19results about How to "Realize intelligent processing" patented technology

The invention discloses a high-precision charging pile measurement data processing system and method based on artificial intelligence, and relates to the technical field of charging intelligent management, and the method comprises the steps: analyzing and marking the equipment matching degree between equipment operation parameters in equipment operation data and a charging pile; acquiring historical environment monitoring records of the charging pile, acquiring abnormal equipment operation parameters from the abnormal equipment operation data, and analyzing data relevance between environment monitoring indexes in the historical environment monitoring records and the abnormal equipment operation parameters in the charging pile; acquiring a historical data measurement record of the charging pile, establishing a charging fault prediction model of the charging pile, acquiring a historical environment monitoring record, acquiring associated environment data, and optimizing the charging fault prediction model; and monitoring the charging state of the charging pile in the current period, performing fault prediction on the charging pile by using the charging fault prediction model, and managing the charging of the charging pile.

The embodiment of the invention provides a document processing method and device, electronic equipment and a storage medium. The document processing method comprises the following steps: displaying a first document outline in a first interface; in response to an editing operation for the first document outline, updating at least part of contents of the first document outline to obtain a second document outline; and according to the second document outline, generating a target file in a second interface or updating the target file in the second interface. According to the embodiment of the invention, the document processing efficiency can be improved.

The invention discloses an underground while-drilling gas cut intelligent treatment device which comprises a drill column, and a closed gas collection chamber, a gas detection chamber and a gas treatment chamber are sequentially connected to the position, close to a drill bit, in the drill column from bottom to top through gas conveying pipes. The gas detection chamber generates large pressure difference in a water-driven gas mode, gas cut gas is collected in combination with a hydrophobic and breathable semi-permeable membrane, hydrocarbon gas and hydrogen sulfide gas in the gas cut gas are detected through infrared light and ultraviolet light respectively, the optical path of gas detection is increased by arranging an optical lens assembly, and the detection accuracy of the gas cut gas is improved. The detection accuracy is effectively improved, hydrogen sulfide gas is absorbed through an alkaline solution in the gas treatment chamber, hydrocarbon gas is adsorbed through an active solid, the adsorbed active solid is sealed and coated and then is circulated to the ground along with the drilling fluid, a desorption experiment can be carried out on the saturated active solid, and the detection accuracy is improved. Therefore, the components and the content of the underground hydrocarbon gas can be accurately analyzed.

The invention discloses a method for solving complaint work order treatment by a construction problem monitoring robot, and the method comprises the steps: obtaining multi-channel customer complaint data, and classifying complaint work order problems; key information after complaint work order classification is extracted, and a structured work order task is generated; performing clustering analysis on the generated structured work order task to obtain a standard work order; constructing a proposal board and a common problem discovery model, and predicting a basic problem of the complaint work order; the predicted fundamental problem is diagnosed by using the affair map, and the root cause of the problem is output; and enterprise intelligence brain is built, customer service GPT is output, and solution suggestions are quickly provided for root causes of complaints. According to the invention, intelligent processing of customer complaints is realized, the problem solving efficiency is improved, the customer complaint rate is effectively reduced, and powerful support is provided for enterprises to improve customer satisfaction and service quality.

This invention provides a contract review assistance system, method, and storage medium. By constructing a four-layer architecture of "main agent - sub-agent - toolset - data resource layer," intelligent processing of contract review and related business scenarios is achieved. This architecture not only improves the flexibility and collaborative efficiency of task processing but also reduces reliance on manual intervention and error rates. Thus, it achieves an efficient, accurate, and structured review process through intelligent means, thereby improving the processing efficiency of contract review and related business scenarios. This solves the technical problem that existing contract review methods cannot fully meet the core review needs of the contract marketing and risk control domains, leading to low contract review efficiency.

