673 results about "Business management" patented technology

The invention discloses a building industry human resource management system based on a block chain technology, and aims to solve the problems that a current building industry human resource management system is slow in processing speed and difficult to meet flexible employment and rapid recruitment requirements of the building industry, so that transaction processing is delayed, sensitive information of employees may be leaked, a decentralized architecture needs multi-party coordination, and the efficiency is high. The system comprises a block chain module which is used for data storage, security and automatic execution of a consensus mechanism; and the business management module is used for carrying out precise management on complex scenes in the building industry through characteristics of decentralization, non-tampering and the like. According to the method, a decentralized distributed architecture is adopted, the data is stored on a plurality of nodes, the security of the data is ensured, each piece of data is recorded on the block chain and cannot be tampered by any person, the authenticity and integrity of the data are ensured, intermediate links can be reduced, and the management cost and risk are reduced.

The invention relates to the technical field of artificial intelligence, and discloses an interaction method and device based on voice recognition, equipment and a storage medium, and the method comprises the steps: obtaining collected user voice; a recognition model is adopted to convert the user voice into voice characters, and the identity of a speaker and the emotion of the user are obtained through recognition; obtaining the above-mentioned reply text, converting the voice text, the speaker identity and the user emotion into a prompt word text by adopting a language model, and generating a target reply text according to the above-mentioned reply text and the prompt word text; and converting the target dialogue text into target dialogue voice by adopting a text-to-voice model, and controlling a loudspeaker to play the target dialogue voice. The method can be applied to business management program systems of financial science and technology, medical treatment and the like, the problem of double limitation of intelligence and emotional interaction faced by existing human-computer interaction is solved, and the industry service quality and the user stickiness are improved.

The invention discloses a geological exploration service management method and system based on cloud intelligence, and relates to the technical field of geological exploration management, and the system comprises a standard specification system, a base layer, a data layer, a platform layer, an application layer and a safety guarantee system. Data collaborative acquisition, processing and sharing are realized through a multi-level architecture design, project approval analysis, work layout, task distribution auditing and data management are realized, multi-specialty collaborative acquisition and safety management of a field data acquisition APP are supported, rapid mapping and standardized filing of an interior work data processing tool are supported, a standardized process is formed, and data processing efficiency is improved. The working efficiency and the data quality are improved through indoor and outdoor real-time collaboration, multi-source data verification, edge calculation and the like, the data safety is guaranteed, the team collaboration and achievement customization ability is enhanced, meanwhile, integrated data sharing is achieved through the cloud computing pool, and the efficiency of geological exploration work is improved.

The invention relates to an improved NSGA-III-based multi-target geographic site selection optimization method and system, belongs to the technical field of optimization in business management and resource planning, and particularly relates to resource allocation and site selection decision making by using a calculation model. The technology aims to solve the problems of slow scheme convergence, non-uniform solution set distribution and low calculation efficiency when multi-target site selection is carried out under limited resources. According to the scheme, geographic space data is preprocessed, and an initial population representing different site selection schemes is generated; carrying out optimization iteration by adopting an improved NSGA-III algorithm, and calculating a plurality of objective functions such as coverage rate, normalized population density and medical service accessibility; and performing individual selection and population updating by utilizing improved reference point generation and vertical distance measurement. The method is mainly used for improving the efficiency and effect of commercial and municipal decisions such as urban planning, medical resource configuration, energy station layout and logistics network optimization.

The invention relates to the technical field of commodity trade management, and discloses a commodity trade business management system based on a block chain. A block chain data acquisition module of the system obtains commodity basic information, trade enterprise qualification information and logistics node information in real time through a preset data interface, and synchronizes the information to a block chain distributed account book; the trade risk quantitative analysis module generates a trade link real-time risk coefficient set based on account book real-time data in combination with a trade compliance rule base, historical order fulfillment data and current logistics state data; a risk control strategy collaborative analysis module generates a plurality of candidate risk control strategy schemes when the risk coefficient exceeds a preset threshold value, calculates a collaborative execution cost factor when the enterprise qualification state is changed in combination with logistics node information, and obtains an interference influence value set of each scheme on the trade process; and a risk control strategy execution feedback module updates a block chain smart contract execution instruction according to the optimal risk control strategy scheme, and facilitates efficient management and control of commodity trade business.

