Portable electronic communication data intelligent processing system based on artificial intelligence

Abstract

The invention discloses a portable electronic communication data intelligent processing system based on artificial intelligence, and relates to the field of data processing, and the system comprises an intelligent data processing platform which comprises a data collection module, a data analysis module, a transmission management module, a data processing module, an interaction management module and a data transmission module; the data acquisition module acquires electronic communication data and transmission state data; the data analysis module obtains communication characteristic data corresponding to the electronic communication data; the transmission management module generates a real-time transmission monitoring shared graph according to the transmission state data; the data processing module carries out encoding processing on the electronic communication data according to the real-time transmission monitoring shared graph and the communication characteristic data to generate initial transmission encoding information; the interaction management module carries out real-time adjustment according to the initial transmission coding information to obtain preferable transmission coding information; the data transmission module is used for transmitting the preferable transmission coding information; according to the invention, the security and transmission efficiency of electronic communication data are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly to an intelligent processing system for portable electronic communication data based on artificial intelligence. Background Art

[0002] With the rapid development of technology, portable electronic communication devices have become an indispensable tool in people's daily life and work, and the popularization of portable electronic communication devices has made information exchange between people more portable and efficient; however, with the widespread use of portable electronic communication devices, the quantity of communication data has increased rapidly, and it has characteristics such as high dynamics and diversity; therefore, how to efficiently process the corresponding communication data has become an important challenge faced currently.

[0003] After retrieval, the invention patent with Chinese patent number CN104618322A discloses a data processing method and device based on an instant messaging tool. The method includes the following steps: obtaining invitation content, the instant messaging identifier and identity information of the invitation initiator; generating an invitation request message including the invitation content, the instant messaging identifier and identity information of the invitation initiator; sending the invitation request message to other instant messaging identifiers or instant messaging group identifiers associated with the instant messaging identifier through the instant messaging tool; receiving a response message generated by other instant messaging identifiers or instant messaging group identifiers as invitation responders to the invitation request message; generating an electronic voucher including the invitation content, the instant messaging identifier of the invitation initiator, and the instant messaging identifier or instant messaging group identifier of the invitation responder according to the response message. For the above data processing method and device based on an instant messaging tool, the electronic voucher information can be used as a data traceability voucher, improving the security of the data.

[0004] Compared with the prior art, the invention patent with Chinese patent number CN104618322A can set an electronic voucher through corresponding invitation request messages and response messages of invitation responders, and improve the security and traceability of data information through the corresponding electronic voucher; However, in the actual use process of the above method, only a single type of electronic voucher is generated as the corresponding data traceability voucher, which to a certain extent affects the security and transmission efficiency of data information. Summary of the Invention

[0005] The objective of the present invention is to solve the problems of low security and low transmission efficiency existing in the prior art, and propose an intelligent processing system for portable electronic communication data based on artificial intelligence.

[0006] To achieve the above objective, the present invention adopts the following technical solutions: An artificial intelligence-based intelligent processing system for portable electronic communication data, including an intelligent data processing platform, wherein a data acquisition module, a data analysis module, a transmission management module, a data processing module, an interaction management module, and a data transmission module are provided in the intelligent data processing platform; The data acquisition module is used to acquire the electronic communication data corresponding to the corresponding portable electronic communication device and the transmission status data corresponding to the corresponding data transmission device; The data analysis module is used to classify and process the corresponding electronic communication data, and sequentially perform quantization processing and clustering analysis according to the classification processing results to obtain the communication feature data corresponding to the electronic communication data; The transmission management module is used to analyze and process the obtained transmission status data to generate a real-time transmission monitoring and sharing graph; The data processing module is used to encode the corresponding electronic communication data according to the real-time transmission monitoring and sharing graph and the corresponding communication feature data to generate initial transmission coding information; The interaction management module is used to perform transmission interaction evaluation on the corresponding initial transmission coding information according to the real-time transmission monitoring and sharing graph, and perform real-time adjustment on the initial transmission coding information according to the evaluation results to obtain optimal transmission coding information; The data transmission module is used to select a corresponding data transmission path according to the obtained optimal transmission coding information and the corresponding real-time transmission monitoring and sharing graph to complete the corresponding data transmission.