The invention discloses a Wuyi rock tea full-process-flow full-automatic clean production system which comprises a withering, cooling and rocking circulation line, a fixation line, a rolling line, a drying line and a finished product packaging line corresponding to each working procedure / process of Wuyi rock tea production, the withering, cooling and rocking circulating line is arranged in the front of the production system and is used for realizing circulating withering, cooling and rocking of fresh leaves; the withering, cooling and rocking circulation line is provided with a chain plate feeding machine I, a multi-layer chain plate type withering machine, a chain elevator I, a reciprocating conveyor I, a chain elevator II, an adjustable rocking machine, a reciprocating conveyor II, a chain plate elevator I, a chain elevator III and a distributing machine; the first chain plate feeding machine and the multi-layer chain plate type withering machine are connected front and back to form a long-distance withering conveying line, and the second chain elevator, the adjustable green leaf rocking machine, the second reciprocating conveyor and the first chain plate elevator are connected front and back to form a long-distance green leaf rocking conveying line. The system comprises the whole technological process of Wuyi rock tea production, and automatic and intelligent production can be achieved.

The present invention provides a context-adapted intelligent recommendation method and system, which respond to an advertisement push request from a recommendation end, receive interactive push data sent by the recommendation end, obtain a target item sent by a user end, retrieve the corresponding interactive push data based on the target item and display it to the user end; receive customized posture data uploaded by the user end based on the interactive push data, obtain a posture comparison result based on comparison information between the customized posture data and the interactive push data; when it is determined that the posture comparison result is a similar comparison result, replace the demonstration model in the interactive push data according to a context posture adaptation strategy and the customized posture data to obtain context-adapted data; when it is determined that the posture comparison result is a difference comparison result, retrieve a free posture adaptation strategy to adapt the customized model in the customized posture data to obtain context-adapted data, and send the context-adapted data to the user end.

The invention discloses an intelligent processing device for gas invasion while drilling in a well, comprising a drill string, wherein a sealed gas collection chamber, a gas detection chamber and a gas processing chamber are connected in sequence from bottom to top near a drill bit in the drill string through a gas transmission pipe; the gas detection chamber generates a large pressure difference by means of water-driven gas, and realizes the collection of gas invasion gas by combining a hydrophobic and breathable gas molecule semipermeable membrane, and utilizes infrared light and ultraviolet light to detect hydrocarbon gas and hydrogen sulfide gas in the gas invasion gas respectively, and increases the optical path of gas detection by arranging an optical lens assembly, thereby effectively improving the detection accuracy; finally, the hydrogen sulfide gas is absorbed by an alkaline solution in the gas processing chamber, and then the hydrocarbon gas is adsorbed and processed by an active solid, and the adsorbed active solid is sealed and coated and circulated to the ground along with the drilling fluid, and a desorption experiment can be performed on the saturated active solid, thereby accurately analyzing the composition and content of the hydrocarbon gas in the well.

The invention relates to the technical field of water treatment, in particular to an industrial salt-containing water purification treatment method which comprises the following steps: S1, conveying a water body to be treated to a reservoir for pretreatment, S2, obtaining the particle size and the content of pollutants in the pretreated water body to calculate a pollution characteristic value, and S3, calculating the pollution characteristic value according to the particle size and the content of the pollutants in the pretreated water body. The method comprises the following steps: S1, monitoring the water body after pretreatment, adaptively selecting a preset treatment branch to treat the water body, conveying the pretreated water body to each treatment branch according to a pollution characteristic value, and evaluating a treatment result, and S4, conveying the treated water body to a target area. Damage of pollutants to the membrane in the subsequent membrane separation process is reduced, intelligent treatment of the water body is realized, and the treatment efficiency is improved.

The invention relates to a cross-border transportation control system and a control method thereof, and the system comprises a cross-border transportation management platform which is used for carrying out the transportation scheduling according to a transportation demand and a vehicle state, monitoring the transportation data and cargo information in a transportation process, and carrying out the data analysis and risk early warning; the customs inspection optimization system is used for analyzing the cargo information and pre-judging a customs inspection result; automatic customs inspection and unified management of data are carried out; the intelligent transportation decision-making system is used for planning a transportation path and allocating transportation resources according to cargo characteristics and transportation requirements; the cross-border logistics information integration and analysis system is used for collecting, processing and analyzing cross-border logistics data and deploying the data according to an analysis result; the cross-border transportation safety guarantee system is used for evaluating safety risks in the cargo transportation process and handling emergencies. Compared with the prior art, intelligent management and scheduling of the cross-border transportation process are realized, and the transportation flexibility and efficiency are improved.

