183results about How to "Improve service experience" patented technology

The invention provides a smart park optimization method and device based on digital twinning and BIM, and the method comprises the steps: collecting the actual information of a park, and carrying out the preprocessing; based on the configured basic BIM model, integrating the basic BIM model by using actual information; constructing a three-dimensional digital twinborn model, and fusing the integrated BIM model with the three-dimensional digital twinborn model; and analyzing and processing the park operation data by using the current fused three-digit digital twinborn model so as to realize park optimization. The digital mirror image of the smart park is constructed by integrating digital twinning, BIM, Internet of Things, big data, cloud computing, GIS and other frontier technologies, and comprehensive perception, accurate analysis, intelligent decision and efficient management of the park are realized. According to the scheme, the intelligent level, the operation efficiency and the sustainable development capability of the park are improved, and convenient, efficient and intelligent service experience is provided for park managers, settled enterprises and individual users.

According to the intelligent home environment intelligent regulation and control system and the control method thereof, various intelligent sensors are arranged, various environment data such as indoor temperature, humidity and illumination are monitored in real time, the data are preprocessed and then sent to a data analysis layer, data features are extracted according to the monitored data and historical data based on the deep learning technology, and user preferences are deduced; the control parameters are adjusted and sent to the equipment control layer, a specific instruction is sent to an indoor smart home, an air conditioner, a humidifier or a curtain and the like are controlled to accurately control the indoor environment, the living preference of a user is met, and in the process, the effect monitoring and dynamic adjusting layer monitors the adjusting condition in real time, and the user experience is improved. If the ideal effect is not achieved after adjustment, the equipment control layer is controlled to continue adjustment, in the process, the abnormal condition of the system is detected, the power consumption of the equipment and other data are monitored at the same time, normal work of the system is guaranteed, possible faults are predicted, a user is reminded in time, and safe and energy-saving operation of the whole system is guaranteed.

According to the intelligent energy-saving analysis method based on the building information model (BIM), building thermal performance parameters and an intelligent simulation algorithm are integrated, building heat conduction, a heat bridge effect and solar heat gain are accurately simulated, and a scientific basis is provided for design. Meanwhile, an energy-saving optimization strategy is automatically generated, such as wall thickness adjustment and window design, so that energy consumption is reduced. Besides, a multidisciplinary cooperative working platform is established, effective implementation of energy-saving measures is ensured, and energy use and maintenance tracking of the whole life cycle of the building are realized and energy-saving performance is continuously optimized in combination with an energy management system. The innovation of the method lies in the automatic and intelligent analysis process, and a comprehensive solution is provided for the field of building energy conservation.

The invention discloses an automobile fault diagnosis method and system, and belongs to the technical field of fault diagnosis, and the system comprises an automobile fault identification model, an automobile fault knowledge graph model and a reasoning diagnosis integration model. S100, acquiring a natural language description text of the automobile fault, preprocessing the natural language description text of the automobile fault, and extracting a description entity related to the automobile fault; s200, constructing an automobile fault identification model, inputting the description entity related to the automobile fault into the automobile fault identification model, and outputting a fault type; s300, constructing an automobile fault knowledge graph model, inputting a description entity and a fault type related to the automobile fault into the automobile fault knowledge graph model in combination with Cypher to perform semantic similarity matching, and querying a matched answer; and S400, constructing a reasoning and diagnosis integrated model, inputting the description entity and the answer related to the automobile fault into the reasoning and diagnosis integrated model in combination with prompt, and outputting a fault analysis result and a visual correlation analysis result.

The invention relates to the technical field of computers and finance, and particularly discloses a fraudulent behavior identification method and device, a storage medium and computer equipment, and the method comprises the steps: obtaining a plurality of to-be-identified complete call records, segmenting each complete call record, and obtaining a plurality of record segments; for a plurality of recording segments, identifying the recording segment with the dialogue role as the user from the recording segments, determining a target recording segment based on the recording segment with the dialogue role as the user, performing voiceprint feature extraction on the target recording segment, obtaining voiceprint feature vectors based on an extraction result, and performing clustering processing on each voiceprint feature vector; determining suspected fraudulent call records from all the complete call records according to a clustering result; and for each suspected fraudulent call record, converting the suspected fraudulent call record into text data, determining a fraudulent probability score corresponding to the text data through the large model, and judging whether the suspected fraudulent call record comprises a fraudulent behavior based on the fraudulent probability score.