[0007] The above technical solution further includes: The process of collecting electronic communication data and transmission status data includes: A communication collection unit and a transmission collection unit are set; The communication collection unit is used to collect the electronic communication data corresponding to the corresponding portable electronic communication device; The transmission collection unit is used to collect the transmission status data corresponding to the corresponding data transmission device, and the transmission status data includes the electronic transmission status data set in the portable electronic communication device and the platform transmission status data corresponding in the intelligent data processing platform.

[0008] Further, the process of classifying and processing electronic communication data includes: Obtain a historical electronic communication data set, respectively perform marking processing on different types of historical electronic communication data in the historical electronic communication data set, and generate a historical electronic communication data subset according to the marking processing results; Respectively perform feature extraction on each historical electronic communication data subset to obtain the classification feature data corresponding to each historical electronic communication data subset, set a classification evaluation standard according to the obtained classification feature data, and generate a classification evaluation axial link according to the classification evaluation index; Traverse the classification evaluation indicators in the corresponding classification evaluation axial link for the obtained electronic communication data in sequence, and obtain the classification results corresponding to the corresponding electronic communication data.

[0009] Further, the process of obtaining the communication feature data corresponding to the electronic communication data includes: Perform sampling processing according to the classification results corresponding to the electronic communication data, set the mapping quantization chart corresponding to the corresponding data type, obtain communication sample data, perform quantization analysis on the obtained communication sample data according to the corresponding classification results, and map the obtained quantization analysis results into the corresponding mapping quantization chart to obtain a finite number of discrete values corresponding to the communication sample data; Generate a communication sample signal according to the obtained values, and obtain the corresponding quantization feature data according to the communication sample signal; Perform similarity analysis on the historical quantization feature data, perform associative cyclic sorting on the historical quantization feature data according to the similarity analysis results, connect the head and tail according to the associative cyclic sorting results, construct a quantization clustering map, and set the corresponding cyclic feature nodes; Compare and analyze the obtained quantization feature data with each cyclic feature node in the quantization clustering map in sequence to obtain the position information and communication occupancy data of the quantization feature data belonging to the quantization clustering map; Obtain the communication feature data corresponding to the corresponding electronic communication data according to the obtained communication occupancy data and the corresponding position information.

[0010] Further, the process of generating a real-time transmission monitoring sharing map includes: Obtain transmission status data, and perform analysis and processing on the electronic transmission status data and the platform transmission status data respectively; Obtain the transmission mode types corresponding to each transmission status data, set transmission monitoring nodes according to the corresponding transmission mode types, where the transmission monitoring nodes are used to analyze and process the transmission status data corresponding to the corresponding transmission mode types, obtain the corresponding transmission monitoring data, and perform visual analysis on the obtained transmission monitoring data; Set an equipment transmission monitoring image and a platform transmission monitoring image respectively according to the visual analysis results of the transmission monitoring data corresponding to the electronic transmission status data and the platform transmission status data; Generate a corresponding real-time transmission monitoring sharing map from the equipment transmission monitoring image and the platform transmission monitoring image.

[0011] Further, the process of generating the initial transmission coding information includes: Obtain the historical transmission monitoring shared graph and the historical optimal transmission coding information, construct a transmission coding data set of the transmission monitoring data regarding the corresponding electronic communication data coding process of the corresponding communication feature data according to the corresponding historical transmission monitoring data and the corresponding historical optimal transmission coding information, set the transmission coding correlation coefficient according to the obtained transmission coding data set, and integrate the obtained transmission coding correlation coefficients to construct a transmission coding association graph; Obtain the transmission monitoring data corresponding to each transmission mode type in the corresponding device transmission monitoring image in the real-time transmission monitoring shared graph, perform sorting analysis on the transmission monitoring data, and sequentially obtain the transmission coding correlation coefficients corresponding in the corresponding transmission coding association graph according to the sorting analysis results; Obtain the communication feature data corresponding to the electronic communication data, perform segmentation processing on the electronic communication data according to the communication feature data to obtain the corresponding communication segmented data, perform coding processing on the obtained communication segmented data respectively based on the transmission coding correlation coefficients obtained for the corresponding transmission mode types to obtain the corresponding segmented transmission coding information, and integrate the obtained segmented transmission coding information to generate the initial transmission coding information.

