Description: 在网络异常检测中,为了提高对异常状态的检测率，降低对正常状态的误判率,本文提出一种基于量子粒子群优化算法训练小波神经网络进行网络异常检测的新方法。利用量子粒子群优化算法(QPSO)训练小波神经网络,将小波神经网络(WNN)中的参数组合作为优化算法中的一个粒子,在全局空间中搜索具有最优适应值的参数向量。- In order to improve the detection rate for anomaly state and reduce the false positive rate for normal state in the network anomaly detection, a novel method of network anomaly detection based on constructing wavelet neural network (WNN) using quantum-behaved particle swarm optimization (QPSO) algorithm was proposed. The WNN was trained by QPSO. Platform: |
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Author:liang |
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Description: 此算法使用于单波段或者多波段图像中的非监督异常检测，性能很好~-The algorithm used in single-band or multi-band image unsupervised anomaly detection, performance very good ~ Platform: |
Size: 1024 |
Author:朱阳阳 |
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Description: 结合小波变换和香农定理，介绍了小波时间熵算法，并引用于信号异常检测中-Wavelet transform and the Shannon theorem, introduced the wavelet time entropy algorithm, and applied Signal Anomaly Detection Platform: |
Size: 256000 |
Author:jayzilong |
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Description: 异常检测和推荐系统的MATLAB实现案例，非常好的机器算法应用学习资料-MATLAB realization Case anomaly detection and recommendation system, a very good machine algorithm learning materials Platform: |
Size: 808960 |
Author:不错哦matlab |
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Description: Andrew Ng Cousera 机器学习 异常检测勇于服务器故障分析以及用于电影推荐的推荐系统的源代码和说明文档。(Andrew Ng Cousera's machine learning implement the anomaly detection algorithm and apply it to detect failing servers on a network. In the second part, you will use collaborative filtering to build a recommender system for movies.) Platform: |
Size: 1676288 |
Author:mark198033
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Description: 改进的遗传算法优化的BP神经网络，用于电厂数据的异常检测和故障诊断，已验证有效性。(The improved genetic algorithm optimized BP neural network has been validated for power plant data anomaly detection and fault diagnosis.) Platform: |
Size: 23231488 |
Author:十年12345
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Description: A deep one-class classification based method for the task of high-dimensional anomaly detection for large-scale applications.
This repository includes the code for the experiments carried out for the Master’s Thesis “Deep Support Vector Data Description” by Lukas Ruff, Humboldt University of Berlin.(A deep one-class classification based method for the task of high-dimensional anomaly detection for large-scale applications.) Platform: |
Size: 7081984 |
Author:刘晓颖 |
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