The present invention relates to the technical field of digital twin cities, and in particular to a spatial data integration method and system applied to digital cities. The method comprises the following steps: using satellite remote sensing equipment, a laser radar building scanner and a traffic sensor to obtain digital twin city spatial data and digital twin city flow data; using a spatial interpolation algorithm to interpolate and map the real-time traffic simulation data of the digital twin city to generate a traffic simulation density distribution map of the digital twin city; using a voxel modeling method based on three-dimensional modeling technology to perform three-dimensional modeling on a three-dimensional digital twin city data set; using a deep learning algorithm to perform real-time interactive visualization processing on the digital twin city traffic simulation density distribution map; performing dilation convolution and multi-scale sampling on the digital twin city building three-dimensional model and the digital twin city traffic real-time simulation interactive view to construct a digital twin smart city model; the present invention realizes efficient and orderly operation of the digital twin city.

The utility model discloses a hot-blast stove with a tail gas recovery function, which belongs to the field of hot-blast stove tail gas treatment and comprises a tail gas recovery box body, a gas inlet pipe is fixedly mounted on one side of the tail gas recovery box body, and an exhaust pipe is fixedly mounted on the other side of the tail gas recovery box body. A sieving cavity, a liquid medicine soaking cavity and an odor removing cavity are formed in the tail gas recycling box body, a coarse sieve plate is fixedly mounted in the sieving cavity, a fine sieve plate is fixedly mounted in the sieving cavity, a first ventilation pipe and a second ventilation pipe are fixedly mounted at one end of the inner wall of the sieving cavity, and a soaking agent is arranged in the liquid medicine soaking cavity; nozzles are evenly and fixedly installed at the top end of the inner wall of the liquid medicine soaking cavity, a discharge pipe is fixedly installed at the bottom end of the tail gas recovery box body, and vent grooves are evenly formed in one side of the inner wall of the liquid medicine soaking cavity, tail gas exhausted by the hot blast stove can be fully filtered and cooled, and the pollution after tail gas emission can be effectively reduced.

The utility model relates to the technical field of moxa stick processing, in particular to a moxa stick processing device which comprises a processing table, a first conveying belt is arranged on the processing table, a third motor for driving the first conveying belt to operate is fixedly installed on the side wall of the processing table, and a processing box is arranged on the processing table. And two cutting rollers are symmetrically and rotationally mounted at the top end of the processing box. The first motor can drive the cutting roller and the spiral conveying roller to rotate at the same time, the cut folium artemisiae argyi can be conveyed while the folium artemisiae argyi is cut, the number of used driving sources can be reduced, the use cost can be reduced, the folium artemisiae argyi can be tightly attached to a base material, moxa pastes can be formed, and the production efficiency is improved. And the forming effect of the moxa pastes can be guaranteed by evenly pressing the pressing rollers, meanwhile, starting and stopping of corresponding electric elements can be controlled through the PLC, intelligent processing of the moxa pastes can be achieved, the processing efficiency can be improved, meanwhile, the labor cost is reduced, and the economic benefits are improved.

This invention belongs to the field of data processing technology, specifically disclosing a safety assessment method for energy storage power stations based on real-time monitoring data. The method includes: performing multimodal feature analysis on voltage and environmental data sequences of the energy storage power station to obtain static voltage feature tensors and static environmental feature tensors; conducting collaborative analysis of the static voltage and environmental feature tensors to obtain an environmental voltage feature correlation group; performing entropy weight dynamic analysis on the environmental voltage feature correlation group to construct a multidimensional state vector; performing time-series deduction on the multidimensional state vector to obtain a safety situation evolution matrix; and performing residual analysis between the safety situation evolution matrix and real-time monitoring time-series data to obtain a comprehensive deviation index; and performing root cause assessment on the comprehensive deviation index to obtain comprehensive risk information. This invention enables more accurate, dynamic, and efficient safety assessment of energy storage power stations, allowing for comprehensive situation perception and rapid identification of risk root causes.

