240 results about "Customer requirements" patented technology

The invention discloses a parcel logistics multimodal transport cooperative scheduling method based on big data, which relates to the technical field of big data, and comprises the following steps: when an information monitoring terminal monitors an abnormal condition, triggering dynamic correction of a transport efficiency coefficient, a cost fluctuation coefficient and a service risk coefficient; and when the absolute value of the difference value between the updated evaluation index and the original evaluation index exceeds a preset threshold value, the scheduling decision terminal re-executes the scheme generation process to generate an emergency scheme. Through a built-in evaluation model, according to scheduling modes such as cost priority, timeliness priority and safety priority selected by clients, weights are dynamically allocated, evaluation indexes are output, a transportation mode combination is generated in combination with a genetic algorithm, time connection verification and equipment matching verification are carried out, multi-target collaborative optimization is realized, different client requirements can be flexibly adapted, and the method is suitable for large-scale popularization and application. And the transportation efficiency, the cost and the safety are balanced, and the multimodal transport resource allocation efficiency is improved.

The invention relates to the technical field of business service dynamic optimization, in particular to a customer demand dynamic analysis and consultation service optimization platform based on deep learning, which comprises a user portrait module, an intention analysis module, a knowledge graph module, a learning engine and a recommendation module, the intention analysis module is connected with the knowledge graph module, the knowledge graph module is connected with the learning engine and the recommendation module, the learning engine is connected with the user portrait module and the recommendation module, and the recommendation module is connected with the user portrait module; according to the method, the accuracy of new user demand understanding is remarkably improved, the system can still provide accurate services in the absence of historical data through dynamic extension of the knowledge graph and an incremental learning mechanism, the problem of insufficient personalization caused by user portrait missing is thoroughly solved, and the user experience is improved. And meanwhile, the security and adaptability of data processing are ensured through multi-modal analysis and federal learning.

The invention relates to an auxiliary verbal skill self-adaptive generation method fusing a knowledge graph and reinforcement learning, and belongs to the technical field of artificial intelligence and service compliance management crossing. The method comprises the following steps: collecting service data, extracting entities, attributes and relationships among the entities through natural language processing, constructing a knowledge graph marked with compliance attributes, and establishing an updating mechanism; determining a verbal skill generation main body according to an actual service scene, and integrating a conversation context, a client real-time state and a business target construction environment state; the verbal skill generation subject retrieves associated business knowledge according to the current environment state, and after the seat selects adaptive verbal skill interaction, verbal skill generation strategy parameters are updated through deep reinforcement learning; and constructing a multi-dimensional effect evaluation method based on the business data, feeding back an evaluation result to an iteration link, and optimizing reward calculation and knowledge graph association logic. Dynamic self-adaption of verbal skills in multiple service scenes is realized, and customer demand solving efficiency and business conversion quality are improved.

The invention relates to the technical field of business process management, in particular to a data processing method, system and device based on business process management and a medium, and the method comprises the steps: constructing a business process model driven by an abstraction layer, and configuring a multi-protocol standardized interface; according to the business process model driven by the abstraction layer and the multi-protocol standardized interface, a process instance matched with the business scene is generated, and a task is distributed to a target client according to a task demand; managing form state circulation and node jump logic according to a task control engine; an event monitor is deployed through a process key node to monitor the process, and when the process reaches a specified node, external service calling operation is triggered to form an end-to-end automatic closed loop. Therefore, the problems of code redundancy, high maintenance cost, difficulty in quickly adapting to diversified customer requirements and the like due to the fact that business process management generally needs to be subjected to customized development for different subsystems in related technologies are solved.

The invention relates to the technical field of bank customer marketing scenes, in particular to an intelligent marketing decision-making system based on dynamic customer grouping. Comprising a data acquisition and preprocessing module, a dynamic customer grouping module, a multi-channel marketing collaboration module, a marketing effect evaluation and optimization module, a data security and privacy protection module and a customer feedback and complaint processing module. According to the intelligent marketing decision-making system based on dynamic customer grouping, the real-time data acquisition and preprocessing module is adopted, customer behavior data are captured in real time through a stream processing engine, real-time cleaning and standardization processing are carried out, meanwhile, the dynamic customer grouping module carries out dynamic grouping according to the customer real-time behavior data by using a deep clustering algorithm, and the dynamic customer grouping efficiency is improved. A traditional static grouping rule is replaced, the data timeliness is improved, marketing decisions can be based on latest customer behavior data, and market changes and customer demands can be captured in time.