The invention discloses a method and device for providing insurance consultation service, equipment and a storage medium, and belongs to the technical field of artificial intelligence. The method comprises the following steps: performing semantic analysis on a consultation question text to obtain key text information; mapping the key text information to a pre-constructed insurance domain knowledge graph to obtain an initial query node set; searching associated knowledge nodes directly or indirectly connected with each initial query node in an insurance domain knowledge graph; calculating relevancy scores among the associated knowledge nodes, obtaining the knowledge nodes with scores ranked in the first N positions according to the relevancy scores, and constructing a knowledge sub-graph based on the first N positions of knowledge nodes; the knowledge sub-graph is expanded and supplemented; and converting the extended knowledge sub-graph into an answer text in a natural language form. The invention further relates to the technical field of block chains, and the problem text is stored on a block chain node. According to the invention, comprehensive knowledge related to the question can be provided, and the accuracy and efficiency of consultation service are improved.

The invention provides a method for accessing user equipment to a vehicle-mounted system in a cross-system virtual manner and navigating, which comprises the following steps of: in a cross-system virtual access process, converting an operation request and a data transmission instruction of the user equipment into a format which can be identified by the vehicle-mounted system through a virtualization middleware technology, and performing encryption and integrity verification on transmission content; the compatibility and security of communication are ensured; a heartbeat detection mechanism between a vehicle-mounted system and user equipment is established, network connection quality is evaluated in real time by periodically sending probe packets and monitoring response time, and if overtime or too high packet loss rate is found, a standby link is automatically switched to ensure seamless connection and service continuity; historical load data of a vehicle-mounted system are analyzed through a machine learning algorithm, a load prediction model is constructed, and computing resources and network bandwidths are dynamically scheduled and reserved in advance according to spatial and temporal distribution characteristics of navigation requests, so that resource bottlenecks and service congestion are avoided.

The invention provides an intelligent energy-saving analysis method for thermal performance of a building based on BIM (Building Information Modeling). The intelligent energy-saving analysis method comprises the following steps of: scanning the building in all directions by using a three-dimensional laser scanning technology to obtain three-dimensional geometric data of the building, and constructing a BIM model in BIM software based on the three-dimensional geometric data of the building; thermal performance parameters of the building envelope are integrated in the BIM model; based on the thermal performance parameters, utilizing a thermal performance simulation algorithm to simulate heat conduction, a heat bridge effect and a solar heat gaining condition of the building; and automatically generating an energy-saving optimization strategy according to a simulation result of the thermal performance simulation algorithm by utilizing machine learning and an energy-saving optimization algorithm. According to the method, a comprehensive, accurate and automatic analysis and optimization method can be provided for the field of building energy conservation, remarkable improvement of building energy efficiency and effective reduction of energy cost are facilitated, and meanwhile, convenient, efficient and personalized service experience is provided for users.

The invention relates to the technical field of inter-city cargo splicing and loading, in particular to an inter-city cargo splicing and loading transportation path optimization algorithm based on large model optimization, and solves the problems that in the prior art, an optimization algorithm based on a large model generally relates to a complex calculation process and needs a large amount of calculation resources and time, and especially in a real-time path planning scene, the calculation process is complicated. And the calculation delay can influence the transportation efficiency. The invention discloses an inter-city cargo splicing transportation path optimization algorithm based on large model optimization. The algorithm comprises data collection and preprocessing, model construction and training, algorithm optimization and verification, path optimization calculation, result evaluation and feedback, and algorithm deployment and application. According to the method, various possible transportation paths are analyzed and compared through an algorithm, the optimal path is selected, unnecessary detour and waiting time is reduced, so that the transportation efficiency is improved, and the algorithm can perform intelligent scheduling and reasonable arrangement of transportation vehicles and routes according to real-time traffic conditions, cargo demands, vehicle states and other information.

