Business process guided self-learning optimization algorithm

Abstract

The invention provides a business process guided self-learning optimization algorithm, which specifically comprises the following steps of: firstly, organizing and self-adapting an algorithm based ona mining mode according to a similarity process category division algorithm driven by comprehensive knowledge and a classification business operation mode of joint learning; and solving the self-adaption problem of each business process on the basis of the mining mode; secondly, based on a global business process intelligent guiding algorithm of operation graph and data aggregation, according to an operation graph and data aggregation algorithm of a common coupling neural network, a business process intelligent guiding algorithm of complex graph structure shortest path optimization and a centrality algorithm of a hierarchical network constructed by a graph network; and finally, completing flow self-learning optimization based on full-link multi-dimensional data composite guidance through guide environment construction processing based on intelligent edges and background large-center full-link multi-dimensional data and in combination with deep reinforcement learning. The algorithm canshield unnecessary business fields and realize point-to-point business guidance by taking the task as a destination.

Description

technical field [0001] The invention belongs to the technical fields of business process understanding, process division, business operation mode mining guidance, and self-adaptive organization of business processes, and in particular relates to a business process guidance self-learning optimization algorithm. Background technique [0002] Now for large-scale business networks, there are a large number of similar business processes and functional classification categories, and it is necessary to understand the process, process division and other processing procedures. In addition, in order to control the length of business links, shield unnecessary business areas, and realize task-oriented point-to-point business guidance and shortest path optimization business process guidance, there are the following problems: (1) Mining business processes is cumbersome, The mining mode is relatively single, which consumes a lot of manpower, material resources and financial resources; (2) ...

AI Technical Summary

Problems solved by technology

In addition, in order to control the length of business links, shield unnecessary business areas, and realize task-oriented point-to-point business guidance and shortest path optimization business process guidance, there are the following problems: (1) Mining business processes is cumbersome, The mining mode is relatively single, which consumes a lot of manpower, material resources and financial resources; (2) Due to the separation of business operations from data and knowledge, the business process is time-consuming and labor-intensive, the staff learning curve is extremely steep, and the number of times users are involved in the business loop is too much.

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