The invention relates to a product customization and configuration method and system based on a product model and a knowledge base. The method comprises the following steps: (a) associating a product structure model and a product knowledge base of a target product series; (b) constructing a product configuration model integrating a product structure model, a product knowledge graph and a configuration rule; (c) customer demand parameters are received, and a customized configuration scheme is generated through the product configuration model; (d) automatically generating a design material list and a process material list based on the customized configuration scheme; and (e) executing cost accounting according to the generated design bill of material and the process bill of material and outputting quotation data. The method has the advantages that the requirement of a user for customization can be met, the requirement for configuration can also be met, data such as technologies and processes can be automatically configured for the user, the data can be synchronously updated to related software systems such as PLM and PDM, and the intelligent design and intelligent manufacturing capacity of an enterprise is greatly improved.

The invention relates to the technical field of intelligent window scheduling, in particular to a multi-objective optimization intelligent window dynamic scheduling method and system combined with business rules. The method comprises the following steps: acquiring reservation queuing data, customer demand characteristics and window state data associated with each service window in real time; based on real-time collected data, a multi-objective optimization function including global average waiting time minimization, overall service efficiency maximization of all windows and global resource utilization balance degree maximization is constructed; solving the multi-objective optimization function based on a sorting genetic optimization algorithm; selecting an optimal scheduling strategy through a multi-factor fuzzy decision maker; and dynamically allocating window service resources according to the optimal scheduling strategy, and adjusting a window service queue in real time. By constructing the multi-objective optimization function, the resource waste problems of partial window congestion and partial idle windows caused by traditional fixed rule scheduling are effectively avoided, and the overall rationality and efficiency of window scheduling are improved.

The invention, which relates to the technical field of printing production management, discloses a production processing tracking system and tracking method for a printing industry, and the method specifically comprises the steps: creating a corresponding production order in a preset printing production management system based on customer demand information, generating a unique identification code for each production order according to a dynamic random number algorithm, and associating and binding the unique identification code with each production order; obtaining a process node of each production order associated with the unique identification code to construct a process dependency graph of each production order; calculating the remaining delivery time of each production order associated with the unique identification code, and sorting each production order in real time to construct a self-adaptively updated priority scheduling queue; obtaining a current process node of each production order, and obtaining a state attribute of each process node of each production order and a corresponding execution progress; and carrying out full-link visual display on the state attribute of each process node of each production order and the corresponding execution progress, and inputting a unique identification code through a client to carry out query.

The invention discloses an internet scene-oriented date selection method and device and electronic equipment, and relates to the technical field of distributed systems or other related fields, and the method comprises the following steps: receiving an operation request initiated by user side equipment to a calendar panel, the interaction mode for initiating the operation request comprises manual input, visual selection or voice interaction; a date selection process is generated according to the operation request and the interaction mode, and the process logic of the date selection process is determined by the interaction mode; the date selection process is executed, an execution result is obtained, and the execution result is used for recording a user intention date corresponding to the operation request; and returning the execution result to the calendar panel of the user side equipment. According to the invention, the technical problems that the operation mode in the internet date selection scene is single and the customer demand cannot be met in the related technology are solved.

The invention discloses a transportation route optimization method and system based on the Internet of Things, and relates to the technical field of transportation route optimization, by integrating multi-source environment information and combining dynamic traffic data and transportation vehicle position data, transportation route planning is more intelligent and flexible, and when traffic jam, sudden accidents or road closing occur, the transportation route can be optimized more intelligently and flexibly. The system can detect the traffic condition of a transportation path in real time and recalculate and optimize the path through cloud computing when needed so as to ensure that the transportation task is completed on time, and the method not only can automatically adjust the transportation path, but also can continuously monitor the transportation process according to the real-time feedback data so as to ensure that the distribution is smoothly carried out, and meanwhile, the transportation efficiency is improved. A self-adaptive compensation algorithm is adopted to correct path deviation, so that the transportation route can be quickly adjusted, the transportation efficiency and customer requirements are ensured to be met in time, the transportation flexibility, timeliness and safety are greatly improved, and the development of intelligent transportation and logistics management is promoted.

