652 results about "Computational analysis" patented technology

The invention belongs to the field of network security, and discloses a network security evaluation system and method based on a dynamic attack and defense game model, and the evaluation system comprises four functional modules of attack and defense game construction, risk prediction, dynamic defense optimization and security situation awareness. According to the method, the idea of dynamic attack and defense game is introduced, multi-level and multi-scene attack and defense simulation is carried out according to historical states, strategy data and real-time data, and the optimal attack path and attack strategy are calculated and analyzed through a game equilibrium solution; according to the method, network resources and network security resources are dynamically adjusted by relying on reinforcement learning and deep learning technologies and a defense rule base generated by pre-training, network configuration is optimized according to a real-time evaluation result, and waste of system resources is reduced. By implementing the system and the method provided by the invention, the security of the target network can be dynamically evaluated, the security defense strategy of the network can be adjusted in real time, and unknown attacks such as advanced persistent threat (APT) and zero-day attack can be effectively resisted.

The invention relates to the technical field of the Internet of Things, and discloses a machine room equipment environment monitoring method and system based on the Internet of Things, and the method comprises the steps: constructing an edge calculation hardware system of the Internet of Things to obtain an integrated terminal which integrates a communication unit, an acquisition unit and a control unit; performing multi-channel parallel acquisition and edge calculation analysis on equipment and environment parameters in the machine room to obtain a standard data tuple and an analysis data packet; executing local hierarchical storage and logic control to obtain a control instruction and storage data; executing three-layer network communication interaction on the storage data to obtain a remotely accessible monitoring view; according to the method, intelligent alarm and system self-maintenance are achieved, graded and classified alarm information and a system state report are obtained, the data transmission amount is greatly reduced, meanwhile, the system response delay is reduced, the control decision accuracy is improved, and the misoperation risk is reduced.

The embodiment of the invention discloses a life omics research method and device based on artificial intelligence, and the method comprises the steps: carrying out the preprocessing of a project according to the intelligent interaction between a user and a system, and generating standardized data; and meanwhile, carrying out transfer learning on the large language model to construct a life science large language model. And according to the standardized data, decomposing a research target by adopting a life science big language model in cooperation with an intelligent agent, and generating an analysis plan. And based on the analysis plan, the intelligent agent is scheduled through the coordinator, and a hierarchical task is generated. And calling a multi-omics analysis tool by the intelligent agent to calculate and analyze the grading task, and outputting an analysis result. And based on data features, integrating analysis results through an integrated advanced model, and outputting a final report to complete the research of life omics. According to the embodiment of the invention, full-process automation and natural language interaction are realized, the standardization of data analysis and the repeatability of results are ensured, the research efficiency is remarkably improved, and the technical threshold is reduced.

The invention discloses a nondestructive testing method for infrared thermal imaging spatio-temporal information fusion, which relates to the technical field of nondestructive testing and comprises the following steps: establishing a linear laser heat source scanning infrared thermal imaging nondestructive testing system; collecting a dynamic infrared thermal image sequence; and calculating and analyzing dynamic infrared thermal image sequence data, and carrying out data processing on the acquired dynamic infrared thermal image sequence by using an infrared thermal imaging spatio-temporal information fusion post-processing method to obtain a full-field thermal response image with surface crack defects. According to the method, spatio-temporal information can be fused to obtain data with higher resolution, more comprehensive and accurate full-field thermal response characteristics are obtained while the calculation efficiency is improved, the method has better flexibility and wider applicability, and the purpose of nondestructive detection of metal surface defects is achieved.