The invention provides a business travel management system and method, and relates to the technical field of enterprise management, a route is planned through an itinerary planning module, business trips are on business according to the planned route, and the business trips are positioned through a positioning module; the method comprises the following steps: acquiring positioning information of a business tripper through a trajectory analysis module, acquiring a trajectory of the business tripper according to the positioning information, analyzing a staying place and time corresponding to the staying place, and acquiring a consumption level of the staying place; a business tripper reports a bill, the bill reported by the business tripper is received through a fee auditing module, the bill place, the bill time and the bill amount are identified, the bill place, the bill time and the bill amount are compared with the staying place, the time corresponding to the staying place and the consumption level of the staying place, and the abnormal bill is marked. The business travel management system solves the problem that existing business travel management is time-consuming and labor-consuming, and is suitable for business travel management of enterprises.

The invention relates to the technical field of business process management, in particular to an enterprise data intelligent analysis management method and system, and the method comprises the following steps: obtaining a business data timestamp, an input source, an operation type and a transmission path, analyzing a data flow node, and generating a business data flow dependency matrix. According to the method, abnormal data is screened based on stability calculation, the data quality is improved, error interference is reduced, task execution pressure and dependency are combined, task sorting is optimized, the scheduling sequence is dynamically adjusted, conflicts are reduced, execution efficiency is improved, the priority level is adjusted according to the execution progress and urgency degree, and efficient hierarchical scheduling is achieved; by combining resource demand, consumption value calculation, calculation node matching, resource allocation optimization, utilization rate improvement, waste reduction, data analysis accuracy improvement, task execution strategy optimization, resource matching efficiency improvement and business management intelligence level enhancement are realized.

The invention discloses a general cargo transportation background business management system and method and electronic equipment, the system comprises a data acquisition module, an information management module, a position tracking module and a scheduling management module, and automatic acquisition of cargo position, attribute and safety inspection information is realized through an integrated sensor, an RFID tag technology and an image identification device; the GPS positioning and local wireless network complementary correction technology is utilized to break through the positioning precision limitation in the indoor and outdoor complex environment; based on a distributed database and a real-time data processing engine, high-concurrency query and dynamic information updating are supported; in combination with cargo state and position data, an optimization scheduling instruction is generated through an algorithm, empty driving waiting of loading and unloading equipment is reduced, the method covers intelligent scheduling processes of multi-source data acquisition, standardized processing, real-time tracking and cloud driving, full-life-cycle automatic management of cargos is realized, and electronic equipment realizes full-life-cycle automatic management through a software and hardware collaborative architecture. An existing port management system is compatible, and deployment cost is reduced.

The invention belongs to the crossing field of computer technology and business management, and discloses a purchase return risk early warning and management method and system based on multi-mode intelligent auditing, electronic equipment and a computer readable storage medium. The method comprises the following steps: segmenting a PDF invoice image through an improved Apache PDFBox analyzer; a CLIP model and an OCR technology are combined, a cross-modal attention layer is used for correcting an OCR text, a multi-modal consistency difference value is generated, and invoice authenticity is judged; when a false invoice is detected, generating a standardized risk event, and extracting supplier, purchaser and transaction edge data from the graph database to construct a time sequence sub-graph; and identifying an abnormal mode based on the graph neural network, verifying the risk by using a time sequence risk scoring model, and executing a treatment strategy. According to the method, through multi-modal fusion, dynamic graph analysis and time sequence modeling, the problems of low false invoice detection precision, long abnormal fund tracing time consumption, risk prediction lag and the like in traditional auditing are solved.