A system for generating a bill of materials comprising one or more product recommendations aligned with customer requirements, comprises a bill of materials processing device. The bill of materials processing device is configured to execute an AI-based recommendation engine. The recommendation engine is configured to receive customer data from one or more user inputs, retrieve product data from a product data source, and retrieve transaction data from a transaction data source. The recommendation engine includes a pre-processing module, training module, and inference module. The pre-processing module executes one or more pre-processing techniques to translate the data into a program-compatible format. The training module executes training and inference processes to generate the bill of materials. The training processes put the data in better condition for the inference module. The inference module uses two or more product recommendation processes to evaluate the data and to generate the BOM in a machine-readable format.

The invention discloses a hardware configuration method of a device, an electronic device and a storage medium, and the method comprises the steps: carrying out the filtering selection of hardware in a database for many times through a method flow containing a hardware resource database (a preset hardware knowledge base), customer demands (configuration condition information of a to-be-configured device), and an optimal assembly scheme (a target configuration strategy); and the final selection of hardware is carried out through a mode of comprehensively considering the enterprise inventory priority, the performance matching degree and the cost coefficient, so that rich hardware information basis and accurate customer requirements can be provided, and finally, the optimal assembly scheme considering both the performance and the cost can be generated through the selected target hardware. According to the method and the device, balance and optimization of different factors are realized, so that the technical problem of how to quickly determine a configuration scheme considering performance and cost in the hardware configuration process of the server can be solved, and the technical effect of efficiently realizing intelligent generation and optimization of a hardware assembly scheme of equipment is achieved.

The invention discloses a power customer demand management method, system, equipment and medium based on a data warehouse, and belongs to the technical field of power customer demand management, and the method comprises the steps: collecting multi-source data in real time, carrying out the multi-level verification, carrying out the data cleaning and standardization, integrating multi-dimensional data through a snowflake-shaped data model, and carrying out the management of the multi-dimensional data. And data extraction, conversion and loading are carried out through an ETL process, customer groups are divided by using a clustering algorithm, a regulation and control strategy is generated in combination with a dynamic threshold and a hierarchical competing rule, and parameters are optimized through closed-loop feedback. According to the method, the problem that a traditional method is slow in response in a complex scene is solved, and autonomous evolution of system parameters is achieved by fusing a closed-loop optimization system of incremental learning and attenuation coefficients.

The invention discloses a multi-agent collaborative real-time dynamic travel planning method and system, and relates to the technical field of computer application, and the method comprises the steps: collecting travel appeal information of a user; judging the space-time rationality of the travel appeal information, if the travel appeal information does not have the space-time rationality, judging that the space-time is unreasonable, otherwise, judging that the space-time is reasonable; when the time and space are judged to be reasonable, planning to obtain corresponding travel itinerary information based on the path distance and the path time consumption; wherein the travel appeal information comprises a departure place, a destination, optional scenic spots, travel days, departure time, accompanying person information, accommodation preference and travel preference. According to the method and the device, time-space rationality judgment is performed in advance based on the personalized travel demands of the users, and then information matching is performed, so that travel planning information meeting customer demands is pushed conveniently and intelligently, the actual demands of the users are met, and the authenticity, rationality and accessibility of the travel are comprehensively considered in the generated travel.

The invention relates to the crossing field of artificial intelligence and hotel informatization management, in particular to a hotel knowledge base self-learning correction method, system and device and a medium. The method comprises the following steps: acquiring a client call voice stream, and preprocessing to obtain voice data; inputting the voice data into a preset multi-modal analysis model and an incremental learning model to generate a knowledge correction decision; updating a knowledge base version and an AI response generator based on the knowledge correction decision, and obtaining customer satisfaction feedback; and adjusting the knowledge correction decision through the feedback. And a knowledge correction decision is automatically generated by using a multi-modal analysis model and an incremental learning model, and a knowledge base version is quickly updated based on the decision. By means of the process, automatic correction of knowledge is achieved, the knowledge updating period is greatly shortened, the knowledge base can reflect latest service information and customer requirements in time, and the timeliness and accuracy of the knowledge base are improved. By incorporating the implicit knowledge into the knowledge base, the knowledge base is richer and more comprehensive.