The invention provides a house waterproof maintenance system based on an intelligent detection and self-repairing technology, and the system comprises an intelligent sensing layer which is used for collecting multi-dimensional physical parameters of building waterproof key nodes in real time; the edge calculation analysis layer is used for performing fusion analysis and risk prediction on the perception data; the dynamic self-repairing execution layer is used for triggering a multi-stage repairing mechanism according to an analysis result; the cloud management layer is used for realizing visual management and control and strategy optimization of the whole system, and relates to the technical field of building waterproofing, the building state is monitored in real time through a multi-mode sensing network, water leakage risk prediction is realized in combination with an edge calculation algorithm, and collaborative repair of a microcapsule repair agent, a shape memory alloy grid and an electrodialysis module is triggered; the system remarkably improves the timeliness and reliability of waterproof maintenance, reduces the manual intervention cost, and is suitable for intelligent maintenance of residential buildings, industrial buildings and historical protection buildings.

The invention, which relates to the technical field of traffic management, discloses an intelligent detection system for a vehicle parking space in a passenger and goods mail fusion station, and the system comprises a multi-mode sensing module which is configured to collect vehicle data information, the collection mode comprises the steps that vehicle data information is collected through an enhanced geomagnetic array, an adjustable video monitoring set, a lateral laser radar and a piezoelectric sensor; and the edge computing node module is configured to integrate an AI chip, the AI chip comprises a vehicle classification model, an abnormal parking detection algorithm and a data fusion engine, and the collected data is computed and analyzed. The edge computing node is integrated with an AI chip, and data are analyzed and processed through a built-in algorithm; the hybrid communication network transmits data through an optical fiber backbone network and a specific redundant link, self-adaptive visual adjustment and intelligent algorithm optimization are performed, the problem of complex vehicle type detection in a passenger and goods mail fusion station is solved, and the parking space utilization rate and the operation efficiency are remarkably improved.

The invention discloses a traction energy-saving method and system based on dynamic load flow calculation for rail transit, electronic equipment and a readable storage medium, and the traction energy-saving method comprises the steps: planning a multi-vehicle collaborative energy-saving module through an ATO single-vehicle energy-saving + ATS working diagram, a dynamic diagram adjustment module according to passenger flow requirements, a regenerative braking energy feedback module and other modules; multi-dimensional coupling conditions of power supply, vehicles, signals, tracks and the like are dynamically analyzed, dynamic load flow calculation is performed from the perspective of energy flow through a dynamic load flow calculation and analysis module of the traction power supply system, technical means such as ATO energy saving, ATS energy saving and regenerative braking energy recovery device energy saving are dynamically coordinated, unified management and cooperative linkage are performed, and the dynamic load flow calculation and analysis module of the traction power supply system is realized. Energy consumption monitoring and statistical analysis are carried out for different traction energy-saving measures, and long-term energy-saving operation effect tracking and evaluation are carried out; and an energy-saving control strategy is continuously adjusted and optimized according to an analysis result through a prediction model between line energy consumption and operation data variables, so that a better energy-saving effect in a real sense is achieved.

The invention discloses a water conservancy project risk assessment method and system based on artificial intelligence, and relates to the technical field of risk assessment management, and the method comprises the steps: obtaining a feature parameter set; calling an information value quantification function to quantitatively analyze the prediction capability of the water conservancy project risk coefficient to obtain a first value coefficient; if the first value coefficient reaches a preset threshold value, adding the first feature to a candidate feature factor list; and activating the accident cause Bayesian network model to perform cause analysis on the candidate feature factor list to obtain a target cause chain and a target key feature factor list, performing dynamic feature collection on the target water conservancy project to obtain a real-time feature parameter set, and performing normalization calculation analysis to obtain a target risk coefficient of the target water conservancy project. The technical problem of low risk assessment precision caused by lack of systematic analysis of water conservancy project multi-source features in the prior art is solved, and the technical effect of improving the water conservancy project risk assessment precision is achieved.

The invention discloses a meta-model-based technical index construction and management method and system. The method comprises the steps of defining index metadata according to standard specifications, project experience and historical data; according to product design requirements, constructing a structured index template library; quoting an index template library, defining indexes and association relationships between the indexes and a demand model, a SysML model, a geometric model and the like, and forming an index library; calling an index suite, and applying the index set to form a plurality of sets of index parameter solutions; calculating and analyzing the index parameters of different solutions so as to realize preliminary balancing of the solutions; according to the changed index parameters, the associated index parameters are identified, and change prompting is carried out; performing tracking, detection and early warning on the index parameters through calculation and analysis of the index parameters; setting an index verification task according to the product research and development process, and managing the execution condition and result of the verification task. According to the technical scheme provided by the invention, full-life-cycle management of the product indexes can be realized.