The invention discloses a customized order receiving method and system for a designated driver based on a saas platform. The invention relates to the technical field of designated driving services. Receiving demand data of a driver, wherein the demand data comprises order receiving preference, a service area and service time; receiving personal information input by a driver, wherein the personal information comprises basic information and order receiving preference setting; wherein the demand data comprises order receiving preferences, service areas and service time of drivers and users; wherein the basic information comprises a name, a driving age and a vehicle type; according to the invention, the driver is allowed to set personalized order receiving conditions according to own order receiving preference, service area and time, so that the working flexibility of the driver is greatly improved. The driver can autonomously select the order suitable for himself / herself, so that the rejection rate of improper orders is reduced, and the working efficiency and the satisfaction degree are improved. And through an intelligent order receiving matching algorithm, the system can quickly match the most appropriate order for the driver, so that the empty driving time and waiting time of the driver are reduced, and the working efficiency and income are further improved.

The invention discloses a full-volume voice analysis method and device based on a large model, equipment and a storage medium. The method comprises the following steps: acquiring voice interaction data of an agent and a user; according to an artificial experience rule and a large language model, extracting attributes associated with a product service in the voice data as increment mark information; obtaining full-amount marking information after standardization of the voice interaction data; training the large language model by taking the voice interaction data, the incremental marking information and the full marking information as training data to generate expert model information; and matching a target seat, a target user and a corresponding target product according to the expert model, and feeding back to a calling system, so as to push a call strategy matched with the prediction information to the target seat. Through incremental marking and total analysis of the voice interaction data, the outbound strategy and the call strategy are accurately matched for the seat, and the service efficiency and the success rate of the seat and the user are improved.

The invention provides an elevator fault diagnosis method and device based on machine learning, a medium and equipment, and relates to the technical field of elevator fault diagnos.The elevator fault diagnosis method comprises the steps that firstly, time sequence data, environment data and operation and maintenance record data in historical operation of an elevator are obtained, and time sequence features and environment features are extracted; the operation and maintenance record data are evaluated based on an expert scoring method, and the elevator fault probability reflecting the elevator operation quality is generated; then, constructing and training a deep learning network model by using the features and the fault probabilities as labels; and finally, current time sequence data and environment data of the elevator are obtained in real time, corresponding features are extracted and input into the trained model, the current elevator fault probability is obtained, the current running state of the elevator is judged by comparing the current elevator fault probability with a preset fault threshold value, and therefore efficient and accurate fault diagnosis and early warning are achieved.

The invention provides an aquatic product traceability management method and system based on a block chain, and relates to the technical field of aquatic product management, the aquatic product traceability management method based on the block chain comprises the following steps: establishing an aquatic product traceability network platform, and obtaining aquatic product full life cycle data in real time; performing anomaly verification on the acquired aquatic product full life cycle data based on a data verification method, and storing the verified data in an encrypted form in an aquatic product tracing network platform through a curve encryption algorithm; collecting feedback information after the user inquires the aquatic product traceability information through the aquatic product traceability network platform; and analyzing the collected user feedback information, and adjusting and optimizing aquatic product full life cycle management according to an analysis result. According to the method, the data is stored to the block chain in an encrypted form through a curve encryption algorithm, so that the security and non-tampering property of the data are ensured, and comprehensive optimization and guarantee are provided for production and management of aquatic products.

The invention relates to a vehicle control method and a vehicle control system. The method comprises the following steps: establishing interconnection with a vehicle terminal; the desktop application is sent to the vehicle terminal, the vehicle terminal displays the desktop application on a display screen, and when a touch instruction for the display screen is detected, the touch instruction is sent to the mobile terminal; receiving the touch instruction and the intelligent cabin data sent by the vehicle terminal; and the intelligent cabin data is analyzed, a control instruction corresponding to the touch instruction is obtained, and the control instruction is sent to the vehicle end execution equipment so as to control the vehicle end execution equipment to respond to the control instruction. According to the invention, the intelligent cabin function of the vehicle is set in the mobile terminal, and the intelligent cabin function is operated by using the resource of the mobile terminal home terminal, so that the deployment of the intelligent cabin function at the vehicle terminal can be omitted, the experience of touch control of the vehicle terminal can be provided for a user, and the interconnection application of the mobile terminal and the vehicle terminal can be expanded.