[0012] Further, the process of obtaining the optimal transmission coding information includes: Obtain the initial transmission coding information corresponding to the sorting analysis result of the transmission mode types in the device transmission monitoring image, combine the transmission monitoring data corresponding to each transmission mode type in the device transmission monitoring image and the platform transmission monitoring image to perform transmission interaction evaluation on the transmission process of the obtained initial transmission coding information, obtain the corresponding transmission evaluation data for the corresponding transmission mode type, and obtain the optimal transmission mode type according to the obtained transmission evaluation data; Re-obtain the corresponding transmission coding correlation coefficients for the obtained initial transmission coding information according to the obtained optimal transmission mode type, perform real-time adjustment on the initial transmission coding information according to the transmission coding correlation coefficients, and obtain the corresponding optimal transmission coding information according to the adjustment result.

[0013] Further, the process of performing data transmission on the optimal transmission coding information includes: Obtain the optimal transmission coding information corresponding to the corresponding electronic communication data and the corresponding optimal transmission mode type; Set the data transmission path according to the transmission monitoring data of the data transmission devices corresponding to each transmission mode type in the device transmission monitoring image and the platform transmission monitoring image, and perform data transmission on the optimal transmission coding information corresponding to the electronic communication data according to the data transmission path.

[0014] The present invention has the following beneficial effects: 0. In the present invention, by classifying the obtained electronic communication data and analyzing and processing according to the classification result, corresponding communication feature data is obtained. Based on the communication feature data, the corresponding electronic communication data is encoded, which to a certain extent avoids the low data transmission efficiency and low encoding security caused by a single encoding method.

[0015] 1. In the present invention, the process of encoding electronic communication data by using the transmission status data of corresponding data transmission devices in portable electronic communication devices and intelligent data processing platforms is flexibly adjusted, and a corresponding suitable data transmission path is selected, so that the data transmission device can dynamically adjust the encoding method corresponding to the transmission mode type according to the real-time communication status, thereby increasing the transmission efficiency and dynamic adjustability between portable electronic devices. Brief Description of the Drawings

[0016] Figure 1 It is a schematic structural diagram of a portable electronic communication data intelligent processing system based on artificial intelligence proposed by the present invention. Detailed Embodiments

[0017] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0018] Embodiment 1 As Figure 1 shown, a portable electronic communication data intelligent processing system based on artificial intelligence proposed by the present invention includes an intelligent data processing platform, and a data acquisition module, a data analysis module, a data processing module, a transmission management module, an interaction management module, and a data transmission module are arranged in the intelligent data processing platform; The intelligent data processing platform is used for intelligently analyzing and processing the electronic communication data corresponding to the portable electronic communication devices in the platform, so as to facilitate the users of the corresponding portable electronic communication devices in the intelligent data processing platform to provide convenience during the electronic communication data transmission process; It should be further noted that in the specific implementation process, the portable electronic communication device is a device used by relevant users in the corresponding intelligent data processing platform, and is different from the corresponding mobile phones, tablet computers and other portable electronic communication devices on the market.