The invention belongs to the technical field of BIM (Building Information Modeling), and particularly relates to a curved surface composite truss design and construction integrated method and device based on the BIM technology. The method comprises the following steps: considering four structural schemes for a building facade, generating a corresponding parameterized structural topology and a three-dimensional structural line model, adding a load, calculating, analyzing and optimizing a cross section, and generating four structural calculation models and building scheme models; the building space effects and the structure force transmission efficiency of the four structure schemes are compared, and the optimal one is selected as an implementation scheme; and forming a full-professional BIM model according to the selected implementation scheme. Building datamation is achieved through the BIM technology, digital delivery of design results is achieved, the link of two-dimensional plotting is reduced, steel structure deepening is further conducted through the BIM model in the construction stage, visual deduction is conducted on key procedures such as steel structure machining, assembling and hoisting, and digital construction is achieved.

The invention discloses an intelligent regulation and control method and system for a dust removal system of an iron and steel enterprise, and the method comprises the following steps: collecting real-time data according to a set frequency, including the operation parameters of each dust production point, the opening degree of a valve, and the operation parameters and exhaust condition parameters of a dust remover, dust conveying equipment and a fan, and dividing the data into operation variables and regulation variables; a hybrid neural network model is constructed, the hybrid neural network model comprises an LSTM-GPT-Neo backbone network, a DenseNet branch network and a meta learning feature fusion correction layer, and the LSTM-GPT-Neo backbone network fuses an LSTM architecture and a GPT-Neo architecture; inputting time sequence data to carry out model training and optimization; and inputting the data into the trained hybrid neural network model for calculation and analysis, and outputting the opening degree of the valve and the optimal operation parameters of the fan. Under the condition that the dust removal efficiency and stability are guaranteed, the electricity utilization cost of the steel plant can be remarkably reduced, and the problem of equipment loss caused by excessive dust emission or excessive air volume due to insufficient air volume is avoided.

To adjust a human flow in a display hall, rationally plan a display route based on the preferences of participants in different age groups, and enhance experiences of participants of display.SOLUTION: An intelligent display management system based on a smart display hall includes an interactive system and an analysis system. The interactive system includes a use module and a sense module. The use module correlates a relationship of two people actively or passively based on the pieces of individual information of participants of display. The sense module has an ability of feedback of position information of participants, detection of wearing states of participants and monitoring of an admiring state. The analysis system includes a calculation analysis module; and a route planning module. The calculation analysis module calculates a degree at which each display booth and each display hall are recommended to participants in each age group. The route planning module plans a route in real time based on the above-mentioned recommendation degree and the number of accompanying people.SELECTED DRAWING: Figure 1

The invention discloses an intelligent evaluation system fusing behavior data and a scale, and the system comprises a data collection module which is used for collecting multi-dimensional behavior data; the data processing and feature extraction module is used for cleaning and preprocessing the data and extracting and calculating features; the analysis and evaluation module performs analysis and evaluation based on the behavior characteristics and scale scores; and the result output and explanation module is used for displaying the psychological state evaluation result generated previously to the user and explaining the evaluation result displayed by the user. According to the method, by collecting the multi-dimensional behavior data of the user in the answering process and combining the traditional psychological scale score, the limitation that the traditional psychological scale evaluation method excessively depends on self-reporting and lacks behavior data analysis and integration is overcome, more comprehensive, accurate and objective evaluation of the psychological state of the user is achieved, and powerful support is provided for the field of psychological health.

