48 results about "Decision support tools" patented technology

The invention discloses a shale oil reservoir geology-engineering double-dessert compressibility comprehensive evaluation method, and relates to the technical field of petroleum and natural gas yield increase transformation and geotechnical engineering, in particular to a shale oil reservoir geology-engineering double-dessert compressibility comprehensive evaluation method, which comprises the following steps of performing normalization processing on a logging basic parameter standard deviation; geological dessert parameters are established by calculating the weight of each factor; influence factors influencing the longitudinal expansion capacity of the hydraulic fracture of the target reservoir are obtained; constructing a geological-engineering double-dessert compressibility comprehensive evaluation model of three types of lithofacies'reservoir performance-transformation potential 'synergistic mechanisms; and establishing a geological-engineering double-dessert compressibility kernel density estimation map, and dividing the reservoir compressibility on the premise of adaptive bandwidth. According to the method, the operability and prediction precision of an evaluation result are remarkably improved, and an innovative decision support tool is provided for horizon optimization and scheme design of shale oil reservoir fracturing transformation.

The invention discloses a public facility reachability evaluation method and system based on geographic multiple agents, and belongs to the field of urban calculation and geographic information. According to the method, a multi-agent system comprising a user agent and a facility agent is firstly constructed, and then a dynamic utility function combined with an evolutionary game theory is introduced to simulate the dynamic decision and congestion avoidance behavior of a user; and user strategies are balanced through multiple rounds of iterative evolution, so that a macroscopic reachability pattern emerging from a microcosmic game is obtained. According to the method, starting from the microscopic individual level, by simulating the dynamic game process of a large number of agents, the defects of a static calculation model are overcome, and dynamic evaluation and predictive simulation of reachability of public facilities are achieved. Compared with the prior art, the evaluation result is more accurate, dynamic feedback of the real world can be reflected, and a scientific decision support tool is provided for urban planning.

The invention discloses a corn crossbreeding intelligent matching system and method based on artificial intelligence, and the method comprises the steps: collecting molecular marker genotype data and phenotype data of candidate parents, calculating the genetic distance between the parents, and constructing a genetic distance matrix; analyzing the phenotypic complementarity degree of the parent pair, and calculating a phenotypic complementarity index; constructing a heterosis prediction model based on genetic distance and phenotype complementarity, and predicting the yield heterosis value of the candidate hybrid combination; evaluating the environmental adaptability and resistance comprehensive score of the candidate combination; and adopting a Pareto multi-objective optimization strategy to screen an optimal matching scheme. According to the method, molecular marker data and phenotype data are integrated, a heterosis prediction model considering a genetic distance nonlinear effect is constructed, collaborative optimization of multiple breeding targets such as yield, resistance and environmental adaptability is achieved, the prediction accuracy is improved by about 20% compared with that of a traditional method, and the method is suitable for large-scale popularization and application. And an intelligent and precise decision support tool is provided for corn crossbreeding.

Decision support tool for real estate selection having at least one computer system and user interface. A content database of real estate properties includes spatial, temporal, material, risk, and financial variables for a set of at least one real estate property from the real estate properties, wherein the at least one real estate property can include a set of at least one real estate property with at least one second real estate property. At least one software program is disposed on at least one computer system designed to calculate user vectors wherein at least one machine learning program is designed to build the set of at least one real estate property from the real estate properties. The user interface is designed to receive inputs and present outputs wherein users may create user sets of at least one selected real estate property from the real estate properties.

The invention provides an intelligent cargo warehouse management system and management method. The intelligent cargo warehouse management system comprises a data acquisition module, a cargo pick-and-place module, a data transmission and storage module and an intelligent control module. The data acquisition module is used for reading cargo information; the goods taking and placing module is used for taking and placing goods on the goods shelf; and the intelligent control module is used for constructing a warehouse three-dimensional virtual scene, and carrying out optimal path goods taking on the goods in combination with the goods taking and placing module. High automation of the goods warehousing and ex-warehouse process is achieved, and the requirement for manual intervention is reduced. The intelligent control module is deployed in the local server, and the goods storage and taking operation can be automatically executed only by inputting a goods taking order number or issuing a goods storage command, so that the operation process is simplified, and the working efficiency is improved. The system constructs a three-dimensional virtual scene by using a panoramic jigsaw algorithm, and displays the inventory distribution condition in combination with a manifold visualization technology, thereby providing a visual decision support tool for managers, and enhancing the visual management level of the storage state.