The invention discloses a data processing method and system based on a business management platform, particularly relates to the technical field of advertisement putting business management, and is used for solving the problems of difficulty in abnormal attribution and low decision-making efficiency caused by dimension data isolation of an existing system. The method comprises the following steps: synchronously acquiring a channel dimension click rate and a contact dimension blacklist interception rate; when the channel click rate is abnormally reduced, extracting a blacklist interception log associated with the corresponding channel and a product dimension conversion rate; user behavior path topology distortion intensity and decision manifold compactness caused by a blacklist strategy are verified based on an interception log; when the distortion intensity exceeds a threshold value or the compactness is lower than a threshold value, backtracking an advertisement exposure user path of a corresponding channel product; analyzing time sequence association of blacklist interception nodes and product exposure nodes in the path, and generating a candidate root cause set; and detecting the product conversion rate fluctuation direction in the abnormal time period, thereby determining the root cause from the candidate set, and remarkably improving the operation decision-making efficiency and accuracy.

Embodiments of the present disclosure provide a method for dynamic computing resource allocation based on an IIoT data center, the method comprising: receiving, via an IIoT user platform 110, a business demand of an enterprise user, and sending the business demand via an IIoT service platform 120 to a data computing center of a IIoT management platform 130; monitoring, by a monitoring module, resource data of a business management sub-platform; determining, based on the business demand, a resource demand feature of the enterprise user; determining, based on the resource demand feature and the resource data of the business management sub-platform, a resource allocation parameter; and, generating, via the control center, a resource allocation instruction based on the resource allocation parameter.

The invention discloses a canal channel dredging construction big data basic business management system, and relates to the field of dredging construction data management. A canal channel dredging construction big data basic business management system comprises a data processing module, a data analysis module and a data management module. The method solves the problems that in the actual use process in the prior art, only business data in construction of the trailing suction dredger can be managed, and accurate decision support cannot be provided for channel dredging work, and the real-time processing of the data in the channel dredging process can be realized by collecting and processing various data in real time and applying a big data analysis method, so that the real-time processing of the data in the channel dredging process can be realized. And deep mining and intelligent analysis are carried out on the collected data, and accurate decision support is provided for channel dredging work. Besides, the system has the functions of remote monitoring, fault early warning and the like, comprehensive and efficient management of the canal channel dredging construction big data basic business is realized, the construction efficiency and quality are improved, and the construction cost and risk are reduced.

The invention relates to the field of business management, in particular to a production and manufacturing resource scheduling-oriented mixed integer programming optimization system, which comprises six modules: a data acquisition module acquires industrial big data streams; the data mapping module processes the data flow and constructs a real-time data model; the dynamic modeling module is used for automatically generating a mixed integer programming model according to a built-in steel production process model library based on a real-time data model; the model solving module generates a resource scheduling scheme through an optimization engine; the instruction analysis module analyzes a specific management and operation instruction; and the scheduling recalculation module starts a new round of mixed integer programming modeling and solving according to the increment information. According to the system, information such as resources is summarized through a mixed integer programming method, a specific production instruction is generated through a solver, a new round of modeling and solving are started when an accident occurs, rapid and accurate response to resource scheduling is achieved, and the response efficiency of resource scheduling and the reliability of the system are improved.

The invention relates to the technical field of financial knowledge management, and discloses a multi-modal Agent coordinated reasoning system, and the key points of the technical scheme are that the multi-modal Agent coordinated reasoning system comprises a data interface module which is used for connecting a data source to obtain target data, and is also used for receiving a task instruction; the function management module is used for constructing functional Agents with various data processing functions and executing corresponding data processing on target data according to a scheduling strategy through the functional Agents; the business management module is used for constructing a business Agent of each business field and carrying out business processing according to a scheduling strategy through the business Agent; and the scheduling decision module is used for generating a scheduling strategy according to the task instruction and the target data, and performing scheduling and collaboration on the function Agent and the service Agent according to the scheduling strategy.

The invention relates to a large-model water conservancy business intelligent arrangement calculation method and system. The method comprises the following steps: obtaining hydro meteorological data, hydraulic engineering data, ecological protection data and business management data containing a cross-regional cooperation framework and a scheduling principle, and fusing to generate a hydraulic engineering data set; constructing a water conservancy digital twinborn body based on the water conservancy data set; deducing the water safety situation change through a preset environment evolution model; when the water safety situation change reaches a preset threshold value, analyzing a cooperation framework and a scheduling principle in the service management data through a decision engine based on the situation change and the digital twin, and generating a water conservancy service scheme containing a cross-domain cooperation constraint condition; analyzing the cross-domain collaborative constraint condition by adopting a graph neural network, and generating a multi-service logic topological graph; and generating a water conservancy business execution instruction sequence based on the structural features of the topological graph. According to the invention, water conservancy business full-process intelligent decision-making and cross-domain cooperative scheduling are realized, and the water safety guarantee capability is improved.