[0019] The data acquisition module is used to acquire the electronic communication data corresponding to the corresponding portable electronic communication device and the transmission status data corresponding to the corresponding data transmission device. The specific implementation process includes: Set up a communication acquisition unit and a transmission acquisition unit; The communication acquisition unit is used to acquire the corresponding electronic communication data for the corresponding portable electronic communication device. The specific implementation process includes: Set up communication data acquisition ports in the corresponding portable electronic communication devices within the intelligent data processing platform. The communication data acquisition ports are installed in each portable electronic communication device and are used to acquire the corresponding electronic communication data within the corresponding portable electronic communication device; The transmission acquisition unit is used to acquire the transmission status data corresponding to the corresponding data transmission device. The data transmission device includes the electronic transmission device corresponding to the portable electronic communication device and the platform transmission device within the intelligent data processing platform for transmitting various portable electronic communication devices. Moreover, each electronic transmission device and the platform transmission device may include multiple data transmission channels corresponding to different transmission methods, and mark each data transmission channel; Respectively acquire the electronic transmission status data corresponding to the electronic transmission device and the platform transmission status data corresponding to the platform transmission device through the transmission acquisition unit, and respectively set corresponding marks for the obtained electronic transmission status data and platform transmission status data according to the types corresponding to the respective data transmission channels; It should be further noted that in the specific implementation process, the electronic transmission device corresponds to the data interaction end corresponding to different portable electronic communication devices, and sends or receives the corresponding electronic communication data through the data interaction end corresponding to the corresponding portable electronic communication device; the platform transmission device is used to assist in transmitting the electronic communication data sent or received by the data interaction ends corresponding to each portable electronic communication device, so that the corresponding information interaction can be successfully completed between each portable electronic communication device.

[0020] The data analysis module is used to classify the obtained electronic communication data, perform quantization signal analysis and clustering analysis according to the classification result, and obtain the communication characteristic data corresponding to the electronic communication data. The specific implementation process includes: Set up a corresponding data analysis module in each portable electronic communication transmission device, and analyze the communication characteristic data corresponding to the electronic communication data in the corresponding portable electronic communication transmission device through the data analysis module; Set up a data classification unit and a data analysis unit; The data classification unit is used to classify the obtained electronic communication data. The specific implementation process includes: Obtain historical electronic communication data, construct a historical electronic communication data set, perform marking processing on different types of historical electronic communication data in the historical electronic communication data set respectively, and obtain historical electronic communication data subsets corresponding to different data types; Extract features from each of the obtained historical electronic communication data subsets respectively, and obtain classification feature data corresponding to each historical electronic communication data subset. The classification feature data includes format feature data, extension feature data, and auxiliary feature data. Among them, the auxiliary feature data is the content feature corresponding to the corresponding data viewing tool; Set classification evaluation criteria according to the classification feature data corresponding to each historical electronic communication data subset, sort the classification evaluation criteria corresponding to different types of historical electronic communication data subsets in sequence according to the type proportion data, set a classification evaluation axial link, and map the classification evaluation criteria to the corresponding positions of the classification evaluation axial link in sequence according to the sorting result; Obtain electronic communication data, traverse each classification evaluation criterion in the corresponding classification evaluation axial link in sequence for the obtained electronic communication data, and conduct comparative analysis with each classification evaluation criterion until it conforms to the corresponding classification evaluation criterion, and obtain the classification result corresponding to the corresponding electronic communication data; It should be further noted that in the specific implementation process, the classification results corresponding to the electronic communication data include various types such as text data, audio data, video data, and picture data.