The invention provides an urban green infrastructure comprehensive benefit applicability evaluation method based on subjective and objective weights. The urban green infrastructure comprehensive benefit applicability evaluation method comprises the steps of establishing a basic evaluation system, screening indexes, calculating index weights, calculating quantitative indexes, calculating qualitative indexes, performing grading evaluation, performing standardized score assignment and performing comprehensive evaluation. The basic evaluation system is of a three-layer structure and covers four criteria of runoff regulation and storage benefits, environmental benefits, economic benefits and social benefits and 19 indexes; a subjective weight is determined through an analytic hierarchy process, an objective weight is determined through an entropy weight method, and a comprehensive weight is obtained in combination with a D-S evidence theory fusion method; quantitative indexes are calculated through methods such as hydrological simulation, and qualitative indexes are rated by public; the indexes are unified into dimensionless scores through standardized score assignment, and finally an evaluation result is obtained through weighted summation. According to the method, the applicability quantitative evaluation of matching of the typical green infrastructure and the site condition construction target is realized, and a scientific and quantitative decision support tool is provided for sponge city planning.

The invention discloses a policy information recommendation method, which solves the problem of low matching degree between policy recommendation and enterprise requirements in the prior art by combining the information extraction capability of a closed source large language model and the semantic understanding capability of an open source large language model, and achieves the technical effects of improving the policy recommendation accuracy and the user experience. Complex relations between enterprises and policies can be deeply understood and matched, the correlation and practicability of policy recommendation are improved, and an efficient and intelligent decision support tool is provided for science and technology enterprises and policy formulators.

The invention discloses an energy-saving city design-oriented building performance proxy model construction and application method, which comprises the following steps of: establishing a parameterized city block model, and defining city form design variables and building performance evaluation indexes; based on the parameterized city block model, generating a training data set comprising a plurality of groups of city form design variables and building performance evaluation indexes corresponding to the city form design variables through building performance simulation software; constructing and training a deep neural network model by using the training data set, so that the deep neural network model learns a nonlinear mapping relationship between urban form design variables and building performance evaluation indexes to obtain a building performance proxy model; and applying the trained building performance agent model to predict a corresponding building performance evaluation index according to the input urban form design variable. According to the method, real-time prediction of the building performance is realized through the constructed agent model, and an efficient and reliable decision support tool is provided for early scheme evaluation and optimization of energy-saving city design.

The invention provides a configuration optimization system and method for a water and soil conservation type protection forest, and relates to the technical field of protection forest configuration, and the system comprises an information collection module which is used for obtaining multi-source data of a target area; the information matching module is used for screening a candidate tree species set; the grid generation module is used for dividing a region into a plurality of evaluation unit grids with geographic attributes; the configuration strategy generation module is used for generating an initial configuration scheme; the strategy optimization module is used for constructing a water and soil conservation benefit evaluation model and generating a recommendation configuration scheme with optimal comprehensive benefits; and the man-machine interaction module is used for finely adjusting and confirming the recommended configuration scheme. According to the invention, through multi-module cooperation and intelligent analysis, the improvement of protection forest configuration from extensive experience decision making to scientific and accurate planning is realized, the scientificity, high efficiency and sustainability of protection forest construction are significantly improved, and a powerful decision support tool is provided for the synergistic interaction of water and soil loss treatment and ecological system service functions.

The invention discloses a forearm radial side branch penetrating flap operation scheme generation and prognosis prediction method based on a generative model and a Bayesian model, and belongs to the field of computer-aided surgery. According to the method, three types of medical data of the structure, the function and the form of the forearm of a patient are acquired and processed, a plurality of personalized flap operation alternative schemes and rationality scores thereof are generated by using a conditional generative adversarial network, and then risk quantitative prediction with a confidence interval is performed on each scheme through a Bayesian neural network. And finally synthesizing an intelligent decision report. According to the invention, intelligent generation and quantitative evaluation of the skin flap operation scheme are realized, and a practical decision support tool is provided for core surgical preoperative planning.