The invention belongs to the technical field of urban logistics and resource management, and provides a logistics resource scheduling method based on rule guidance and hierarchical greedy, which comprises the following steps: S1, customer demand structured analysis; s2, carrying out multi-dimensional logistics resource attribute modeling; s3, realizing resource filtering through rule guidance; s4, defining a combined path template; s5, obtaining an optimal solution through a hierarchical greedy resource matching algorithm for resource scheduling; comprising the following specific steps: S5.1, carrying out resource level dependence modeling; s5.2, setting a comprehensive matching degree algorithm and a matching priority rule; and S5.3, optimizing a resource combination path based on a hierarchical sequence and a greedy strategy. The method can adapt to different customer requirements to realize the reasonability of resource combination, and can also guarantee better resource matching efficiency.

The invention discloses a multifunctional automatic aging system and method, and the system comprises a multi-parameter measurement module, an integrated oscilloscope, a universal meter and a temperature sensor, and is used for measuring the output voltage ripple, the output voltage value, the output current value and the surface temperature of an aging module in real time; the data comparison and judgment unit is used for automatically comparing the real-time measurement data of the multi-parameter measurement module with a preset standard value, recording unqualified data and identifying the corresponding aging module; the abnormity monitoring and processing unit is used for monitoring over-temperature, over-current and overload abnormal states in the aging process in real time, triggering alarm and executing preset processing operation; the database module is used for storing all test data and supporting production process tracking and problem tracing based on the stored data; the report generation module is used for automatically screening test data according to customer requirements and generating a standardized test report; and the control software unit is provided with modules for setting aging time, selecting models of products to be tested, configuring test functions, reporting templates and the like.

The invention discloses a user interaction system and method based on a digital human, and the system comprises a data acquisition module which is used for collecting user voice data; the dynamic judgment module is used for calculating and obtaining a voice detection threshold value through a dynamic threshold value model based on the user voice data, and judging whether an interruption mechanism is triggered or not; the voice recognition and analysis module is used for converting the voice data of the user into text information and acquiring potential intentions of the user; the knowledge graph matching module is used for generating a response text according to the potential intention of the user and performing interaction through a digital human; the semantic matching module is used for judging whether a secondary interruption mechanism is triggered or not; and the information recording module is used for recording the current broadcasting progress and the key information. Effective interruption and mistaken interruption can be intelligently distinguished, blind pause of broadcasting or missing of customer requirements is avoided, and interaction fluency is greatly improved; and secondary interruption judgment satisfies interaction habits of different clients, and can recover from a logic node after interruption, so that the service efficiency is improved.

The invention discloses a hotel customer demand intelligent analysis and response method, device and equipment and a medium, and relates to the technical field of hotel management intellectualization, and the method comprises the steps: mapping a customer behavior time sequence data set into a hypergraph structure, calculating an attention weight coefficient based on a multi-head attention mechanism, and generating a hypergraph feature vector; constructing a resource state graph based on the resource state time sequence data set, inputting the hypergraph feature vector and the resource state graph into a multi-objective optimization model based on the game theory, defining a customer satisfaction function, a hotel revenue function and a resource consumption function, and taking the functions as game participants; calculating a non-dominated solution set of a game participant in an equilibrium state through a Pareto frontier solver, and screening out an optimal response strategy; according to the method, the multi-modal data are dynamically fused through the hypergraph feature vectors and the multi-head attention weights, and the problem of multi-modal data relevance missing is solved.

The invention relates to a multi-target logistics distribution path optimization method based on AI, and the method comprises the following steps: obtaining order data, road network data and vehicle data of logistics distribution of a customer point, extracting basic information from the three types of data, and constructing the multi-dimensional features of the customer point; inputting the multi-dimensional features of the customer points into a pre-trained graph attention network for feature embedding, generating a distribution network feature graph fusing customer demands and a road network relationship, inputting a pre-trained reinforcement learning agent, and generating an initial path population with quality and diversity balance; performing iterative optimization on the initial path population based on a Memetic algorithm framework; and calculating the fitness of each individual on a plurality of preset optimization objectives, maintaining a Pareto solution set by adopting a multi-objective evolutionary algorithm with reference points, and recommending a final path scheme from the Pareto solution set based on user preferences. The method has the effect of remarkably improving the quality, efficiency and dynamic adaptability of path optimization.