The invention relates to the technical field of fault prediction and health management, in particular to a primary and secondary fusion complete ring main unit fault diagnosis method and system. Comprising the following steps: acquiring three-phase instantaneous voltage and current signals in real time, and converting the signals into digital transient data; performing time window preprocessing on the digital transient data, and executing wavelet packet decomposition to generate a transient feature vector; calculating and analyzing the transient feature vector through a transient zero-sequence power direction method and a support vector machine model to generate a local diagnosis result; when the local diagnosis result is that cooperative positioning needs to be started, a transient current similarity coefficient and a transient waveform intensity difference coefficient are calculated based on the digital transient data, and a comprehensive positioning result is generated; determining a fault line according to the comprehensive positioning result, and generating a remote control command; and executing a fault isolation operation based on the remote control command, and executing a PHM process. According to the method, the double local transient diagnosis and the cross-terminal cooperative positioning are deeply fused, so that the high-precision determination of the boundary of the fault section is realized.

The invention discloses an intelligent-based abnormal carbon emission data automatic identification early warning system, which belongs to the technical field of intellectualization and comprises a data acquisition preprocessing module, a high-precision space-time analysis module, an intelligent analysis module, an automatic abnormal identification module, a carbon footprint tracing module, a self-adaptive adjustment module and an intelligent emission prediction module. A carbon emission source and time-space distribution characteristics are accurately positioned through spatial positioning and time sequence analysis of the high-precision time-space analysis module, a spatial distribution diagram is more detailed and accurate through the optimized sensor position and an interpolation algorithm, and time sequence analysis is more accurate through timestamp correction and power spectrum density analysis. The method effectively evaluates the periodic intensity of the signal, analyzes a hidden mode and an association rule in the data through the intelligent analysis module integrating the spatial-temporal characteristics and the related information of the data acquisition and preprocessing module, analyzes the spatial-temporal association between variables through the calculation of a clustering center and the association intensity, and facilitates the discovery of a potential abnormal mode.

The invention discloses a spacecraft space environment safety guarantee system and method based on three-step calculation, and the system comprises two subsystems: a space environment data service subsystem and a three-step calculation and analysis subsystem, and the three-step calculation and analysis subsystem calls data and an algorithm model from the space environment data service subsystem. The space environment safety guarantee analysis based on the three-step calculation is executed; the space environment data service subsystem comprises a metadatabase and a comprehensive database; the metadatabase comprises space environment space-based monitoring data, space environment foundation monitoring data and data from a specified space environment mechanism; the comprehensive database comprises a space environment numerical calculation model library and a spacecraft business application rule algorithm model library; the three-step calculation and analysis subsystem comprises a sun-earth space environment analysis and calculation module, a spacecraft orbit ring layer environment analysis and calculation module and a spacecraft task influence risk assessment and calculation module, and three-step calculation is executed through the three modules.

The invention provides a digital wetland ecological environment monitoring system, which comprises an intelligent sensing terminal deployed in a wetland experiment sample area and used for collecting multi-source heterogeneous wetland monitoring data and transmitting the multi-source heterogeneous wetland monitoring data to information transmission equipment; the information transmission equipment is used for receiving, transmitting, summarizing, storing and analyzing the multi-source heterogeneous wetland monitoring data; and the wetland data center is used for acquiring the summarized multi-source heterogeneous wetland monitoring data through information transmission equipment, providing data analysis service on line by utilizing a distributed calculation and analysis technology and a data mining tool on the basis of the multi-source heterogeneous wetland monitoring data, and providing data service for the application service center and the intelligent decision center. According to the invention, multi-source heterogeneous data is integrated, wetland ecological monitoring related management applications and data services are integrated to a unified monitoring platform, and application of the system in ecological evaluation and simulation prediction is realized, so that informatization, digitization and intelligence of wetland ecological monitoring are further realized.

