320 results about "Calculation algorithm" patented technology

The invention discloses a three-dimensional model lightweight reconstruction and rendering method based on multi-strategy collaboration, and the method comprises the steps: 1, extracting geometric information, appearance information and semantic attribute information of a three-dimensional model, separating the geometric information from the appearance information and the semantic attribute information, and storing the semantic attribute information to a three-dimensional model database; 2, instantiating components with the same geometric structure in the three-dimensional model, realizing material sharing through a material reference mechanism, and reducing rendering overhead on the premise of not changing the structure of the model; step 3, carrying out lightweight processing on the exported geometric and appearance information to obtain reconstructed lightweight models with different precision grades; and 4, dynamically adjusting the geometric complexity of the lightweight model through the sight distance and the frame rate by using a hierarchical calculation algorithm for rendering, and meanwhile, obtaining component semantic attribute information and synthesizing the semantic attribute information by calling a three-dimensional model database interface to realize visual display of the reconstruction model.

The invention discloses a privacy protection effect evaluation method and system, and the method comprises the steps: carrying out the hierarchical analysis of a privacy protection effect evaluation index system, defining the definition and calculation boundaries of four first-level dimensions, i.e., data features, compliance, availability and safety, and subordinate second-level indexes, carrying out the adaptation of a calculation algorithm for different types of indexes, and carrying out the weighted integration of the second-level indexes through employing an analytic hierarchy process, thereby achieving the evaluation of the privacy protection effect. Multi-dimensional quantitative evaluation is realized; an index association rule base and a matrix are constructed through static analysis and dynamic mining, and linkage analysis is achieved; determining an index fluctuation reference according to scene characteristics and historical data, converting user demands into a variation amplitude of a fluctuation reference unit, and realizing index dynamic linkage updating based on an incidence matrix; and finally, the optimization rule is verified through simulation testing and historical data backtracking, and a dynamically adaptive and self-iterative optimization relation rule system is formed, so that the limitation of traditional evaluation is broken through, a scientific basis is provided for privacy protection strategy optimization, and the privacy governance efficiency is improved.

The invention discloses a geotechnical engineering catastrophe dynamic real-time intelligent early warning method and system based on displacement monitoring, and the method comprises the steps: collecting the real-time displacement data and related parameters of a geotechnical engineering region through displacement monitoring equipment, and transmitting the real-time displacement data and related parameters to a bank slope stability evolution analysis platform to establish a multi-dimensional database; calling a fractured rock mass effective stress analysis model to calculate rock mass effective stress distribution characteristics, and inputting a multi-grid sliding surface stress calculation algorithm to obtain a potential sliding surface stress state and a critical threshold value; inputting the sliding surface stress parameters and the displacement data into a multi-field coupling analysis learning prediction model to obtain a displacement evolution trend and a catastrophe risk coefficient; and finally, real-time early warning information is generated and fed back through the catastrophe dynamic real-time intelligent early warning module. The method improves the real-time performance and accuracy of early warning, can effectively guarantee the safety of geotechnical engineering, and is suitable for catastrophe early warning scenes of geotechnical engineering such as bank slopes and foundation pits.

The invention discloses a multi-device collaborative passenger flow statistical method and system, and the method comprises the following steps: presetting a unique identity label and a physical position index for devices, reading the unique identity label and the physical position index, and initializing the attribute information of the devices; a user datagram protocol broadcasting mechanism is started, and heartbeat information including the unique identity label, the physical position index and the online state is sent according to a preset period; monitoring the user datagram protocol broadcast message in the local area network, constructing and maintaining an online equipment list, and updating the online state of the equipment according to the heartbeat information receiving analysis condition; judging adjacent equipment based on a physical location index, and deciding whether to start a first boundary or a second boundary according to the online state of the adjacent equipment; and the decision result is transmitted to a passenger flow statistical algorithm to generate a shop-crossing detection line. According to the invention, multi-device collaborative passenger flow statistics dynamic boundary configuration is realized, the shop-crossing detection line is accurately generated, and the passenger flow statistics problems of fixed boundary configuration, easy missed counting and poor multi-device collaboration are solved.

