Research On Multi-agent Knowledge-Syncretism Process Based On The Neural Network

With the continuous development of the global knowledge economy,the core competitiveness that business organizations rely on to survive in the market environment is increasingly tilted toward technology innovation,and their organizations are gradually turning to the center of knowledge to carry out various activities.Under normal circumstances,the higher the level of integration of the knowledge flow in the region,the greater the knowledge innovation capability of the innovation subject is,and the more sensitive the response of the innovation entity to the incremental knowledge innovation in the region.In the specific corporate competitive environment,the competition model among enterprises has increasingly shifted from the former rivalry compete to the present-day cooperation and competition,and in this way,knowledge alliances have been constructed so that all enterprises cooperate in competition and competition in cooperation.The knowledge alliance model established between enterprises not only can effectively reduce the company's joint management risk,improve the efficiency of knowledge blending,but also can promote every company in the alliance to achieve innovative progress.As the basis and platform for regional innovation,the multi-agent innovation system is a set of knowledge symbiosis that encompasses multiple innovation nodes and their associated application nodes.The essence of the multi-subject innovation process is the selfimprovement process of the information organization system based on the endowment of the innovation node's own knowledge.The need for collaborative innovation processes to improve the structural constraints of innovation networks,and their desire for heterogeneous knowledge elements,objectively requires knowledge exchange and integration among innovative entities.The innovation node in the regional multi-agent innovation system is similar to the neural network in the neural network.The dynamic collaboration process among the various innovation nodes has significant information processing characteristics such as significant nonlinearity,self-adaptability,fault self-tolerance,analyze and design consistency.This study explores and analyzes the connection mechanism of innovation nodes and knowledge transfer,and describes the process of knowledge node conduction and knowledge flow state transition in the innovation node.In the knowledge innovation network,the constraint mechanism between the innovation nodes is the basis for the equilibrium of the node's main interests and risks,and it is also a necessary condition for the integration of knowledge transfer between nodes.This study first elaborated the research background,research purpose and research significance of the innovation network,and made clear research ideas and possible research methods.Secondly,the current research dynamics of knowledge flow control and technology,fusion technology and neural network theory are elaborated,and the current theoretical and practical research on innovation network is combed.Innovate the knowledge flow and knowledge flow relationship between network nodes,and analyze the constraint characteristics of node innovation.Then,it focuses on analyzing the knowledge-incentiveincentive relationship of knowledge transfer in the innovation process.Based on this,it builds the relationship model of node knowledge transfer in the innovation process and analyzes the general knowledge innovation under the multi-agent system by setting and adjusting related parameters.The process defines the preconditions or key influencing factors for inter-subject knowledge innovation cooperation.Finally,the process of choosing the main path of the innovation of the innovation is expounded,and the examples are applied to analyze the examples.