Optical cable laying plan generation method, device, equipment and storage medium

By acquiring engineering information and using a pre-built laying method decision model and a hybrid genetic algorithm to optimize the optical cable laying plan, the problems of long design cycle and lack of personalization in traditional methods are solved, and efficient and accurate optical cable laying plan generation is achieved.

CN120562083BActive Publication Date: 2025-09-30FOSHAN ELECTRIC POWER DESIGN INSTITUTE CO LTD
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Patent Information

Application Number
CN202511053059.1
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-07-30
Publication Date
2025-09-30
Estimated Expiration
2045-07-30

AI Technical Summary

Technical Problem

Traditional optical cable design methods rely on engineers' experience, resulting in long design cycles, large manual calculation errors, inability to achieve personalized optimization, and the risk of optical cables being affected by geological disasters in complex terrain.

Method used

By obtaining engineering information, preprocessing it and converting it into input feature vectors, the optical cable laying plan is optimized using a pre-built laying method decision model and a hybrid genetic algorithm. Combined with geographical characteristics and cost correction factors, an objective function is constructed and the optical fiber information is solved to generate a personalized optical cable laying plan.

Benefits of technology

Significantly shorten the design cycle, reduce manual intervention, achieve personalized optimization of road sections, improve planning efficiency and solution accuracy, and reduce maintenance costs and network interruption risks.

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Abstract

The present invention relates to the field of data processing technology, and in particular to a method, device, equipment and storage medium for generating an optical cable laying plan. The method comprises: processing engineering information to extract road section information; converting the road section information into a feature vector and inputting the feature vector into a laying method decision model to determine the laying method; determining whether to correct the laying method based on feature labels included in the road section information, and obtaining a cost correction coefficient if no correction is required; constructing an objective function and constraint conditions; solving the objective function using a hybrid genetic algorithm to obtain optical fiber information; integrating road section information, laying methods and optical fiber information to generate an optical cable laying plan; the method disclosed in the present application can automatically process engineering information to quickly obtain road section information, significantly shorten the design cycle to several days, reduce manual intervention, and improve planning efficiency; in addition, by constructing feature vectors and decision models, personalized optimization of road section laying is achieved to ensure accurate adaptation of the plan.
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