[0021] The data analysis unit is used to perform analysis processing according to the classification processing results corresponding to the electronic communication data, and obtain corresponding communication feature data. Its specific implementation process includes: Obtain the classification results corresponding to the electronic communication data, and perform signal quantization analysis and clustering analysis in sequence according to the classification results corresponding to the electronic communication data; Perform sampling processing on the obtained electronic communication data to obtain communication sample data corresponding to the corresponding electronic communication data respectively; Set corresponding quantization processing procedures for the obtained communication sample data according to the corresponding classification results, set a mapping quantization chart according to the corresponding classification results, and obtain a finite number of discrete values for the corresponding communication sample data according to the mapping results of the corresponding mapping quantization chart. Its specific implementation process includes: If the classification result is text data, analyze and process the corresponding communication sample data based on a convolutional neural network to obtain corresponding text local features; Perform analysis and processing based on natural language algorithms according to the text local features to obtain the sentiment tendency corresponding to the corresponding text local features, and map the sentiment tendency results into the mapping quantization chart; If the classification result is audio data, a corresponding measurement period is preset, the sound amplitude data of the audio data is obtained through the measurement period, and the obtained sound amplitude data is mapped into a mapping quantization chart; If the classification result is video data, for each frame image corresponding to the video data, the chrominance component is obtained according to the YUV color space, and the obtained value result corresponding to the chrominance component is mapped into a mapping quantization chart; If the classification result is picture data, the gray value quantization processing is performed on each pixel point in the picture data, and the gray value quantization result is mapped into a mapping quantization chart; Corresponding mapping values corresponding to the corresponding classification results are respectively preset in the mapping quantization chart; Encoding processing is performed according to a corresponding finite number of discrete values in the mapping quantization chart corresponding to the communication sample data to generate a corresponding communication sample signal; Feature extraction is respectively performed on the generated communication sample signals, a quantization feature analysis model is constructed based on a deep learning framework according to the data type corresponding to the communication sample signals, and the corresponding communication sample signals are analyzed and processed based on the quantization feature analysis model corresponding to the corresponding data type, and corresponding quantization feature data is output; Cluster analysis is performed on the quantization feature data of the communication sample signals corresponding to the corresponding data type, and communication feature data is obtained according to the cluster analysis result. The specific implementation process includes: Cluster analysis maps are respectively set according to the quantization feature data corresponding to the corresponding data type, the historical quantization feature data is subjected to correlation analysis, and the historical quantization feature data is subjected to correlation cyclic sorting according to the correlation analysis result. The correlation cyclic sorting is sorted according to the magnitude of the correlation, so that the historical quantization feature data with insufficient correlation is in a parallel and opposite state, and the historical quantization feature data with correlation has an included angle state; Connect the head and tail according to the correlation cyclic sorting result, and set the cyclic feature nodes corresponding to the cluster analysis map according to the result of connecting the head and tail. The cyclic feature nodes are the standard feature data corresponding to the corresponding correlation data; The historical quantization feature data corresponding to the corresponding portable electronic communication device is mapped into the cluster analysis map according to the matching result with the corresponding cyclic feature node to construct a quantization cluster map; The quantization feature data corresponding to the corresponding data type is compared and analyzed with the corresponding quantization cluster map to obtain the position information of the quantization feature data belonging to the quantization cluster map, and the corresponding position information corresponds to the corresponding correlation data; Perform clustering proportion analysis based on the distribution of each data information within the quantization clustering map according to the position information of the quantization feature data within the quantization clustering map, and obtain the communication proportion data corresponding to the corresponding quantization feature data and the historical communication feature data of the corresponding position information according to the proportion analysis result; Obtain the communication feature data corresponding to the corresponding quantization feature data according to the corresponding communication proportion data and the corresponding historical communication feature data; It should be further noted that in the specific implementation process, the historical communication feature data includes the historical transmission information, historical feature information, etc. corresponding to the corresponding quantization feature data.

[0022] The transmission management module is used to analyze and process the obtained transmission status data to generate a real-time transmission monitoring sharing map. Its specific implementation process includes: Obtain the transmission status data, and analyze and process the electronic transmission status data and the platform transmission status data respectively; Obtain the transmission method type corresponding to each transmission status data, set transmission monitoring nodes according to the corresponding transmission method type. The transmission monitoring nodes are used to analyze and process the transmission status data corresponding to the corresponding transmission method type, obtain the corresponding transmission monitoring data, and perform visual analysis on the obtained transmission monitoring data; Set the device transmission monitoring image and the platform transmission monitoring image respectively according to the visual analysis results of the transmission monitoring data corresponding to the electronic transmission status data and the platform transmission status data, where: The device transmission monitoring image is a monitoring visualization image of the transmission status data corresponding to the corresponding data transmission device within the corresponding portable electronic communication device; The platform transmission monitoring image is a monitoring visualization image of the transmission status data corresponding to the platform data transmission device for communication transmission within the platform connected to the corresponding portable electronic communication device; Generate the corresponding real-time transmission monitoring sharing map from the device transmission monitoring image and the platform transmission monitoring image.