The invention relates to the field of English customs consultation, and discloses an English customs consultation-oriented multi-agent collaborative workflow construction method, which comprises the following steps of constructing a four-dimensional dynamic hypergraph; converting the four-dimensional dynamic hypergraph into tensor representation, performing tensor decomposition, and identifying key agent role nodes under a high weight dimension; constructing an alliance value function and carrying out optimization solution; respectively representing Chinese and English input by adopting an encoder, generating a semantic representation vector, and obtaining a structured semantic fusion result; and carrying out incremental updating on system weight parameters to realize model synchronization of dynamic policy contents. According to the invention, a multi-agent cooperation mechanism and a dynamic hypergraph construction technology are adopted, and real-time information integration in English customs affair consultation is realized. According to the technology, the accuracy of policy interpretation is remarkably improved, and compared with an existing information access information processing technology based on a static database, the problem of information isolated island is solved, and customer requirements are responded in time.

An exhibition stand design intelligent generation system based on multi-modal semantic analysis belongs to the technical field of design and comprises a data acquisition and labeling module, a multi-stage semantic analysis module, a multi-modal fusion generation module, a dynamic style adaptation implementation module and a test and optimization module. The data acquisition and labeling module comprises an industry label determination sub-module, an exhibition stand space size design sub-module, a function partition sub-module and a display product sub-module; the multi-stage semantic analysis module comprises a domain knowledge graph determination sub-module and a semantic analysis model establishment sub-module; the multi-modal fusion generation module comprises a two-channel Transform architecture sub-module, a three-dimensional layout generation sub-module, an input sub-module and an AIGC large model establishment sub-module; the dynamic style adaptation implementation module comprises an industry feature coding sub-module and an adversarial training strategy sub-module; the application method of the exhibition stand design intelligent generation system based on multi-modal semantic analysis comprises five steps. According to the method, the exhibition stand design scheme meeting the customer requirements can be quickly generated, the multi-view effect picture is output, and the exhibition service response speed and the customer experience can be improved.

This disclosure provides a service recommendation method, apparatus, electronic device, medium, and product, relating to the field of computer technology. The method includes: filtering available services based on customer needs to generate a candidate service list; for each candidate service in the candidate service list, constructing an input sequence of the candidate service based on the customer needs and the candidate service; inputting the input sequence of the candidate service into an analysis model to obtain the matching degree between the candidate service and the customer needs; and obtaining a service recommendation result based on the matching degree between all candidate services in the candidate service list and the customer needs. This method can accurately identify the complex interaction relationships between customer needs and services, improving recommendation accuracy.

The application relates to the technical field of order allocation, in particular to a dynamic distribution order allocation optimization method considering the supply-demand state of a transport capacity system.S1, a dynamic pickup and delivery problem model is constructed, the dynamic pickup and delivery problem system state and the action set are determined, and the dynamic pickup and delivery problem model is constructed;S2, a rolling time sequence mechanism is adopted to describe the dynamic nature of the urban dynamic pickup and delivery problem; and S3, a mixed allocation strategy is adopted to allocate the dynamic distribution order.The dynamic distribution order allocation optimization method considering the supply-demand state of the transport capacity system optimizes the design of the order allocation, efficiently allocates a scheme and a solution algorithm, realizes the matching of efficient dynamic time requirements and distribution resources, reduces the distribution cost and improves the distribution punctuality rate; meanwhile, the efficient order allocation strategy and the distribution optimization search operator based on the transport capacity supply-demand are designed, the response speed of the distribution system to the dynamic time requirements is improved, the distribution service quality of the distribution enterprise to the market and the customer requirements can be improved, and the distribution cost is optimized.

The invention relates to an intelligent order placing method and device for designated driving service, computer equipment and a medium. The method comprises the following steps: acquiring original customer demand data through a target order placing channel; preprocessing the original customer demand data to obtain customer demand text information; performing semantic recognition on the customer demand text information, and extracting key business information from a semantic recognition result; detecting whether the key service information contains necessary service information or not; if yes, formatting the key service information according to an order issuing protocol, and performing service information supplement on the formatted key service information to obtain complete service information; and sending an order placing request carrying the complete business information to a transaction system to generate a designated driver order. According to the method, key business information is automatically extracted from multi-source data and complete business information is generated through data preprocessing and a semantic recognition algorithm, automatic ordering of designated driving service is realized, and efficiency and accuracy are improved.