The application discloses a railway construction management multi-objective balanced optimization method based on an improved MOPSO algorithm, which comprises the following steps: 1) under the premise of meeting the basic constraint conditions of a railway construction project, four objective function optimization models are constructed, and each objective function optimization model corresponds to an optimization target; 2) according to the four objective function optimization models constructed in the step 1), a multi-objective balanced optimization model is constructed; 3) the multi-objective balanced optimization model constructed in the step 2) is iteratively solved by using an improved multi-objective particle swarm optimization MOPSO algorithm, and an optimal solution set of the project under the balance of four aspects of a construction period, resources, cost and safety is obtained. The method can effectively consider the four optimization targets of the construction period, resources, cost and safety of the railway construction project, can significantly improve the convergence speed, diversity maintenance capability and constraint processing flexibility of the MOPSO algorithm, and provides an efficient, reliable multi-objective comprehensive decision support tool for railway construction management.

This application relates to the field of artificial intelligence knowledge graph technology, and discloses a customs emergency decision-making method and system based on a multi-agent large language model. The method includes: constructing a knowledge graph from unstructured customs emergency procedure documents through a multi-agent collaborative framework; the multi-agent collaborative framework includes at least a procedure parsing agent, a key point filtering agent, an emergency element extraction agent, and a logic construction agent; based on the constructed knowledge graph, a graph navigation agent driven by a large language model provides support for users' customs emergency decision-making problems and provides customs emergency decision-making answers. This application can achieve high-fidelity automated construction of customs emergency knowledge graphs, ensuring the accuracy and completeness of knowledge; it can transform static knowledge graphs into interactive dynamic decision support tools, truly connecting the entire chain from unstructured procedure documents to intelligent decision support.

The application relates to the technical field of data prediction, and discloses a marine foundation bearing capacity prediction method and system based on scour pit fractal reconstruction and deep learning, a terminal and a storage medium.The method comprises the following steps: acquiring measured three-dimensional point cloud data, performing interpolation and reconstruction, and generating a three-dimensional scour pit digital geometric model; based on the three-dimensional scour pit digital geometric model, the foundation limit bearing capacity under different scour pit morphologies is calculated, and a scour pit morphology quantitative descriptor is extracted to form a data pair sample library; the deep learning model is trained by taking the data pair sample library as a training set, and a trained deep learning prediction model is obtained; the newly detected scour pit morphology data is input into the deep learning prediction model after being reconstructed and quantitatively described, and the foundation prediction bearing capacity under the current morphology is obtained. The application realizes end-to-end rapid prediction from detection data to bearing capacity evaluation, and provides an efficient and accurate decision support tool for the safe operation and maintenance of marine structures.

The invention relates to the technical field of industrial automation and intelligent manufacturing, in particular to an equipment scheduling management method for coal preparation plant production, which comprises an information sharing platform, a dynamic scheduling algorithm, an adaptive scheduling system and a decision support tool, and monitoring equipment operation data in real time, and transmitting the data to the cloud server for centralized processing and analysis. The dynamic scheduling algorithm utilizes a machine learning model to carry out real-time analysis on equipment efficiency and production requirements, and an optimized scheduling scheme is automatically generated. The self-adaptive scheduling system can quickly evaluate other available equipment and perform resource reconfiguration when the equipment fails or production conditions change, so that the production continuity is ensured. The decision support tool generates maintenance demand prediction based on historical data and real-time information, and helps dispatchers to arrange a maintenance plan in advance.

The invention relates to a crop phenotype information generation system for unmanned aerial vehicle multispectral remote sensing images. The method comprises the following steps: acquiring remote sensing images by using an unmanned aerial vehicle with a multispectral sensor and a visible light sensor; constructing and using a user-defined vegetation index calculation module, and extracting characteristic variables with biological significance from the data; performing preliminary screening on all vegetation indexes; carrying out model training, and carrying out system evaluation on a training result by adopting multiple performance evaluation indexes; loading the trained model to carry out field prediction; predicting and generating a two-dimensional prediction image consistent with the original image in size; the topdressing amount is calculated, and a fertilization prescription map suitable for guiding agricultural machinery operation is generated in combination with the unmanned aerial vehicle remote sensing image and the grid width input by the user. According to the method, full-chain visualization from remote sensing data preprocessing to prediction result output, crop parameter inversion estimation and farmland management prescription map automatic generation functions are realized, and an intuitive decision support tool is provided for precision agricultural practice.