The invention relates to the field of enterprise business management, in particular to an AI-based enterprise business data processing system and method, and the method comprises the steps: 1, obtaining source system data, and storing the obtained data in one or more target systems; step 2, constructing a data synchronization strategy, and monitoring and managing data synchronization between the target system databases based on the data synchronization strategy: generating the data synchronization strategy based on the data synchronization cost; after the importance of the data and the data synchronization task is quantified, the data and the data synchronization task are combined with the data synchronization cost, and a data synchronization strategy is optimized; an adjustment rule is added in the optimized data synchronization strategy, and the importance of data or tasks is dynamically adjusted; and step 3, sending the data of the one or more target systems to the cloud platform for storage.

The invention belongs to the technical field of artificial intelligence, and relates to a sensitive information-based file tracing method, which comprises the following steps of: performing text recognition on a to-be-traced file based on a text content recognition technology to obtain a content recognition result; performing sensitive information matching on the content identification result through a preset sensitive information identification strategy; determining that the file to be traced contains sensitive information, generating sensitive file identification information and recording user information; in response to an operation behavior of a user on the to-be-traced file, obtaining operation information, and calling an integration tool to inject the user information and the operation information into the to-be-traced file to generate file integration information; and generating a traceability chain based on the sensitive file identification information and the file integration information. The invention further provides a file traceability device and equipment based on the sensitive information and a storage medium. The method can be applied to business management program systems of financial science and technology, medical treatment and the like, the source, the circulation path and the final destination of the file can be clearly presented, and full-life-cycle management of the file is achieved.

The invention belongs to the technical field of artificial intelligence, and discloses a CNN-based call quality inspection method, device and equipment and a storage medium, the CNN-based call quality inspection method comprises the following steps: inputting a word vector sequence obtained by converting a target text corresponding to a target seat call into a preset sentiment analysis model to obtain a sentiment tag corresponding to the target text; analyzing the importance degree of each word vector in the word vector sequence to obtain a keyword vector in the word vector sequence; performing named entity recognition on each word vector in the word vector sequence to obtain an optimal entity tag sequence corresponding to the word vector sequence; and splicing the audio feature, the emotion tag, the keyword vector and the optimal entity tag sequence, inputting the obtained multi-modal fusion feature into a preset evaluation model, and outputting to obtain a quality inspection result. The method and the system can be applied to business management systems of financial science and technology, medical health and the like, and solve the technical problem that efficiency and quality cannot be considered in a call quality inspection mode based on the prior art.

The invention discloses a traffic service management big data comprehensive analysis, research and judgment system, and the system comprises an access module which is used for accessing a multi-source big data flow in real time according to the traffic service demands, and generating a cleaned real-time data flow; the loading module is used for loading the risk rule to the rule engine, converting the risk rule into an executable rule model, and performing dynamic adjustment to generate an initialized rule engine; the matching module is used for performing real-time risk identification and rule matching according to the real-time data stream and the rule engine, and generating a risk identification result set based on a matching result; and the early warning module is used for carrying out early warning triggering according to the risk identification result set and pushing corresponding early warning information to the user in real time so as to realize comprehensive analysis, research and judgment of the traffic service management big data. By using the embodiment of the invention, the potential risk in the traffic business process can be effectively analyzed, researched and judged, and the accuracy and timeliness of risk identification are improved.

The invention discloses an investment and research information sharing and distributing method for group business management and control, and relates to the technical field of data sharing, and the method comprises the following specific steps: information collection and integration: collecting an external authority information source and capturing related investment and research information by using a network robot, according to the method, multiple authoritative external information sources are regularly monitored and sorted, investment and research data generated by the internal business departments of the group are collected, the universality and accuracy of the information sources are ensured, meanwhile, intelligent screening is carried out by utilizing a rule-based expert system, and the accuracy of the information sources is improved. According to the method and the system, the pertinence and availability of the information are further improved by combining the social relation data with the user portraits and the project requirements, and the personalized and accurate pushing of the information is realized, so that the group enterprises can quickly obtain the information closely related to the business decision.