The invention relates to the technical field of Internet of Vehicles communication, and discloses an Internet of Vehicles data acquisition full-link monitoring method, device and equipment, the Internet of Vehicles data acquisition full-link monitoring method comprises the following steps: firstly, transmitting acquisition data of different link sensors to an upstream data node; the upstream data node sends a monitoring application instruction to the downstream data node through the data bus after receiving the data, and if the downstream data node does not report data receiving state information in time, the system judges that the data is lost, locks data loss time and triggers an alarm signal of data loss of a corresponding link sensor; acquiring a server log of the upstream data node in a target time period according to the alarm signal; and finally, performing fault analysis on the server logs in the upstream data node target time period to obtain a data acquisition full-link monitoring result. Therefore, the stability and reliability of the Internet of Vehicles system are ensured, and better service experience is provided for users.

The invention belongs to the field of artificial intelligence and the field of financial science and technology, and relates to an artificial intelligence-based query information processing method and device, computer equipment and a storage medium, and the method comprises the following steps: analyzing input query information to generate a token sequence; acquiring a context and a special mark corresponding to the query information; generating an input sequence based on the query information, the token sequence, the context and the special mark; encoding the input sequence based on an encoder in the target prediction model to generate hidden representation; performing prediction processing on the hidden representation based on an extractor in the target prediction model, and generating prediction probability scores of all answer spans; determining a target answer span from all answer spans based on the predicted probability score; and generating an answer text based on the target answer span, and returning the answer text to the user. In addition, the invention also relates to a block chain technology, and the answer text can be stored in a block chain. The reply processing accuracy is improved, and the service experience of the user is improved.

The invention relates to the technical field of tourism information service, and discloses an AI accompanying service method and device applied to scenic spot tourism, and the method comprises the steps: obtaining scenic spot traffic information and user position information; calculating the commuting time of each road from the current starting point to the recommended scenic spot according to the scenic spot traffic information and the user position information; selecting the road with the shortest time as a recommended commuting route according to the commuting time; acquiring people number distribution information around the scenic spot, and calculating a people number distribution thermodynamic diagram according to the people number distribution information; according to the number of people distribution thermodynamic diagram, carrying out optimal playing route analysis to obtain a recommended playing route; and sending the people number distribution thermodynamic diagram, the recommended commuting route and the recommended playing route to a display device, and visually displaying to a user. The method can recommend the playing route according to the flow of people, and improves the use and playing experience of the user.

The invention provides an intelligent insurance claim settlement triggering system based on the Internet of Things technology, and the system collects data in real time through Internet of Things monitoring equipment disposed at the place of an insurance object, and carries out the analysis through a data processing unit. The core of the system is an intelligent claim settlement triggering algorithm which can automatically judge whether claim settlement requirements are met or not according to preset conditions. Once a specific event, such as a vehicle accident, a family fire or a health crisis, is detected, the system automatically triggers a claim settlement process through an intelligent contract to realize quick response. In addition, the system further comprises a user interaction interface, an insurance client and an insurance company are allowed to check the equipment state and the claim settlement progress in real time, and the safety and non-tampering performance of all data are ensured through the block chain technology. According to the system, through real-time monitoring and prediction analysis, the efficiency and customer satisfaction of the insurance industry are improved, the risk and cost are reduced, and an innovative automatic claim settlement solution is provided for the insurance industry.

The invention relates to the technical field of freight processing systems, and discloses a digital freight processing settlement system and a settlement method thereof. And the management module is in bidirectional communication connection with the user interface module, the order management module, the abnormity management module, the cost simulation module, the freight settlement module and the data analysis module, and is used for managing data information generated in the operation process of the system and carrying out corresponding system parameter setting and interface management according to each account permission. The freight calculation unit performs freight calculation according to a clear calculation formula and a rate table, supports the calculation of special fees such as overtime waiting fees, highway fees and bridge passing fees, and provides a detailed list of fees, so that a cargo owner and a driver can clearly know the source and calculation basis of each fee, thereby avoiding fee disputes and improving the efficiency of the system. And the smoothness in the freight processing process is improved.

The invention provides an intelligent community management robot system based on an artificial intelligence technology, and belongs to the technical field of intelligent community robots, and the system comprises a community data automatic sensing module which is used for automatically sensing and collecting community data, and obtaining multi-modal data; the multi-modal data integrated management module is used for performing centralized management and processing on the acquired multi-modal data to obtain single information flow data; the sustainable artificial intelligence calculation module is used for carrying out intelligent calculation and analysis on the single information flow data, identifying community service requirements, optimizing a service process and outputting an instruction of the community service requirements; the community governance service function module is used for providing intelligent services; and the community robot task execution module is used for providing a human-computer interaction interface and executing intelligent service according to the instruction required by the community service. The intelligent community management robot system solves the problems that the service function of an existing intelligent community management robot system is difficult to achieve, the resident participation degree is low and the intelligent degree is low.

