光通信研究Issue(4)：115-122,8.DOI:10.13756/j.gtxyj.2026.250285
多维度量化的光网络智能化能力评测方法
Multidimensional Quantitative Evaluation Method for Intelligent Capability of Optical Networks
摘要
Abstract
[Objective]To address the issue that traditional evaluation methods struggle to quantitatively assess Artificial Intelligence(AI)-driven autonomous capabilities in the intelligent evolution of optical networks,this paper proposes a multi-dimensional intelligent capability evaluation method.This method aims to resolve core problems such as the insufficient adaptability of static evaluation mechanisms in dynamic service scenarios and poor cross-vendor compatibility.[Methods]The paper designs an optical network Capability Maturity Index(CMI)by constructing a three-level indicator system of'infrastructure-algorithm-application',and integrates a dynamic weight adjustment mechanism to achieve precise quantification.Firstly,we establish an evaluation model that includes 9 core indicators such as optical layer programmability and fault self-healing rate,and innovatively introduce the dimension of knowledge generalization ability.Then,an online weight adjustment algorithm based on Long Short Term Momery(LSTM)is proposed.It is combined with a sliding window mechanism to achieve environment adaptation.Finally,a distributed evaluation system was developed and validated through a simulation platform(OMNeT++simulating a 12 node topology)and a multi vendor network in the laboratory.Typical faults such as fiber breakage and wavelength conflicts were considered for comparative analysis.[Results]The experiment showed that the dynamic weighting mechanism can reduce the volatility of evaluation results by 42%,and the fault localization time(2.73±0.41 s)was reduced by 44.5%compared to traditional methods.The optimization of resource allocation latency is 38.6 ms,which is reduced by 51%.The fault missed detection rate in a cross vendor environment is only 0.8%,which is better than the static weight method(5.7%)and the traditional Telecommunications Management Network(TMN)method(23.6%).The stability of CMI index in sudden traffic scenarios reaches±0.11,meeting the threshold requirement of±0.15.[Conclusion]This method significantly improves the accuracy and environmental adaptability of intelligent evaluation of optical networks through hierarchical quantization and dynamic weighting mechanism.It provides a standardized evaluation tool for device selection and technological evolution.In the future,further integration of digital twin technology is needed to enhance the ability to emulate the physical layer disturbances.关键词
光网络/智能化能力评测/动态权重调整/能力成熟度指数Key words
optical network/intelligent capability evaluation/dynamic weight adjustment/CMI分类
信息技术与安全科学引用本文复制引用
孟海军..多维度量化的光网络智能化能力评测方法[J].光通信研究,2026,(4):115-122,8.基金项目
工信部制造业专项资助项目(125) （125）