The invention belongs to the technical field of building design, and discloses an environment-friendly fabricated building modular design method. The method comprises the steps that customer demand data is acquired and analyzed, building components are determined, and adaptive components are screened out from a pre-constructed modular component library; building components which do not exist in the modular component library are marked as missing components, and all the missing components are subjected to personalized design; combining all the adaptive components and the missing components to form a fabricated building model, comprehensively evaluating the environmental protection performance, and judging whether a component optimization instruction is generated or not; if the component optimization instruction is generated, evaluating the environmental protection performance of each adaptive component and the missing component, and identifying a defective component; parameter optimization is carried out on each defective component, and a design scheme is generated; according to the method, diversified building requirements can be effectively met, in-depth analysis and customized design of building components are achieved, and the environmental influence is reduced to the maximum extent.

According to the manufacturing method of the screen cloth for the solar photovoltaic screen printing plate, the screen cloth is woven by adopting various warp and weft combinations, so that downstream customers can meet the requirements of various properties and the service life more flexibly according to the requirements of the customers. Warps and wefts with different diameters and different meshes are adopted for mixed weaving, according to customer requirements and market requirements, different weft diameters and different warp and weft mesh numbers are set for weaving, and the method comprises the following specific steps that S1, tungsten filaments used for weaving are wound on a raw material shaft according to reed parameter indexes; s2, enabling a tungsten filament for weaving a net to penetrate through a palm sheet and a reed, wherein the palm sheet is divided into a front sheet and a rear sheet; s3, uniformly adhering the warp yarns penetrating through the palm sheet and the reed to an adhesive tape; and S4, driving the weft yarns to weave through reciprocating motion of the rapier belt.

The invention provides a customer demand function and production line function bidirectional decoupling-oriented efficient production line software integration method suitable for a laser radar. The method mainly comprises the following steps of customer business demand analysis and development, customer production line function demand confirmation, business demand side and production line side combination, small-batch verification, customer evaluation and mass production software generation. According to the method, the production efficiency can be improved to the greatest extent while the business demand side and the production line demand side of a customer are developed in a combined manner, intersection point type integration is adopted during production, production line functions are associated with communication addresses after leaving a factory, and secondary password + physical separation is performed, so that the functions of the business side are not influenced, and the production efficiency is improved. And the subsequent self-upgrading of a business demand side and a production line side is not influenced.

The utility model discloses an intelligent lintel billboard system for a micro-module data center channel. The intelligent lintel billboard system comprises a data collector, a data processing box, a strip-shaped display screen and a power distribution system, the data acquisition unit is provided with an LAN interface, a COM interface, a DI interface and a DO interface, key data of the micro-module data center are acquired through the data acquisition unit, the key data are acquired through the data acquisition unit and processed into visual data through the data processing box, and then the visual data are displayed through the strip-shaped display screen. According to the intelligent lintel system, platforms such as cross-WINDOWS web / Android APP / IOS web and the like are supported, networking communication is simple, display content is rich, functions are comprehensive, an interface configuration design module in the data processing box can circularly play videos and pictures and customize a welcome interface according to customer requirements, and the requirements for multiple functions and customization of the intelligent lintel system of the micro-module data center channel are met.

The utility model discloses a three-coordinate measuring tool for an ECU cover part, relates to the technical field of ECU cover three-coordinate measurement, and aims to solve the problem that in the prior art, a current new product ECU cover needs to be subjected to size measurement according to customer requirements in the production process, so that the situation that the size problem of the part flows out to a client and is not found is avoided. In the prior art, a tiger table is used to fix a part, the position of the part is difficult to fix, the part is easy to loosen, the individual size is interfered, and the part cannot be completely measured by three coordinates. An ECU cover is arranged on the base, a preset hole site is formed in the inner side of the base, a first fixing bolt and a second fixing bolt which are used for fixing are arranged between the ECU cover and the base, an adjustable pressing mechanism used for pressing the ECU cover is fixedly installed on the base, and the adjustable pressing mechanism comprises a stand column. A supporting table is fixedly installed on the stand column, and a position adjusting leg and a locking leg are rotationally connected to the supporting table.