Power grid safety monitoring method and system based on neural network, and electronic equipment
The invention provides a power grid safety monitoring method and system based on a neural network and electronic equipment. The method comprises the following steps: acquiring various initial data generated in the operation and management process of a power enterprise; performing word segmentation o...
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| creator | CHEN ZHAOLI ZHANG LIYUAN WEI ZONGHUI MENG QI DONG YUN YIN YUAN AI XUHUA ZHANG XIXIANG TAN QIWEN XIE JING MENG CHUNZHI TAO SIHENG ZHOU DIGUI MENG CHUNCHEN GU ZHEDE CHEN YANYAN TAN NING |
| description | The invention provides a power grid safety monitoring method and system based on a neural network and electronic equipment. The method comprises the following steps: acquiring various initial data generated in the operation and management process of a power enterprise; performing word segmentation on each piece of initial data to obtain a three-dimensional feature matrix corresponding to each piece of initial data; inputting the three-dimensional feature matrix corresponding to each piece of initial data into a recurrent neural network model to obtain a security feature corresponding to each piece of initial data; and obtaining the security level of each piece of initial data according to the security feature corresponding to each piece of initial data, the desensitization feature of each piece of initial data and the encryption feature of each piece of initial data, and performing security monitoring on each piece of initial data according to the security level of each piece of initial data. According to the |
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The method comprises the following steps: acquiring various initial data generated in the operation and management process of a power enterprise; performing word segmentation on each piece of initial data to obtain a three-dimensional feature matrix corresponding to each piece of initial data; inputting the three-dimensional feature matrix corresponding to each piece of initial data into a recurrent neural network model to obtain a security feature corresponding to each piece of initial data; and obtaining the security level of each piece of initial data according to the security feature corresponding to each piece of initial data, the desensitization feature of each piece of initial data and the encryption feature of each piece of initial data, and performing security monitoring on each piece of initial data according to the security level of each piece of initial data. 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The method comprises the following steps: acquiring various initial data generated in the operation and management process of a power enterprise; performing word segmentation on each piece of initial data to obtain a three-dimensional feature matrix corresponding to each piece of initial data; inputting the three-dimensional feature matrix corresponding to each piece of initial data into a recurrent neural network model to obtain a security feature corresponding to each piece of initial data; and obtaining the security level of each piece of initial data according to the security feature corresponding to each piece of initial data, the desensitization feature of each piece of initial data and the encryption feature of each piece of initial data, and performing security monitoring on each piece of initial data according to the security level of each piece of initial data. 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The method comprises the following steps: acquiring various initial data generated in the operation and management process of a power enterprise; performing word segmentation on each piece of initial data to obtain a three-dimensional feature matrix corresponding to each piece of initial data; inputting the three-dimensional feature matrix corresponding to each piece of initial data into a recurrent neural network model to obtain a security feature corresponding to each piece of initial data; and obtaining the security level of each piece of initial data according to the security feature corresponding to each piece of initial data, the desensitization feature of each piece of initial data and the encryption feature of each piece of initial data, and performing security monitoring on each piece of initial data according to the security level of each piece of initial data. According to the</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRIC DIGITAL DATA PROCESSING PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Power grid safety monitoring method and system based on neural network, and electronic equipment |
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