The invention provides an aero-engine test whole-process business management method and system, and belongs to the technical field of whole-process business management, and the method comprises the steps: extracting information in a test item information document and a tester information document, and determining structured data; on the basis of the structured data, forming an initial test plan, performing test personnel allocation optimization on the initial test plan, and determining a target test plan; generating a target test card on the basis of the target test plan, and continuously updating the target test card by adopting an editable block chain according to the data in the test process until the test is finished; and after the test is finished, the operation authority of the target test card is removed, and non-tampered and decentralized aero-engine test whole-process business data is formed. The information utilization efficiency of each link is effectively improved, the distribution rationality of testers is improved, and the safe storage of test data is ensured.

The invention relates to the technical field of business management, in particular to an artificial intelligence business intelligent docking service platform, in the invention, task dependency relationships are rearranged by adopting topological sorting, and waiting time and resource waste caused by improper dependency relationships among tasks are reduced through scientific execution sequence adjustment, so that the service efficiency is improved. The method comprises the following steps of: extracting a business semantic structure chart, mining tasks which can be executed in parallel, recombining an execution path, reducing redundant nodes and unnecessary delay of a process, improving the execution efficiency of the whole process, extracting key operation rules through natural language processing, establishing the business semantic structure chart by adopting a support vector machine, accurately reflecting the hierarchy and association relationship of the operation nodes, and improving the execution efficiency of the whole process. Visualization and operability of complex business logic are achieved, flow optimization is carried out through the greedy algorithm, node priorities are defined, adaptive execution paths are matched, high efficiency and execution accuracy of flow design are ensured, and the response speed, the resource utilization rate and the execution accuracy of the business flow are improved.

The invention provides an intelligent file handling guiding method and device, electronic equipment and a storage medium, relates to the technical field of self-service, is applied to a consultation file handling guiding robot interaction system with a built-in large language model LLM, and extracts a guiding word and a data analysis rule of a corresponding item from a business management platform according to an obtained item name; injecting the guide word into a cue word of a large language model LLM, performing closed domain dialogue with a user based on the large language model LLM, and guiding the user to provide necessary file handling information until the necessary file handling information is complete; and converting the necessary file handling information into a data format consistent with a business handling system according to the data analysis rule, automatically filling the data format into the business handling system, and displaying a file handling information filling result to a user. Therefore, through intelligent guidance of multiple rounds of conversations with the user and automatic data analysis and filling, the file handling efficiency is improved, and the user experience is enhanced.

The invention discloses a flower sales method and system based on big data, and belongs to the technical field of flower sales, the flower sales system comprises a core business management module, a privacy protection master control module and a data synchronization engine module, the core business management module is used for managing flower businesses, and the privacy protection master control module is used for managing the flower businesses; the privacy protection main control module is used for balancing data utility and privacy security through a layered architecture, and is particularly suitable for high-sensitivity data of the flower industry, and the data synchronization engine module is used for realizing synchronous real-time sharing and updating of data of a collection library, a user and a merchant, and storing the data. According to the invention, on the basis of realizing flower sales, user data privacy can be protected, and synchronization with fresh flower stock fresh data can be realized.

The invention relates to the field of business management, and discloses a business management method based on a station inspection platform, which comprises the following steps: collecting order demands and external environment data, establishing a dynamic system model of the order demands, carrying out Kalman filtering prediction, constructing an optimization model based on an optimal control theory and a variational method, and finally realizing optimization of a resource scheduling strategy. Demand fluctuation and uncertainty are processed, and resource configuration is dynamically adjusted by adopting a multi-level feedback mechanism; the invention further provides a service management system based on the station inspection platform. The service management system comprises a data acquisition module, a nonlinear dynamic model module, a demand prediction module, a resource scheduling optimization module, a random control module and a feedback control module. According to the method, a nonlinear dynamic system model and a Kalman filtering technology are combined, so that accurate order demand prediction and dynamic adjustment are realized; resource scheduling is optimized based on an optimal control theory, a random control model is introduced to cope with uncertainty, and a multilevel feedback mechanism ensures quick response and adjustment.