The invention discloses a character recognition method and system based on a large model and an OCR technology, and relates to the technical field of character recognition, and the method comprises the steps: extracting picture information, carrying out the unified preprocessing, generating a text detection box of a character region through a DBNet lightweight text detection model, and obtaining a text position; quickly identifying characters in the textbox by using a lightweight OCR model to obtain text content, and generating an identification information group; carrying out average value calculation on the confidence coefficient of the lightweight OCR model result, and analyzing the overall confidence coefficient; and for the result with low confidence coefficient, inputting the corresponding identification information group into the multi-modal large model, and carrying out secondary identification. According to the method, the text position set and the text character string sequence are combined into the identification information group, so that the effect of structured storage of detection and identification results is achieved, subsequent information retrieval and multi-modal fusion analysis are facilitated, and the effect of optimizing the subsequent processing efficiency and precision is achieved through the combination of the confidence coefficient screening step.

The invention discloses a tire finite element modeling and multidirectional rigidity optimization method and system based on characteristic lines. The method comprises the following steps: extracting tire section characteristic lines from a three-dimensional digital model; introducing the tire section characteristic line into a finite element analysis environment, generating a three-dimensional tire geometric model by rotationally scanning the characteristic line, and performing grid division on the model; setting tire material attributes, performing zoning setting on the model according to a tire crown, a tire shoulder and a tire side wall, and setting tire thickness based on zoning; applying a constraint boundary condition at the center of the tire, and establishing a contact form of the tread and the ground; a progressive inflation pressure load is applied, the deformation state of the inflated tire is calculated, and longitudinal rigidity, radial rigidity and lateral rigidity calculation and analysis steps are set; the tire elasticity modulus and the cord fabric thickness are used as design variables, and an optimization algorithm is adopted to solve a multi-objective optimization function. The method has the advantages of being simple in modeling method and high in practical operability, the tire modeling threshold can be lowered, and the fund and time cost of refined modeling is reduced.

The invention discloses a water conservancy data acquisition device, and relates to the technical field of Internet of Things, and the device comprises the following steps: dividing a target water area into a plurality of monitoring water areas; performing characteristic factor analysis on each monitored water area to obtain a characteristic factor analysis result; adjusting the installation number and positions of the sensors in the monitored water area according to the characteristic factor analysis result, and obtaining hydrological data monitored in real time; performing edge calculation analysis on the hydrological data monitored in real time to obtain an edge analysis result; performing data synchronization on the edge analysis result and uploading the edge analysis result to a cloud platform to obtain cloud data; performing intelligent analysis on the cloud data to obtain a water area dynamic report; performing risk early warning according to the water area dynamic report; the acquisition device collects and analyzes hydrological data of different water areas by combining real-time data acquisition of a sensor and an edge calculation and analysis method. According to the method, loss and errors of hydrological data are reduced, and consistency, high efficiency, accuracy and timeliness of the hydrological data are enhanced.

The invention relates to a method for predicting fracture pressure of a stratified shale extended reach well based on a machine learning model. The method comprises the following steps: S1, acquiring well drilling data, collecting an underground rock core, carrying out an anisotropic shale tensile mechanical experiment along a bedding direction, and constructing a shale fracture criterion according to an experiment result; s2, constructing a stratified shale extended reach well fracture pressure model, and correcting and integrating the calculated fracture pressure value in combination with field ground fracture experimental data; s3, combining well body structure conditions of the highly-deviated well, using a mechanical model to calculate fracture pressure, and using field small pressure data verification to form a fracture pressure calculation and analysis database; s4, training the prediction model based on a machine learning method, determining a WT-LSTM model structure, setting a hidden layer and performing training; and S5, optimizing the rupture pressure model based on machine learning through hyper-parameter adjustment, feature selection and importance evaluation means. According to the method, the prediction accuracy of the fracture pressure of the highly-deviated well is improved by integrating multiple factors, data support is provided for on-site complex stratified shale fracturing engineering design, reasonable parameter selection of extended reach well construction is facilitated, adaptability and safety are improved, and data support is provided for stratified shale oil and gas resource development.

