of interaction on the emergence of intelligent behavior in groups, inspired by social insects and social animals, put forward five basic rules of swarm intelligence, and each individual has four characteristics. They are simple function of the individuals. Their Collaboration Showed groups of intelligent behavior through mutual interaction. Such as perception, learning, making decision, mutual aid, these interactions between individuals show complex behavior because their own individual characteristics and the external environment. At the same time, individual differences in interactions also lead to the association within the group, which is a complex process. The behaviors of top-down of these complex individuals, Show the emergence of swarm intelligence behavior.This paper was base on the complexity of the individual properties between human social groups, started from the perspective of complex network topology evolution, with specific human perception and interaction help in social groups, introduced Mahalanobis distance, and established the evolution network models for the appropriate social groups. Specific research was divided into three parts. The first part: introduced node attributes comprehensive fitness social structure in the study of social structure, targeted to determine the nodes network level in the network of social networks. The second part: in the perception evolving network model, studied the differences between the nodes from different dimensions, introduced node dimension attribute fitness, established network priority connection mechanism based on Mahalanobis distance, discussed influence on network evolution parameters with combination some specific factors, such as specific dimensions of property factor weights, preferential attachment probability threshold, property factor weights associated threshold. The last part in the helping network evolution model, firstly, combining the principle of the strong help the weak, based on the performance of the size of node attributes comprehensive fitness, determined the helping connected local world, secondly, established network priority connection mechanism according to Mahalanobis distance, analyzed the internal and external standards model of statistical parameters, and compared the two models the difference in standards.Researched the characteristics of complex behavior of human groups, the innovation of this research did not extracted a number of rules of conduct from the perspective of group characteristics, but showed the performance of their individual complexity by directly dimension attribute, based on interaction with the dimension attribute, converted into an interactive rules. So could study the group complex behaviors from the complexity of the individual properties dimensions and properties association.