[0023] The data processing module is used to encode the corresponding electronic communication data according to the real-time transmission monitoring sharing map and the corresponding communication feature data to generate initial transmission coding information. Its specific implementation process includes: Obtain the historical transmission monitoring sharing map and the historical preferred transmission coding information; Construct a transmission coding data set of the transmission monitoring data regarding the encoding process of the electronic communication data corresponding to the corresponding communication feature data according to the corresponding historical transmission monitoring data and the corresponding historical preferred transmission coding information; Set a two-dimensional coordinate system of the transmission efficiency of the transmission monitoring data regarding the encoding result of the corresponding electronic communication data according to the transmission coding data set; Analyze and process the obtained two-dimensional coordinate system, mark the change amount within the two-dimensional coordinate system to which the transmission monitoring data belongs as ∆x, mark the change amount within the two-dimensional coordinate system to which the transmission efficiency belongs as ∆y, and obtain the corresponding coding transmission coefficient k t : ; wherein, is the corresponding learning rate, and are the corresponding adjustment factors; According to the coding transmission coefficient, perform coding coefficient decomposition analysis to obtain the transmission coding correlation coefficient CG in the corresponding coding process of the corresponding transmission type method: ; wherein, and are the corresponding adjustment coefficients. There are m transmission state indicators corresponding to the corresponding transmission type method, which are respectively , and the corresponding weight is . There are n transmission efficiency indicators, which are respectively , and the corresponding weight is ; Set the transmission coding correlation coefficient CG according to the obtained transmission coding data set, integrate the obtained transmission coding correlation coefficients, and construct a transmission coding correlation chart; Obtain the transmission monitoring data corresponding to each transmission method type in the transmission monitoring image of the corresponding device in the real-time transmission monitoring sharing map, perform sorting analysis on the transmission monitoring data, and sequentially obtain the transmission coding correlation coefficients corresponding to the corresponding transmission coding correlation chart according to the sorting analysis results; Obtain the communication characteristic data corresponding to the electronic communication data, perform segmentation processing on the electronic communication data according to the communication characteristic data, and obtain the corresponding communication segmented data; Perform coding processing on the obtained communication segmented data respectively based on the transmission coding correlation coefficients obtained for the corresponding transmission method types. There is an encrypted coding library deployed locally, and operation symbols corresponding to the corresponding character positions are set in the encrypted coding library; Perform operation analysis on the subsequent character according to the operation result corresponding to the operation symbol corresponding to the previous character, and progress sequentially to obtain the corresponding segmented transmission coding information. Integrate the obtained segmented transmission coding information to generate the initial transmission coding information.

[0024] The interaction management module is used to perform transmission interaction evaluation on the corresponding initial transmission coding information according to the real-time transmission monitoring sharing map, and perform real-time adjustment on the initial transmission coding information according to the evaluation results to obtain the optimal transmission coding information. The specific implementation process includes: Obtain the initial transmission coding information corresponding to the sorting analysis results of each transmission mode type in the device transmission monitoring image; Combined with the transmission monitoring data corresponding to each transmission mode type in the device transmission monitoring image and the platform transmission monitoring image, conduct a transmission interaction evaluation on the transmission process of the obtained initial transmission coding information, and obtain the transmission evaluation data CP corresponding to the corresponding transmission mode type; ; Among them, H is the number of segmented transmission coding information corresponding to the initial transmission coding information, h is the identification mark, S is the device transmission monitoring data, is the standard device transmission monitoring data, P is the platform transmission monitoring data, is the standard platform transmission monitoring data, 、 and are the transmission influence factors corresponding to the electronic data transmission device, the platform data transmission device, and between the electronic data transmission device and the platform data transmission device respectively; Conduct a sorting analysis based on the obtained transmission evaluation data CP to obtain the corresponding optimal transmission mode type; According to the obtained optimal transmission mode type, re-obtain the corresponding transmission coding correlation coefficient for the obtained initial transmission coding information, adjust the initial transmission coding information in real time according to the transmission coding correlation coefficient, and obtain the corresponding preferred transmission coding information according to the adjustment result.

