基于机器学习的网络故障诊断优化算法

Network Fault-Diagnosis Optimization Algorithm Based on Machine Learning

随着网络的广泛应用,网络故障已成为影响用户体验和业务连续性的主要挑战之一。研究基于机器学习的网络故障诊断优化算法,旨在提高网络故障诊断的准确性和效率。该算法采用深度神经网络(Deep Neural Networks,DNN)模型,通过数据预处理、特征工程、网络故障诊断模型建立等步骤,并模拟真实网络环境进行实验验证,证明了其有效性和可行性。

With the widespread application of networks,network failures have become one of the main challenges affecting user experience and business continuity.The optimization algorithm for network fault diagnosis based on machine learning is studied to improve the accuracy and efficiency of network fault diagnosis.This algorithm adopts Deep Neural Networks(DNN)model,through data preprocessing,feature engineering,network fault diagnosis model establishment amd other steps,and simulates real network environment to verify its effectiveness and feasibility.