The invention belongs to the technical field of automatic operation and maintenance, and particularly relates to an online agent automatic deployment management system. The foreground control system is used for providing a visual control panel for an administrator to set and adjust deployment, configuration information and behavior modes of the intelligent agent; the background monitoring system is used for carefully supervising the operation process of the intelligent agent and providing real-time and accurate information feedback for an administrator; the deployment operation system is used for converting an agent behavior strategy predetermined for the online platform into a specific behavior; the strategy algorithm system is used for providing an efficient and convenient automatic scheme for the operation of the intelligent agent. The invention is used for automatically deploying, managing and monitoring agents on a network online platform, and the system consists of a plurality of modules which work cooperatively to support various functions.

The invention relates to the technical field of equipment maintenance management, and discloses an RCM-based equipment repair and maintenance method and system, and the system comprises an equipment maintenance case cloud library search module, an equipment maintenance scheme analysis module, and an equipment maintenance scheme feedback module. Equipment overhaul and maintenance practical operation information autonomous analysis is carried out based on the essential working time, the travelled distance parameters and the specific equipment overhaul case cloud library object parameters of the equipment through a data search algorithm, and overhaul and maintenance practical operation data with the same running time and the same travelled distance as the overhaul and maintenance equipment are intelligently searched out; based on data statistics, overhaul and maintenance practical operation information with the maximum usage amount and the same running time and mileage as overhaul and maintenance equipment is efficiently and scientifically counted, the current optimal overhaul and maintenance scheme of the equipment is scientifically constructed, and the universality and scientificity of the overhaul and maintenance scheme of the equipment are guaranteed.

The invention provides a non-local verification code information authentication and acquisition method and device and a readable storage medium, and the method comprises the steps: responding to a received request of a target user for obtaining a verification code of a second communication identity through a first communication identity, and verifying whether the second communication identity is matched with the target user; if the second communication identity identifier is matched with the target user, acquiring a verification code of the second communication identity identifier; and sending the verification code of the second communication identity identifier to a terminal corresponding to the first communication identity identifier. The invention provides a non-local verification code information authentication and acquisition method, and the method comprises the steps: enabling a user to request an operator for obtaining a verification code of a second mobile phone number under the condition that the user holds a first mobile phone number, and transmitting the verification code of the second mobile phone number to the first mobile phone number if the operator determines that the second mobile phone number belongs to the user, therefore, the user can authenticate and acquire the non-local verification code information, so that more convenient service experience can be provided for the user.

The invention provides a dialogue generation method and device based on artificial intelligence, and the method comprises the steps: collecting a dialogue of a user in real time, carrying out the initial dialogue generation through a predefined basic reply template, replying the dialogue of the user, and obtaining the initial dialogue record information; performing context information fusion on the initial dialogue record information to obtain a fused context feature vector; performing semantic information fusion on the initial dialogue record information to obtain a fused semantic feature vector; performing secondary fusion on the fused context feature vector and the fused semantic feature vector to obtain a fused feature vector; and generating dialogue content for replying by combining the fused feature vector with the trained intention model. The device comprises modules corresponding to the steps of the method.

According to the intelligent VIP special elevator system and the operation method thereof, the response efficiency of an elevator to special elevator taking requests such as first aid and VIP services is effectively improved. According to the intelligent VIP special elevator system, an adding system is additionally arranged on an elevator system, and the intelligent VIP special elevator system comprises an operation scheduler, a task receiving mechanism, an outer calling shielding mechanism, an inner calling collecting and controlling mechanism, a door opening and closing control mechanism, a state detecting mechanism and a starting confirming mechanism. The system can automatically identify and respond to special elevator requests, shield non-special elevator requests, control the elevator to quickly arrive at a departure floor, and directly reach a target floor after an elevator rider enters. The system is widely applied to all elevators, special transformation of manufacturers is not needed, low cost is achieved, whole-process automatic operation is achieved during operation, and service efficiency and safety are improved. And only authorized elevator passengers can start the elevator through an identity verification mechanism, so that the safety of the system is enhanced. According to the intelligent VIP special elevator system and the operation method thereof, a more efficient, safer and more convenient solution is provided for elevator service.