The invention discloses a big data processing analysis system, which comprises a multi-source sensing module, a dynamic analysis module, a cloud decision module and a visual output module, and is characterized in that the multi-source sensing module comprises a water temperature probe, a pH probe, a dissolved oxygen sensor, a conductivity sensor, a turbidity meter, a flow meter and a water level gauge; the multi-source sensing module is used for being deployed in a target water area and a coastal area; by integrating the multi-source sensor, the dynamic analysis model, the cloud intelligent decision and the GIS visual platform, accurate monitoring and efficient treatment of water quality pollution are realized, the accuracy of pollution source positioning can be greatly improved by utilizing the LSTM prediction model, the limitation of a traditional time difference method is overcome, and meanwhile, the method has the advantages of being simple in structure and convenient to operate. Different pollution levels are generated by combining rainfall, soil and other multi-dimensional data, treatment measures are automatically matched, a reliable decision support tool is finally provided for water environment treatment, and the intelligence and refinement level of water environment management is effectively improved.

The invention particularly relates to a lung cancer death education knowledge map system and method based on a triple semantic network, and the system comprises a patient terminal, a family member terminal, a medical care terminal and a server, and the patient terminal inputs a patient demand for a patient; the family member end is used for inputting basic information, own roles and family member demands of patients by family members; medical staff can inquire education records and feedback suggestions of patients through a patient data inquiry function of the medical care terminal, inquire related knowledge graph contents through a knowledge graph management function, and formulate an education plan through a decision support tool; an interaction module in the server is used for interaction and calling a reasoning module for reasoning, the reasoning module screens out a feedback result matched with the resistance based on the user demand and / or the recognized resistance from the knowledge graph with the defined triple semantics, and the feedback result is fed back to the patient end, the family member end or the medical care end through the interaction module. According to the scheme, comprehensive, accurate and dynamic knowledge support and psychological guidance are provided for patients and family members.

The invention belongs to the field of heat exchanger performance evaluation, and particularly relates to a heat exchanger comprehensive performance evaluation method, a use method and a system. The heat exchanger comprehensive performance evaluation method comprises the following steps: S1, establishing a comprehensive performance evaluation diagram: establishing a logarithmic coordinate system to form the comprehensive performance evaluation diagram; s2, constructing constraint performance lines: in the comprehensive performance evaluation diagram, constructing at least one constraint performance line based on a preset evaluation constraint condition, the constraint performance line being defined by a performance relation model; and S3, performance evaluation: quantitatively evaluating the comprehensive performance of the enhanced heat exchange structure under the selected evaluation constraint condition. According to the heat exchanger comprehensive performance evaluation method, the use method and the system, the limitation of a traditional evaluation system is overcome, and a reliable and efficient decision support tool is provided for design and model selection of an efficient, compact and lightweight heat exchanger.

The present application belongs to the field of heat exchanger performance evaluation, and particularly relates to a heat exchanger comprehensive performance evaluation method, a use method and a system. The heat exchanger comprehensive performance evaluation method comprises the following steps: S1, establishing a comprehensive performance evaluation graph: establishing a logarithmic coordinate system to form a comprehensive performance evaluation graph; S2, constructing a constraint performance line: in the comprehensive performance evaluation graph, at least one constraint performance line is constructed based on a preset evaluation constraint condition, and the constraint performance line is defined by a performance relationship model; and S3, performance evaluation: quantitatively evaluating the comprehensive performance of the enhanced heat exchange structure under the selected evaluation constraint condition. The present application provides a heat exchanger comprehensive performance evaluation method, a use method and a system, overcomes the limitations of the traditional evaluation system, and provides a reliable and efficient decision support tool for the design and selection of efficient, compact and lightweight heat exchangers.