The invention discloses a refining furnace smelting intelligent management method and system based on edge calculation, relates to the technical field of data processing, and comprises the steps of analyzing an association relationship between smelting information in each smelting stage, and providing a reliable basis for establishment and early warning of a subsequent abnormal event standard state. The multiple components of each abnormal event are determined through the incidence relation between the smelting information, abnormity evaluation is conducted on all dimensions, and the smelting early warning reliability and accuracy of the refining furnace are improved. The early warning period of edge calculation and analysis of each smelting stage is set according to the fluctuation condition of the smelting information, and an adaptive early warning period is set according to each smelting stage in combination with the real-time data processing and analysis capability of edge calculation, so that the real-time performance and timeliness of early warning are ensured. The possible abnormal events are analyzed through the state transition probability between the smelting real-time state and the standard state of the abnormal events, management optimization of smelting of the refining furnace is achieved, and efficient and safe operation of the smelting process of the refining furnace is guaranteed.

The invention discloses a high-formwork optimization design method and system based on BIM and finite element analysis, and the method comprises the steps: S100, building a three-dimensional BIM model of a main body structure, and creating an intelligent parameterization frame body family which is mapped with a main body structure family and has a self-verification function; s200, importing a parameterized family and linking the main body model, generating a plurality of groups of frame body arrangement schemes through spatial topology analysis, and performing a three-dimensional collision test after optimization; s300, setting dynamic boundary constraints and construction loads in stages, and generating a geometric and mechanical integrated data packet; s400, data packet parameters are automatically mapped to finite element software through a plug-in, models are built in stages, multi-working-condition analysis is carried out, if the parameters exceed the limit, frame body parameters are modified, iterative optimization is carried out until the parameters meet the standard, and a result is synchronized to a three-dimensional BIM model; and S500, a construction drawing is automatically generated, and visual disclosure and high formwork monitoring point selection are carried out. According to the method, design, computational analysis and construction application data linkage and closed-loop management from design to construction to monitoring are achieved, and the high formwork design efficiency and safety are improved.

The invention discloses a robot mechanical arm joint motion track planning and motion control method. The method comprises the steps that S1, high-precision vibration sensors are installed on a pipe joint and an end effector of a mechanical arm and calibrated; s2, starting a vibration sensor, collecting vibration data of each part in real time, and transmitting the data to a control system; s3, the control system carries out real-time calculation and analysis on the vibration data, and vibration abnormity of the mechanical arm in the operation process is recognized; s4, the mechanical arm is adjusted in real time according to the analysis result, and the stability and precision of the mechanical arm are guaranteed; and S5, storing related data of machine operation and adjustment, thereby facilitating later learning use. Through the technical means of the high-precision vibration sensor, real-time data acquisition and analysis, real-time adjustment, data storage and the like, the vibration condition of the mechanical arm can be monitored in real time, and the movement precision and stability of the robot mechanical arm are remarkably improved.

A pressurized water reactor oxidation corrosion product cross-scale nuclear-thermal-material coupling simulation method comprises the following steps: in the first stage, obtaining a supercooled boiling position through mutual loop iteration simulation of a neutronics model and a thermal hydraulic model; and in the second stage, multi-physics field coupling simulation is carried out through an oxidation corrosion product (CRUD) model, a neutronics model and a thermal hydraulic model, and high-resolution simulation under the pressurized water reactor nuclear-thermal-material coupling condition is obtained. According to the method, a scene in which the thickness range of the oxidation corrosion product is 20-200 microns is considered, multi-physical fields such as pressurized water reactor neutron physics, flow heat transfer and oxidation corrosion product deposition are calculated and analyzed, and the complex physical process can be captured more accurately.