The invention discloses a short multimedia message sending method, a short multimedia message sending system, a medium and a product, and relates to the field of information transmission. Selecting short and multimedia message sending channels of which the real-time load rates are lower than a preset load rate threshold value from the plurality of short and multimedia message sending channels as candidate channels; determining a short multimedia message feature data set according to the short multimedia message sending request; determining channel feature data according to the candidate channels; inputting the short multimedia message feature data set and the channel feature data into a preset sending failure probability prediction model to obtain a sending failure probability; when the sending failure probability exceeds a preset probability threshold value, sending the short multimedia message to the receiver through the standby channel; and when the sending failure probability is lower than a preset probability threshold, sending the short multimedia message to the receiver through the candidate channel. By implementing the method, the success rate of sending the short multimedia message can be improved.

The invention provides a voice recognition model training method, an intelligent customer service voice processing method and device, electronic equipment and a computer readable storage medium, and the method comprises the steps: obtaining voice sample data, generating a label for each piece of voice sample data, training a pre-training model through the voice sample data, obtaining a trained pre-training model, and carrying out dialect adaptability training on the pre-training model by using the voice sample data with the dialect label to obtain a dialect understanding model; and carrying out model fusion on the pre-training model and the dialect understanding model to obtain a language understanding model. According to the method, the label is generated for the voice sample data, the pre-training model is trained by using the dialects, so that the dialect understanding model can accurately identify the dialects, the model fused with the pre-training model can accurately identify mandarin and dialects at the same time, answers of the user during question making can be more accurately matched, the communication efficiency is improved, and the user experience is improved. And better service experience is brought to the user.

The invention discloses a data analysis platform based on a large model and a knowledge graph, which is characterized in that information nodes where entities and relationships related to user questions are located are quickly positioned through the knowledge graph; and a data processing and semantic comprehension algorithm based on artificial intelligence and natural language processing technologies is introduced at the rear end to carry out semantic splicing on the plurality of matched related information node semantics and user consultation question semantics to form prompt information, and the prompt information is input into a large model to generate a consultation answer of the user. Therefore, the knowledge graph and the large model technology can be comprehensively utilized to automatically generate the matched consultation answer according to the consultation questioning information of the user, so that the intelligent level of the data analysis platform is improved, the questioning background of the user can be better understood, the high-quality answer is given, and the user experience is improved. And better service experience is provided for the user.

The invention discloses an investment optimization system based on artificial intelligence investment research, and relates to the technical field of financial investment, and the system comprises the following components: a data collection module which is responsible for collecting data related to an investment portfolio, including historical transaction data, market trend data and company financial data, and carrying out the preprocessing and storage, the risk analysis module is used for analyzing the collected data, evaluating the risk level of the investment portfolio and constructing a risk measurement prediction model, and the module can identify potential risk factors such as market fluctuation and industry risks and give corresponding risk scores and probability distribution, so that the risk level of the investment portfolio is evaluated; according to the invention, rapid processing and accurate analysis of mass financial data are realized through an unsupervised learning algorithm of the data collection module, related information is efficiently captured and integrated from a plurality of data sources, the efficiency and accuracy of investment decision making are greatly improved, investors can better grasp market opportunities, the investment risk is reduced, and the economic benefit is improved. And higher investment return is realized.

The invention discloses an intelligent user service platform based on big data, which comprises a service data analysis management module, a server semantic analysis module and an intelligent service interaction feedback module, the operation method of the platform comprises the following steps: step 1, integrating data, processes, resources, organizations and functions related to business products in different life cycles based on enterprise business services to a unified intelligent user service platform for analysis and management of service data; 2, on the basis of shallow-layer user consultation text semantic analysis, keywords are marked according to semantic similarity and a vector model, and the similarity between the keywords is calculated; step 3, constructing a rule of progressive service of the intelligent user server to the user level; 4, performing question semantic analysis and information retrieval on the questions consulted by the user to form final intelligent service interaction feedback; the problem of invalid service of intelligent customer service under complex conditions is solved, and the user service satisfaction degree and the user intelligent service quality are improved.