[0025] The data transmission module is used to select a corresponding data transmission path according to the corresponding real-time transmission monitoring sharing graph for the obtained preferred transmission coding information to complete the corresponding data transmission. The specific implementation process includes: Obtain the preferred transmission coding information corresponding to the corresponding electronic communication data and the corresponding optimal transmission mode type; Set the data transmission path according to the transmission monitoring data of the data transmission device corresponding to each transmission mode type in the device transmission monitoring image and the platform transmission monitoring image, and perform data transmission on the preferred transmission coding information corresponding to the electronic communication data according to the data transmission path.

[0026] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A portable electronic communication data intelligent processing system based on artificial intelligence, including an intelligent data processing platform, characterized in that, A data acquisition module, a data analysis module, a transmission management module, a data processing module, an interaction management module, and a data transmission module are provided in the intelligent data processing platform; The data acquisition module is used to acquire the electronic communication data corresponding to the corresponding portable electronic communication device and the transmission status data corresponding to the corresponding data transmission device; The data analysis module is used to classify and process the corresponding electronic communication data, and sequentially perform quantization processing and clustering analysis according to the classification processing results to obtain the communication feature data corresponding to the electronic communication data; The transmission management module is used to analyze and process the obtained transmission status data to generate a real-time transmission monitoring sharing graph; The data processing module is used to encode the electronic communication data according to the real-time transmission monitoring sharing graph and the corresponding communication feature data to generate initial transmission coding information; The interaction management module is used to perform transmission interaction evaluation on the corresponding initial transmission coding information according to the real-time transmission monitoring sharing graph, and perform real-time adjustment on the initial transmission coding information according to the evaluation results to obtain optimized transmission coding information; The data transmission module is used to select a corresponding data transmission path according to the obtained optimized transmission coding information and the corresponding real-time transmission monitoring sharing graph to complete the corresponding data transmission.

2. The intelligent processing system for portable electronic communication data based on artificial intelligence according to claim 1, wherein The process of collecting electronic communication data and transmission status data includes: Setting a communication collection unit and a transmission collection unit; The communication collection unit is used to collect the electronic communication data corresponding to the corresponding portable electronic communication device; The transmission collection unit is used to collect the transmission status data corresponding to the corresponding data transmission device, and the transmission status data includes the electronic transmission status data set in the portable electronic communication device and the platform transmission status data corresponding to the intelligent data processing platform.

3. The intelligent processing system for portable electronic communication data based on artificial intelligence according to claim 2, wherein The process of classifying and processing electronic communication data includes: Obtaining a historical electronic communication data set, respectively performing marking processing on the historical electronic communication data of different data types in the historical electronic communication data set, and generating a historical electronic communication data subset according to the marking processing results; Respectively perform feature extraction on each historical electronic communication data subset to obtain the classification feature data corresponding to each historical electronic communication data subset, set classification evaluation criteria according to the obtained classification feature data, and generate a classification evaluation axial link according to the classification evaluation index; Traverse each classification evaluation index in the corresponding classification evaluation axial link in sequence for the obtained electronic communication data to obtain the classification result corresponding to the corresponding electronic communication data.

4. The intelligent processing system for portable electronic communication data based on artificial intelligence according to claim 3, characterized in that, The process of obtaining the communication feature data corresponding to the electronic communication data includes: Performing sampling processing according to the classification result corresponding to the electronic communication data, setting a mapping quantization chart corresponding to the corresponding data type to obtain communication sample data, performing quantization analysis on the obtained communication sample data according to the corresponding classification result, and mapping the obtained quantization analysis result into the corresponding mapping quantization chart to obtain a finite number of discrete values corresponding to the communication sample data; Generating a communication sample signal according to the obtained values, and obtaining corresponding quantization feature data according to the communication sample signal; Perform similarity analysis on historical quantitative feature data, perform associative cyclic sorting on the historical quantitative feature data according to the similarity analysis results, connect the head and tail according to the associative cyclic sorting results, construct a quantitative clustering map, and set corresponding cyclic feature nodes; Compare and analyze the obtained quantitative feature data with each cyclic feature node in the quantitative clustering map in turn to obtain the position information and communication occupancy ratio data of the quantitative feature data belonging to the quantitative clustering map; Obtain the communication feature data corresponding to the corresponding electronic communication data according to the obtained communication occupancy ratio data and the corresponding position information.