The invention discloses a customer portrait analysis method and system based on a knowledge graph, and the method comprises the steps: S1, collecting a user behavior event flow and an external environment event flow, and generating a dynamic event signal carrying a timestamp based on a heterogeneous data source; s2, responding to a dynamic event signal, and analyzing an event type to trigger incremental updating operation; s3, in response to the real-time graph updating signal, updating the feature vector of the user node through an incremental graph calculation algorithm to generate a portrait updating signal; s4, generating a graph updating instruction and a portrait recalculation instruction to form a cooperative control signal; and S5, feeding back a graph updating instruction in the cooperative control signal to an incremental updating operation step, and feeding back a portrait recalculation instruction to a feature vector updating step to drive a real-time cooperative closed loop. According to the air quality intelligent monitoring method and system based on sensing data feedback, the problems of client portrait hysteresis quality and low map-portrait cooperation efficiency can be solved.

The invention provides a method and a device for generating a customized report of an SAAS (Software as a Service) system based on dynamic template configuration. The method comprises the following steps: acquiring a customized visual report template for realizing business data decoupling; editing the report template based on a preset editor, and generating a template configuration file; analyzing a structured marker in the template configuration file to generate a metadata description file; querying a business database through a unified data interface according to a data requirement defined by the metadata description file, and obtaining and assembling customized business data corresponding to the tenant ID; and at least based on the customized business data, controlling a rendering process through a dynamic position calculation algorithm, and dynamically filling the data to a corresponding position of the report template to generate a customized report. According to the method, the problems of code redundancy and difficulty in maintenance of the SAAS multi-tenant report are solved, zero code configuration is realized, and report generation efficiency and tenant personalized adaptation capability are improved.

The invention relates to a two-dimensional image and geometric constraint-based cargo stack three-dimensional pose detection method and device, which are applied to the technical field of computer vision and logistics automation, and comprises the following steps of: through an edge straight line screening strategy, combining robust fitting of a random sampling consistency algorithm, calculating a three-dimensional pose of a cargo stack; a real physical boundary can be effectively and accurately recognized from complex visual interference such as adhesive tape, labels and printed patterns on the surface of a container, the accuracy and robustness of edge detection are remarkably improved, and therefore the high precision of final three-dimensional pose calculation is guaranteed; and secondly, only a common industrial camera is needed, and an expensive three-dimensional sensor such as a laser radar or a depth camera is not needed, so that the hardware cost and the maintenance complexity of the system are greatly reduced, and the cost benefit is extremely high. And thirdly, an efficient image processing and geometric calculation algorithm is mainly adopted, the calculation complexity is low, and the requirement for real-time detection of the goods stack on an industrial automatic assembly line can be met.

The invention relates to the field of data query, and discloses a data aggregation query method and system based on time dimensionalities, the method comprises the following steps: obtaining a data aggregation query request, the data aggregation query request at least comprising a time index table of the time dimensionalities, the time dimensionalities being represented by at least one of year, month, day, hour and minute; analyzing the data aggregation query request, and determining an aggregation granularity, a date index value and an aggregation step length in a time index table; performing aggregation calculation according to the aggregation granularity, the date index value and the aggregation step length, and determining an aggregation date index; and performing field matching in a database through the aggregation date index, and performing grouping aggregation on matching results to determine a data query result. Indexes are added for different aggregation dimensions by creating a date index table, and an index calculation algorithm is combined, so that multiple time dimension query requirements are met, the data query speed can be remarkably increased, consumption of calculation resources is reduced, and the query flexibility is improved.

The invention discloses a rock shear seepage coupling true triaxial test system, which relates to the technical field of rock mechanical tests, and comprises a host, a sigma 1 / sigma 2 direction loading module, a sigma 3 direction confining pressure module, a pressure chamber auxiliary system, a sample clamp, a pore water seepage system, a temperature system, a control module and a data acquisition and processing module, through servo closed-loop linkage double-pump loading in the sigma 1 / sigma 2 direction, synchronous output of the double pumps and coordination of pressure supply of the two oil cylinders by the controller, a strain correction algorithm is combined, stability of a stress loading center is guaranteed, strain measurement accuracy is improved, confining pressure is accurately controlled in the sigma 3 direction through a double-balance pressure chamber and a pressure regulation algorithm, and the stress measurement accuracy is improved. The pressure chamber is in full-automatic operation, manual steps are omitted, errors are reduced, efficiency is improved, a stress-free blank angle clamp eliminates friction interference, a seepage system supports a double-loading mode, a control module achieves multi-control-mode impact-free switching, a data processing module is combined with an elastic modulus calculation algorithm, rock mechanical parameters are accurately obtained, and the multi-field coupling test requirement is met.