The invention relates to the technical field of engineering supervision, in particular to an engineering quality detection system which comprises detection equipment used for collecting detection data and transmitting the detection data to a data collection terminal; the business management platform is used for storing the check information and transmitting the corresponding engineering check information to the data acquisition terminal under the condition that the calling signal is received; the data acquisition terminal comprises an engineering data detection module; the engineering data detection module is used for selecting a detection item; matching a calling signal sent to a business management platform according to the detection item; obtaining corresponding project checking information; acquiring detection data of the corresponding detection equipment according to the detection items; and performing quality judgment on the detection data according to the project check information to obtain a quality detection result, supervising the project quality detection process, and improving the reliability of the project quality detection result.

The invention relates to the technical field of image data processing, in particular to a dynamic content recognition and conversion method and device, equipment and a storage medium, and the method comprises the steps: determining input content in a whiteboard and the content type of the input content; and determining a target conversion file of the input content by using the content type. Through the dynamic content recognition and conversion method, the input content is automatically analyzed and classified, the input content is quickly converted into various digital documents matched with the format corresponding to the input content, the method is suitable for various application scenes such as education, conferences, business management and process design, the decision and execution efficiency is remarkably improved, and the user experience is improved. And the working efficiency of standard normalized content output is improved.

The invention discloses a data management method and device of a security business management system and a storage medium, and relates to the technical field of query languages. According to the method and the device, the original query request language is processed in a manner of adding a plurality of headers and a plurality of expanded table contents corresponding to each header, so that the expanded table can cover more meaning expressions, then a plurality of initial LINQ query statements are generated according to the plurality of meaning expressions, and the query efficiency is improved. And determining a credibility parameter corresponding to each initial LINQ query statement according to the number of repetition times of each initial LINQ query statement. When the final LINQ query statement is determined, the LINQ query statement corresponding to the query request is screened out from the multiple initial LINQ query statements, and the final LINQ query statement meets the preset parameter screening condition, so that the query request given by the operation object is accurately converted into the corresponding LINQ query statement. And finally, the LINQ query statement can accord with the characteristics of data of the security business management system, and query operation can be completed more efficiently.

The invention relates to the technical field of engineering digitization and information, and discloses a water conveyance tunnel BIM model engineering management business application method, which comprises the following steps: carrying out management business carding, and determining an engineering unit hierarchical structure; uniformly coding the data information related to the management service and the hierarchical structure data of the engineering unit to form a service data coding result and an engineering division coding result; creating a water conveyance tunnel BIM model, and endowing model components with the codes to form BIM data carrying code information; inputting the business data and the BIM data carrying the coding information into a digital construction and management system, and associating the business data and the BIM data by using a common coding identifier; based on the association, business management digital applications of investment, progress, quality, safety and the like are carried out in a digital construction and management system. Through standardized data sorting and coding, fusion of the BIM model and engineering management business is realized, the problem of data splitting is solved, and the refinement and digitization level of water conveyance tunnel engineering management is improved.

The invention discloses an information search method and device, computer equipment and a storage medium, and belongs to the technical field of artificial intelligence. According to the method, through intelligent keyword combination and weight evaluation, the accuracy and relevance of search and query are improved, and compared with traditional keyword matching search, the method is based on the pre-trained keyword weight model, the importance of different keyword combinations can be automatically evaluated, invalid or low-relevance query is reduced, and the search efficiency is improved. Meanwhile, a deep learning model is adopted to optimize search query statements, so that the search query statements are more in line with user intentions, the quality of search results is enhanced, the accuracy of information retrieval is improved, and the cost of manually screening and adjusting search keywords is reduced. In a mass data environment, the information method provided by the invention can be applied to business management program systems of financial science and technology, medical treatment, health, old-age care and the like, and more intelligent and efficient information search experience is provided for users.