5. The intelligent processing system for portable electronic communication data based on artificial intelligence according to claim 4, wherein The process of generating a real-time transmission monitoring sharing map includes: Obtain transmission status data, and analyze and process the electronic transmission status data and the platform transmission status data respectively; Obtain the transmission mode type corresponding to each transmission status data, set a transmission monitoring node according to the corresponding transmission mode type, and the transmission monitoring node is used to analyze and process the transmission status data corresponding to the corresponding transmission mode type, obtain corresponding transmission monitoring data, and perform visual analysis on the obtained transmission monitoring data; Set a device transmission monitoring image and a platform transmission monitoring image respectively according to the visual analysis results of the transmission monitoring data corresponding to the electronic transmission status data and the platform transmission status data; Generate a corresponding real-time transmission monitoring sharing map from the device transmission monitoring image and the platform transmission monitoring image.

6. The intelligent processing system for portable electronic communication data based on artificial intelligence according to claim 5, wherein, The process of generating initial transmission coding information includes: Obtain a historical transmission monitoring sharing map and historical preferred transmission coding information, construct a transmission coding data set of the transmission monitoring data regarding the coding process of the corresponding electronic communication data corresponding to the corresponding communication feature data according to the corresponding historical transmission monitoring data and the corresponding historical preferred transmission coding information, set a transmission coding correlation coefficient according to the obtained transmission coding data set, and integrate the obtained transmission coding correlation coefficients to construct a transmission coding correlation chart; Obtain the transmission monitoring data corresponding to each transmission mode type in the corresponding device transmission monitoring image in the real-time transmission monitoring sharing map, perform sorting analysis on the transmission monitoring data, and sequentially obtain the transmission coding correlation coefficients corresponding in the corresponding transmission coding correlation chart according to the sorting analysis results; Obtain the communication feature data corresponding to the electronic communication data, perform segmentation processing on the electronic communication data according to the communication feature data to obtain corresponding communication segmented data, perform coding processing on the obtained communication segmented data respectively based on the transmission coding correlation coefficients obtained for the corresponding transmission mode types, obtain corresponding segmented transmission coding information, and integrate the obtained segmented transmission coding information to generate initial transmission coding information.

7. The intelligent processing system for portable electronic communication data based on artificial intelligence according to claim 6, characterized in that The process of obtaining preferred transmission coding information includes: Obtain the initial transmission coding information corresponding to the sorting analysis results of each transmission mode type in the device transmission monitoring image, combine the transmission monitoring data corresponding to each transmission mode type in the device transmission monitoring image and the platform transmission monitoring image to perform a transmission interaction evaluation on the transmission process of the obtained initial transmission coding information, obtain the transmission evaluation data corresponding to the corresponding transmission mode type, and obtain the optimal transmission mode type according to the obtained transmission evaluation data; Re-obtain the corresponding transmission coding correlation coefficient for the obtained initial transmission coding information according to the obtained optimal transmission mode type, adjust the initial transmission coding information in real time according to the transmission coding correlation coefficient, and obtain the corresponding preferred transmission coding information according to the adjustment result.

8. The intelligent processing system for portable electronic communication data based on artificial intelligence according to claim 7, characterized in that The process of data transmission for the preferred transmission coding information includes: Obtain the preferred transmission coding information corresponding to the corresponding electronic communication data and the corresponding optimal transmission mode type; Set the data transmission path according to the transmission monitoring data of the data transmission devices corresponding to each transmission mode type in the device transmission monitoring image and the platform transmission monitoring image, and perform data transmission on the preferred transmission coding information corresponding to the electronic communication data according to the data transmission path.

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