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IDC\u7f51\u7edc\u8d28\u91cf\u8bc4\u4f30\u7cfb\u7edf <\/strong>[\u8be6\u60c5<\/a>]<\/p>\n\n\n\n

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\u83b7\u5956<\/h2>\n\n\n\n

2018\u5e74\u5ea6\u4e2d\u56fd\u77f3\u6cb9\u548c\u5316\u5de5\u81ea\u52a8\u5316\u5e94\u7528\u534f\u4f1a \u79d1\u6280\u8fdb\u6b65\u5956 \u4e8c\u7b49\u5956 \u201c\u67f4\u6cb9\u52a0\u6c22\u88c5\u7f6e\u8150\u8680\u6cc4\u6f0f\u9884\u6d4b\u9884\u8b66\u7814\u7a76\u53ca\u5e94\u7528\u201d \uff08\u5f90\u9e4f\u6392\u540d\u7b2c\u4e00\uff09<\/p>\n\n\n\n

\u8bba\u6587<\/h2>\n\n\n\n

\u5728\u5927\u6570\u636e\u6280\u672f\u4e0e\u5e94\u7528\u7814\u7a76\u4e2d\uff0c\u56e2\u961f\u7684\u8bba\u6587\u6210\u679c\u805a\u7126\u7cfb\u7edf\u72b6\u6001\u8bc4\u4f30\u3001\u5f02\u5e38\u68c0\u6d4b\u4e0e\u9884\u6d4b\u3001\u5f02\u5e38\u6839\u56e0\u5206\u6790\u7b49\u65b9\u5411\uff0c\u4e5f\u6709\u51e0\u7bc7\u4f20\u7edfNLP\u548c\u56fe\u50cf\u5904\u7406\u65b9\u5411\u7684\u8bba\u6587\u6210\u679c\u3002<\/p>\n\n\n\n

XU P, GAO Q H, ZHANG Z B, et al. Multi-source data based anomaly detection through temporal and spatial characteristics[J]. Expert Systems with Applications, 2024, 237: 121675.<\/p>\n\n\n\n

XU P, GAN H L, FU H, et al. STEAMCODER: Spatial and Temporal Adaptive Dynamic Convolution Autoencoder for Anomaly Detection[J]. Knowledge-Based Systems, 2023, 279: 110929.<\/p>\n\n\n\n

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XU P, DU R, ZHANG Z B. Predicting pipeline leakage in petrochemical system through GAN and LSTM[J]. Knowledge-Based Systems, 2019, 175: 50-61.<\/p>\n\n\n\n

ZHANG A Y, XU P. Practised: Pattern-based representation alignment for cross-domain time series anomaly detection[C]\/\/ECAI 2025. Amsterdam: IOS Press, 2025: 2291-2298.<\/p>\n\n\n\n

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XU P, CHEN D L, LIU X, et al. Image-based Dietary Assessment System for Chinese Children[C]\/\/2018 IEEE International Conference on Big Data (Big Data). New York: IEEE, 2018: 5471-5473.<\/p>\n\n\n\n

\u4e13\u5229<\/h2>\n\n\n\n

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