According to the method for designing the reasonable arch axis of the large-span arch bridge based on the hybrid calculation algorithm and the self-adaptive load distribution, an analytic equation method, a curve fitting method and an intelligent optimization algorithm are combined, and by selecting the initial arch axis, introducing a dynamic load distribution model and applying a genetic algorithm and a particle swarm optimization algorithm, the reasonable arch axis of the large-span arch bridge is designed. Global and local optimization is carried out, and the optimal shape and load distribution of the arch axis are ensured. And finally outputting design parameters, such as a control point, a bending moment, thrust and the like. According to the method, the design precision, flexibility and safety can be effectively improved, the material utilization rate is optimized, the cost is reduced, and the method is particularly suitable for design of large-span bridges and has high practical value.

The invention provides a smooth non-uniform rational B-spline three-dimensional terrain entity fitting creation method and system, which are mainly applied to the field of pumped storage power station engineering and realize efficient conversion from a two-dimensional contour line to a smooth terrain entity. According to the method, a technical route of an NURBS terrain entity is finally generated by establishing a triangulation network curved surface, specifying a boundary, converting DEM data, creating a grid curved surface, extracting control points and fitting an NURBS curve in a UV direction. Converting the contour line into DEM data and creating a grid curved surface; extracting control points and respectively fitting NURBS curve groups according to U / V directions; a complete NURBS three-dimensional terrain entity is formed by enclosing the surface curved surface, the bottom plane and the four side curved surfaces. According to the method, on-demand adjustment of terrain precision can be achieved, the generated entity can be directly used for CAE simulation calculation and can be combined with a panel dam partition amount calculation algorithm, and the engineering design efficiency is improved.

The invention discloses a file access cold and hot degree calculation method and system based on a large model and a medium, and belongs to the technical field of data storage. The method comprises the following steps: a system initialization and monitoring configuration stage: initializing a cold and hot degree calculation algorithm, and loading a pre-deployed large language model; a multi-dimensional feature extraction stage: extracting a multi-dimensional feature vector of the target file in real time; in the dynamic prompt generation stage, the multi-dimensional feature vectors are dynamically arranged into structured natural language prompts, and the structured natural language prompts are input into a large language model; in the popularity generation and cache management stage, a popularity score of each file is generated, and the cache space is managed according to the popularity score; and in the adaptive learning and optimization stage, an implicit user feedback loop is established, and when feedback signals with preset numerical values are accumulated, increment fine tuning is carried out on the large language model according to the collected feedback data. According to the method, the cache hit rate is remarkably improved, and the access fluency of the key data of the user is guaranteed.

The invention provides an optimization method and system of a distributed battery management system. The method comprises the following steps: acquiring battery cell parameters, scene parameters and historical charging and discharging data of a battery cell, and evaluating a battery aging stage; calling a matched battery cell state calculation algorithm according to the scene parameters and the battery aging stage; calculating battery cell state information of the battery cell according to the battery cell parameters, the scene parameters and a battery cell state calculation algorithm; according to the cell state information, the scene parameters and the battery aging stage, dynamically adjusting an equalization threshold and an equalization rate, and executing an equalization strategy to obtain equalization state information; periodically uploading the operation data to a cloud server, receiving an algorithm update package, and updating an adaptive algorithm library; and calculating the overall state information of the battery pack according to the cell state information and the equilibrium state information. The calculation precision of the battery cell state can be effectively improved, the cycle life of the battery is prolonged, and the use safety of the battery is improved.

The invention relates to the technical field of animal monitoring, and discloses a wild animal multi-modal data fusion analysis method, which comprises the following steps: adding corresponding timestamp information to sensor data detected by a sensor assembly arranged at an animal necklace, performing attitude calculation on the converted attitude characteristic data by adopting a six-axis attitude calculation algorithm to obtain a corresponding pitch angle, a roll angle and a yaw angle; constructing a multi-modal feature vector according to the posture feature, the physiological feature, the environment feature, the spatial-temporal feature and the derivative feature; and inputting the multi-modal feature vector into an animal behavior recognition model to perform behavior recognition so as to determine a current behavior tag of the corresponding wild animal. According to the wild animal multi-modal data fusion analysis method in the embodiment of the invention, the state of the wild animal can be comprehensively described. The multi-modal feature vector fuses information of multiple dimensions, behaviors and physiological states of animals in different scenes can be described more accurately, and the recognition accuracy is improved.

