Artificial fish swarm algorithm-based power wireless private network base station planning method

Abstract

The invention provides an artificial fish swarm algorithm-based power wireless private network base station planning method. The method comprises the steps of mapping base station planning position information in a planning region to artificial fish position information in an artificial fish swarm algorithm, establishing a target function by integrating parameters in two aspects of a station establishment cost and a power distribution and utilization business coverage rate, and by calculating the target function, searching for and solving a global optimal target function value; and based on an optimized artificial fish swarm algorithm, by adjusting a visual field, a step distance and a motion mode of an artificial fish, based on the global optimum search, further accurately solving an optimal target function value, thereby obtaining an optimal planning scheme of power wireless private network base station planning, greatly simplifying the calculation process, and improving the accuracy. According to the artificial fish swarm algorithm-based power wireless private network base station planning method provided by the invention, the calculation accuracy and reliability are improved, the calculation efficiency is enhanced, and the construction cost is reduced.

Description

technical field [0001] The present invention relates to the technical field of electric power wireless private network construction, and more specifically, relates to a method for planning base stations of electric power wireless private network based on artificial fish swarm algorithm. Background technique [0002] At present, the power wireless communication network is an important part of realizing smart grid power distribution communication, which carries various services such as power grid production, dispatching, operation, management information and data collection. The base station planning work of the electric power wireless network is an indispensable part of the electric power communication system and has great significance. Traditional base station planning mainly relies on manual measurement, which consumes a lot of manpower and material resources. It is necessary to introduce efficient intelligent algorithms to replace tedious manual network planning. [0003]...

AI Technical Summary

Problems solved by technology

But this solution is only applicable to 3G network scenarios, and the scalability is poor

[0008] Compared with other intelligent optimization algorithms, the artificial fish swarm algorithm has the advantages of initial value, insensitive parameter selection, simple and easy implementation, overcoming local extremum, and strong robustness. The blindness is large, which seriously affects the performance and quality of the algorithm

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