This invention discloses a method for constructing an evaluation model for ecological carrying capacity and industrial layout suitability. By acquiring multi-source ecological environment and socio-economic data of the evaluation area, and constructing three subsystem indicator sets (stress, state, and response) based on the PSR framework, the comprehensive ecological carrying capacity score (ECC) of each evaluation unit is obtained. Industrial layout suitability indicators are extracted from four dimensions: natural suitability, resource support, environmental constraints, and economic accessibility. A combined weighting method using the analytic hierarchy process (AHP) and entropy weighting is employed to calculate the comprehensive industrial layout suitability score (ILS). Finally, the ECC and ILS are quantitatively coupled through a coupling coordination degree model, outputting a coupling coordination degree index D and hierarchical industrial layout decision recommendations. This invention achieves an integrated quantitative evaluation of ecological carrying capacity and industrial layout suitability, providing a scientific decision support tool for regional sustainable development planning.

A decision support tool is provided for discharging a patient by predicting the probability of a patient's readmission based on information prior to discharge. The information used to make the prediction may include labs, vitals, diagnoses, and medications from prior encounters and from the current encounter. At least some of this information may be used to compute a readmission prediction. One or more recurrent neural networks may be utilized to generate the prediction, and one or more sequences may be generated from the patient information to feed into the one or more recurrent neural networks. Based on the prediction, one or more actions may be initiated to reduce the probability of readmission.

The invention discloses an inference knowledge graph-based offshore ecological environment health assessment method, which comprises the following steps of: acquiring water body parameters in real time, acquiring large-range monitoring information through satellite remote sensing data, and accessing literature data to construct a background knowledge base; defining a core entity type, establishing a relationship type between entities, storing the entities and the relationships through a graph database, combining the graph database with a reasoning model, and performing node classification, link prediction and graph representation learning on the entities and the relationships in the graph database; updating the state of the knowledge graph according to the detection data received in real time; and a health threshold is set in combination with historical data and regional features, health state registration and change trend analysis are generated, and an evaluation result and a reasoning process are visually displayed. The knowledge graph and ecological environment health assessment are combined, an intelligent decision support tool is provided for offshore ecological environment management, and the modeling and reasoning capabilities of the dynamic evolution process of the offshore ecological environment are improved.

Provided herein are systems and methods for dynamically providing messages based on indications of states to users at risk of migraines. A server can maintain, on a database, an identification of a set of activities for users at risk of migraines, with each activity having a set of messages to be presented in accordance with a rule. The server can receive, via a user interface, an indication identifying a state of the user associated with the migraine. The server can select, based on the state of the user identified in the response, an activity to provide to the user for the session. The server can identify, in accordance with the rule for the activity, a message from the set of messages. The server can cause the message identifying the activity to be presented via the user interface.

The application provides a supply chain big data management method and system based on artificial intelligence, which comprises the following steps: obtaining identification information of a material, source information of the material and data collection performance information of the material; based on an expected state of the material, an update reference standard of the data collection performance information is established; the data collection performance information of the material is compared with the update reference standard in real time to identify a performance mode deviating from the update reference standard; in response to the performance mode deviating from the update reference standard, background information related to the performance mode is obtained; based on the background information, a root cause leading to the performance mode is inferred; and according to the root cause, a data cleaning strategy in a data processing flow and a running parameter of a decision support tool are adjusted. The application effectively solves the problems of data processing lag and inaccurate decision-making in traditional supply chain management, and improves the response speed and management efficiency of the supply chain.

The present application relates to hemodialysis prescription optimization technical field, especially in a kind of method and device for determining safe and effective prescription interval of hemodialysis.The method is in two-dimensional parameter space with ultrafiltration volume and dialysate sodium concentration as coordinate axis, using double-chamber sodium dynamics model (diffusion equilibrium concentration C_eq=[Na]d / σ (σ=0.97)) to calculate the sodium removal of each parameter combination and serum sodium after dialysis, superimpose sodium removal target line, ultrafiltration rate safety line and serum sodium safety area three constraint boundaries, the area that meets all constraints simultaneously is determined as safe and effective prescription interval.The safe and effective prescription interval is obtained by mathematical model calculation, not determined directly by preset empirical threshold.The present application first proposes the concept of safe and effective prescription interval, upgrades dialysis prescription from single-point empirical selection to interval optimization selection, and the constraint boundary can be dynamically adjusted according to individualized parameters of patients, to provide intuitive multi-constraint prescription decision support tool for clinicians.