The invention discloses a spatio-temporal data visualization index management and application method, and belongs to the field of spatio-temporal data statistical analysis processing. Analyzing a time-space visualization service scene, and determining a statistical calculation rule of the time-space index data; a statistical calculation rule of spatio-temporal index data is configured through a visual interface, structured configuration is generated and stored in a standardized configuration table, an ETL process is automatically generated after the system analyzes the configuration to realize data statistics and circulation, and automatic calculation and timing calculation are supported; the method comprises the following steps: designing a hybrid storage architecture of a standardized index data statistical result, and adopting a relational database and data warehouse dual-mode storage strategy: storing original data and statistical results with small data volume by adopting a relational database; for mass data, the mass data are synchronized to a data warehouse through an ETL process, distributed calculation analysis is executed on a warehouse layer based on index configuration, and an analysis result is persistently stored in a column storage format; transparent access to a heterogeneous storage bottom layer is achieved by constructing a unified access interface layer.

The invention discloses a power distribution network situation deduction method and device based on multi-source data fusion. According to the method, a main and distribution integrated calculation model is established, and a model basis for calculation and analysis is provided for situation deduction; according to the method, data pre-estimation is carried out on equipment which does not acquire real-time measurement and a non-automatic switch state in allusion to the weak condition of power distribution network measurement, and identification and correction are carried out on invariant data based on a pre-estimated value and a real-time measurement value of the equipment, so that multi-source data fusion is realized, and an accurate and complete data basis is provided for situation deduction. According to the invention, based on multi-source data fusion and integrated modeling, panoramic graph model topology active association and power distribution network state real-time sensing are realized, and power flow situation deduction in different application scenes is supported, so that safe, stable and efficient operation of an active power distribution network is effectively supported.

The invention discloses a soft rock TBM jamming risk intelligent prediction method based on numerical mechanism guidance, and the method comprises the following steps: S01, building an extrusion soft rock stratum TBM dynamic tunneling whole process refined numerical simulation model which comprises a TBM cutterhead, a front, middle and tail step shield, soft rock, a segmental lining and a backfill material behind a wall, and simulating an evolution process; s02, systematically calculating and analyzing surrounding rock geological parameters, TBM tunneling parameters, TBM construction parameters and TBM construction parameters, and constructing a machine blocking index numerical value sample library; s03, predicting the large deformation of the soft rock and the extrusion load of the shield, fusing TBM rock-machine interaction multi-source data in actual engineering, and establishing a soft rock TBM jamming risk intelligent prediction model; and S04, evaluating the TBM jamming risk, and verifying the effectiveness of the prevention and control measures. According to the technical scheme, the whole process of dynamic interaction between the TBM and the soft rock can be comprehensively considered; the TBM jamming disaster occurrence mechanism is explained, and the generalization ability of the machine learning method in practical application is improved.

The invention relates to the technical field of casting image data processing, in particular to a casting appearance quality detection method based on machine vision, and the method comprises the steps: determining analysis pixel points in a casting X-ray grayscale image; determining the probability that the analysis pixel point belongs to the pore edge in the color domain according to the difference between the gray value of the analysis pixel point and the gray average value of the thick area or the thin area where the analysis pixel point is located and the gray variance of eight neighborhood pixel points of the analysis pixel point; a plurality of other analysis pixel points are obtained in the texture direction perpendicular to the gradient direction of the analysis pixel points to construct a reference domain of the analysis pixel points, and the probability that the analysis pixel points belong to the pore edge in the spatial domain is calculated; according to the probability that the pixel points belong to the air hole edge in the color domain and the probability that the pixel points belong to the air hole edge in the space domain, the seed points of the watershed algorithm are determined, so that the casting appearance quality detection result is obtained, and the casting quality evaluation accuracy is effectively improved.

Disclosed are systems and methods that provide a decision-intelligence (DI)-based, computerized framework for automatically and dynamically determining a quantity and positioning of APs within a location, for which an optimized WiFi network can be realized. The disclosed framework can operate by determining a floor plan / layout of a location using tracked and analyzed channel metrics from the various WiFi devices in the location. Based upon the computational analysis of such metrics, the framework can identify the ideal spots for signal coverage, detect weak / dead spots for signal coverage, close the coverage hole gaps in the house, and the like. Thus, the network topology of a WiFi network, inclusive of the number of nodes in the topology, as well as the quantity of nodes, can be determined, configured and applied to a location, which can control how a location's network operates.