The invention discloses an electric energy quality operation data management operation and maintenance system based on cloud collaboration, and relates to the technical field of cloud collaboration, and the system comprises a data collection module which collects the number, position, peak power consumption and transmission data of terminals in real time, processes the data through a central calculation module to obtain abnormal parameters and a lag model after preprocessing, analyzes the transmission state according to the abnormal parameters and the lag model, and stores the data; if yes, whether power failure occurs or not is analyzed, and if power failure occurs, an alarm module is called. The central calculation processing module constructs a lagging model, couples parameters to quantitatively evaluate a transmission state, triggers an adjacent-end intelligent calculation algorithm to shunt data when a threshold value is exceeded, relieves bandwidth pressure, distinguishes transmission delay and power failure, avoids misjudgment, and reduces resource waste. Millimeter-level positioning of a power failure area is realized in combination with terminal three-dimensional coordinates, and cloud data are associated to provide one-stop information support.

The invention provides an anti-stray magnetic field rotation angle detection method and system for a three-way sensor, and relates to the technical field of sensor signal processing and motor control, and the method comprises the steps: enabling the three-way sensor to be fixed on a circuit board at an interval of 120 degrees, the sensing axes of the sensors face the rotating part with the permanent magnet together, and the magnetic field direction of the permanent magnet is perpendicular to the sensing axes. The sensor collects three paths of mixed signals containing real angle signals and spurious interference generated when the rotating component rotates, then the signals are subjected to Clark transformation to generate two-phase orthogonal signals, and then anti-interference digital signals are obtained through differential processing and analog-to-digital conversion. Then, a deep learning network based on an attention mechanism is adopted to perform feature enhancement on the signals, and finally, the angle of the rotating part is accurately determined by using an angle calculation algorithm based on the enhanced signals. According to the invention, the accuracy and reliability of angle detection in a strong stray magnetic field interference environment are improved.

The invention relates to the technical field of liquid level reading identification, and discloses a liquid level meter reading identification method based on computer vision. The method comprises the following steps: acquiring and preprocessing an image, acquiring a digital image through image acquisition equipment, and executing normalization, noise removal and contrast enhancement; feature extraction and weight generation: extracting features such as a scale line position and a pointer angle from the preprocessed image, and generating a reading preference weight vector; performing parameter mapping and optimization, mapping the weight vector into an identification control parameter, referring to a predefined parameter anchor point in an offline optimization database, and performing interpolation calculation to adapt to a current image condition; and reading calculation and output: executing a liquid level value calculation algorithm by using the optimized parameters and outputting a result. The method adapts to different image environments through multi-stage cooperation, the adaptability and stability of liquid level reading recognition are improved, and the method is suitable for automatic reading scenes of various liquid level instruments.

The invention discloses a universal shaped protection and monitoring method based on an Internet of Things intelligent system, and relates to the field of safety protection of building engineering construction. A universal embedded intelligent control box is embedded into various set protection facilities, a matched sensor group is used for collecting data, real-time self-diagnosis and risk assessment of the facilities such as edge guardrails and tool type step ladders are achieved by means of an edge calculation algorithm, then a dynamic risk assessment model is adopted to output a comprehensive risk weight value, and the risk assessment accuracy is improved. Triggering multi-level linkage alarm according to comparison results of the data and different levels of thresholds, and finally uploading the data to a cloud through a communication module for collaborative management and block chain evidence storage. According to the invention, the problems of monitoring lagging, passive early warning and the like of a traditional protection facility are solved, and the intelligent level and management efficiency of construction safety protection are improved.

The invention relates to the technical field of data calibration, and particularly discloses an attitude calibration method and system for a self-adaptive anti-shake handheld three-dimensional scanner, and the method comprises the steps: reading IMU initial data to initialize an attitude calculation algorithm and an initial gyroscope zero offset estimation value, carrying out the real-time compensation of the original angular velocity data of a gyroscope based on the current zero offset estimation value, and carrying out the calibration of the attitude of the self-adaptive anti-shake handheld three-dimensional scanner. Second attitude data is obtained by resolving accelerometer data; a final attitude is output through complementary filtering fusion; the quasi-static state of a scanner is analyzed and judged through IMU data variance; original data of a gyroscope is collected in the state to solve an average value; and the zero offset estimation value is updated through first-order low-pass filtering and is fed back to the compensation step. According to the method, hardware cost does not need to be increased, whole-process online self-calibration is achieved, attitude drift is reduced, the algorithm is efficiently adaptive to a low-cost processor, and long-time scanning precision and real-time performance are guaranteed.