The invention provides an infant capillary bronchitis moderate and severe risk prediction model and a construction method and application thereof, and belongs to the technical field of medical prediction models. According to the invention, quantitative evaluation of the severity of the infant capillary bronchitis can be realized, and an objective decision support tool is provided for clinic. The method has the direct effects that the early recognition capability of the child patients with moderate and severe risks is remarkably improved, and clinical doctors are helped to carry out accurate risk stratification. Therefore, medical resources can be distributed more reasonably, high-risk children patients can be monitored and treated more timely and intensively, the occurrence rate of serious illness is expected to be reduced, prognosis of the children patients is improved, unnecessary excessive medical treatment can be avoided for low-risk children patients, and burdens of families and medical systems are relieved. A complex mathematical model is converted into a simple clinical scoring system, the practicability and operability of the technology in a basic medical scene are further improved, and the method has important clinical application value and social significance.

The invention discloses a vision screening intelligent question and answer method based on mixed retrieval and a related device, and relates to the technical field of vision intelligent screening, the method comprises the following steps: preprocessing a vision screening related document, constructing a BM25 keyword index and FAISS vector index two-way structure, and forming a vision screening knowledge base; after user questions are received, parallel retrieval and weighted fusion are carried out through double-path indexes, and Top-K related documents are obtained; constructing Prompt based on the retrieval result, the user question and the dialogue history, calling a large language model to generate and output answers in a streaming mode, and marking the document source of each key conclusion; and finally, automatically generating an intelligent questioning suggestion and maintaining a dialogue history. According to the scheme, the problems of insufficient retrieval accuracy, unknown answer sources and poor interaction experience in the prior art are effectively solved, the retrieval accuracy and the answer credibility are remarkably improved, the response time is shortened, the inquiry interaction continuity is optimized, and an efficient and reliable vision screening knowledge query and decision support tool is provided for medical staff.

The invention provides a supply chain big data management method and system based on artificial intelligence. The method comprises the steps of obtaining identification information of materials, source information of the materials and data acquisition performance information of the materials; based on the expected state of the material, establishing an updating reference standard of the data acquisition performance information; comparing the data acquisition performance information of the material with the updated reference standard in real time so as to identify a performance mode deviating from the updated reference standard; in response to the performance pattern deviating from the update reference standard, acquiring context information related to the performance pattern; inferring a root cause causing the performance pattern based on the context information; and according to the root cause, adjusting a data cleaning strategy in the data processing flow and operation parameters of the decision support tool. The problems of data processing lag and inaccurate decision in traditional supply chain management are effectively solved, and the response speed and management efficiency of the supply chain are improved.

The invention belongs to the technical field of medical information, and particularly relates to an antibacterial spectrum radar map visual evaluation system and a presentation method using the same, and the system comprises a structured antibacterial drug sensitivity database, a multi-dimensional radar map generation engine, and a weighted calculation and interactive display module. The structured antibacterial drug sensitivity database comprises a basic numerical database and a graph and weighted numerical database; the multi-dimensional radar map generation engine maps the sensitivity rates of drugs to six types of pathogens into graphic coordinates; the weighted calculation and interactive display module is used for calculating the overall sensitivity rate of antibacterial drugs to target pathogens based on infection parts and characteristics, the information reading and comprehensive decision-making efficiency is remarkably improved, the quantitative evaluation display decision-making time is shortened by 50% or above, complementary visual evaluation of a drug combination scheme is achieved, and the method is suitable for large-scale popularization and application. Reasonable use of antibacterial drugs is promoted, and extension of professional decision support tools from a fixed workstation to mobility and scenario is realized.

Methods, systems, and computer-readable media are provided for analyzing amounts of time spent by clinicians caring for patients. Clinician locations, patient locations, patient data, and clinician electronic health record activity may be used to facilitate generation of one or more predictive models. Such predictive models will provide, among other things, a decision support tool for scheduling patient-clinician appointments to minimize, at least partially, patient wait times.