The embodiment of the invention provides an insurance issuing method and device, electronic equipment and a storage medium, belongs to the technical field of image processing, and is suitable for the field of financial science and technology. The method comprises the following steps: acquiring a scanning insurance policy image of a target user; performing image recognition on the scanned insurance policy image to obtain an insurance category; based on the insurance category, screening a preset initial insurance policy input workbench to obtain a target insurance policy input workbench, the target insurance policy input workbench being used for performing insurance policy input on the scanned insurance policy image; performing insurance policy input on the scanned insurance policy image based on a target insurance policy input workbench to obtain a target electronic insurance policy; information verification is carried out on the target electronic insurance policy to obtain an insurance policy information verification result, and the insurance policy information verification result is used for representing that the information of the target electronic insurance policy is correct or wrong; and performing insurance issuing on the target electronic insurance policy based on the insurance policy information verification result. According to the embodiment of the invention, the insurance issuing efficiency can be improved.

The invention relates to the technical field of metal plate bending processing, in particular to a real-time collision detection method based on self-adaptive bounding boxes and machine learning, which comprises the following steps: firstly, carrying out geometric feature analysis on each three-dimensional model, and calculating the fitting degree between the volume of the model and the volumes of different bounding boxes (sphere, AABB and OBB); and adaptively selecting and constructing an optimal bounding box with the highest space utilization rate. In a real-time detection stage, aiming at an object pair to be detected, 24-dimensional geometrical relationship feature vectors between bounding boxes of the object pair to be detected are extracted, and the 24-dimensional geometrical relationship feature vectors are input into a pre-trained lightweight multilayer perceptron model. The model outputs continuous collision probability values, and three-level intelligent classification (high-probability collision, critical state and safety) is performed according to a preset threshold value, so that scheduling of accurate detection resources is guided. According to the method, the package tightness of the bounding box can be improved from the source, and the boundary condition is accurately pre-judged by utilizing machine learning, so that the efficiency of real-time collision detection is improved while the detection precision is ensured.

The invention relates to the field of engineering cost, in particular to an engineering cost index analysis method based on reinforcement learning, which comprises the following steps of: identifying a table contour and a standard font contour in file image data, generating optimized image data, extracting a pointing keyword as a label, and forming a clustering set based on semantic similarity clustering; visual similarity analysis is carried out by reserving a table contour, a common label is set, a mapping association network of a keyword label and the common label is constructed, and intelligent processing of data uploaded by a user side is achieved. When the common label is successfully associated, a key data area is positioned according to area information, and local analysis is carried out; and if not, carrying out traversal analysis and semantic understanding on the complete table structure. According to the method, manual marking is replaced by automatic feature extraction, structured association of engineering knowledge is established, differentiation processing strategies are intelligently switched according to the matching degree, and the training data quality and the generalization ability of the model in a complex engineering scene are improved.

The invention discloses a self-adaptive network anomaly detection and policy-driven automatic recovery method and device, and relates to the technical field of network security and network management. The method comprises the following steps: collecting network multi-source indexes, and performing time sequence decomposition and pseudo data elimination to obtain preprocessed data; a weighted distance model is constructed to calculate an anomaly score, and adaptive anomaly detection is realized; after abnormity is determined, an abnormity propagation model is constructed based on network topology and node interaction strength, and an abnormal source node and a propagation path are determined; performing abnormal root cause analysis through graph structure similarity matching; according to the anomaly detection and root cause analysis result, constructing a multi-objective optimization model to generate a differential recovery strategy and executing the differential recovery strategy; the recovery effect is monitored and fed back, and the detection and strategy model is optimized. According to the method, a closed-loop self-healing process of detection-diagnosis-decision-execution-verification is formed through multi-dimensional feature modeling, anomaly propagation analysis and an optimization decision mechanism, and the accuracy and recovery efficiency of network anomaly detection are effectively improved.

The present invention relates to the field of dynamic data processing, and specifically to a dynamic data acquisition and processing method and system based on cloud computing, comprising: a dynamic capture module, a signal modulation module, a cloud preloading module, a pulse update module and a precision feedback module, wherein the dynamic capture module is used to capture the call of dynamic variables, the signal modulation module is used to generate a multidimensional feature vector of dynamic data, the cloud preloading module is used to map the initial dynamic data in a cloud virtual space, the pulse update module is used to update the feature vector and send the update result through a pulse signal, and the precision feedback module is used to adjust the unit lattice distribution generated in the cloud. The present invention can ensure the timely update and feedback of dynamic data, improve the timeliness and reliability of the dynamic data processing process, reduce channel resource overhead, enable the sampling system to adapt to the dynamic data type, and improve the real-time and response speed of dynamic signal sampling and processing.