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根据演化要求,运用人工神经网络理论,从个体特征、连接结构以及学习规则三个方面确定了信息个体到群体演化的形成要素,然后通过输出函数确定出需要的信息个体;在节点吸引力的作用下,完成了信息个体复制过程;最后大量的信息个体在学习规则的作用下会逐渐储存,最终形成了信息群体。上述过程有助于推动网络信息生态链由无序、低效、不稳定的状态向有序、高效、稳定的状态演变,为网络信息生态链的模拟仿真和实证分析提供参考。
According to the evolutionary requirements, using artificial neural network theory, the forming elements of information individual to group evolution are determined from three aspects: individual characteristics, connection structure and learning rules, and then the output information is used to determine the necessary information individuals. At node attraction, , Complete the process of individual copying information; the last a large number of individual information in the role of learning rules will be gradually stored, and ultimately formed a message group. The above process helps to promote the evolution of the network information chain from disorder, inefficiency and instability to an orderly, efficient and stable state, providing reference for the simulation and empirical analysis of the network information ecosystem.