The present invention discloses a method for continuous running obstacle avoidance and wear measurement of power lines, which involves the detection and avoidance of obstacles on the power lines and the detection and feedback of the wear degree of the power lines; during the inspection process, when the diffuse reflection laser sensor detects the presence of an obstacle on the power lines, the running obstacle avoidance method is used to realize the retractable running wheels to open outward to a preset angle to complete the obstacle avoidance function; the online running obstacle avoidance device is equipped with a line laser sensor to form a power line wear inspection device, which performs the power line wear detection task, and adopts the wear state internal calculation algorithm to calculate the wear state value of the power line, and compares the wear state value obtained by the detection calculation with the standard safe wear range value of the power line to judge whether the wear degree of the power line exceeds the safety threshold and needs maintenance and repair; the method of the present invention has important research significance and practical value in the actual maintenance and repair operations of railway power line wear detection equipment.

The invention discloses a swallowing type cow rumen sensor and a disease monitoring and early warning system. Comprising a swallowing type dairy cow rumen sensor, a data receiving host and a cloud platform upper computer, the sensor is of a sealed columnar capsule structure, a pH detection assembly, a TDLAS technology-based methane gas sensing system, a temperature sensor, a three-axis attitude sensor and a vibration power generation unit are integrated in the sensor, and the sensor resides in a rumen through a counterweight; the cow behavior recognition module is used for processing the collected posture data in real time based on an edge calculation algorithm built in the main control module so as to realize cow behavior recognition; the data receiving host is configured with a LoRa wireless receiving module and a 4G communication module and is used for receiving and synchronously uploading data; and the cloud platform upper computer analyzes the uploaded multi-dimensional physiological feature data and behavior recognition results based on a deep learning algorithm so as to realize disease diagnosis and accurate feeding decision. The device solves the problem that the deep body sign of the dairy cow is difficult to obtain, and has the characteristics of small size, corrosion resistance, discharge prevention, self power supply and the like.

The optimal replacement timing for consumable parts is set for each user. [Solution] The image forming apparatus includes a replaceable toner container 101 and a controller 109 that changes a lifespan calculation algorithm for calculating the lifespan when the toner container 101 is replaced according to the timing estimated from its lifespan.

The invention relates to the field of batteries, and discloses a battery welding positioning method and a welding device.The battery welding positioning method comprises the steps that coordinates of two fixed reference points on a battery pack and center position data of a plurality of pole columns are obtained at an addressing station; based on the coordinates of the two fixed reference points and the center position data of each pole, respectively calculating and storing geometric feature data of a geometric figure formed by the center point of each pole and the two fixed reference points; the coordinates of the two fixed reference points are obtained again at the welding station; according to the reference point coordinates obtained again and stored geometric feature data, welding position coordinates of all the pole columns under the current coordinate system are inversely calculated; based on the welding position coordinates, the welding device is guided to move to the corresponding position to execute welding; a coordinate resolving algorithm based on a fixed geometrical relationship is used for replacing a traditional mode of relying on high-precision mechanical repeated positioning, multi-link accumulative errors are eliminated fundamentally, and submillimeter-level welding positioning is achieved.

The invention provides a semiconductor defect analysis method, device and equipment based on an intra-cluster square error, and belongs to the field of semiconductor manufacturing, and the method specifically comprises the steps: obtaining to-be-clustered data in a data set; the clustering numbers are traversed from 1 to N, the intra-cluster square error of the to-be-clustered data corresponding to each clustering number under the K-means algorithm is calculated, and N is a natural number not smaller than 5; dynamically determining the optimal clustering number for the to-be-clustered data based on the difference second-order statistics of the intra-cluster square error; and clustering the to-be-clustered data according to the optimal clustering number, analyzing the clustering center of each category, and determining the defect of each category. Through the processing scheme provided by the invention, the optimal clustering number is dynamically determined, and the defect analysis accuracy is improved.

The invention discloses an atrial fibrillation anomaly detection method and system based on multi-sensing time-frequency pseudo anomalies, and the method comprises the steps: obtaining an atrial electrophysiological signal sequence through an HDS high-density sensing atrial fibrillation analysis platform, carrying out the time-frequency conversion of the signal sequence, constructing a multi-modal time-frequency tensor model, and extracting a time-frequency feature subset related to the atrial fibrillation anomaly; dynamically distributing feature weights by utilizing an extrusion excitation time-frequency pseudo-selection model so as to optimize features; constructing a double-domain hypersphere feature space based on the optimized features, calculating a pseudo-anomaly distance value through a double-domain hypersphere pseudo-anomaly distance calculation algorithm, and dividing a suspected atrial fibrillation anomaly feature sample set in combination with a preset threshold; and carrying out feature fusion on the suspected abnormal sample set, extracting common abnormal features and generating a detection result. The system corresponds to six units, the comprehensiveness of feature extraction and the accuracy of anomaly recognition are greatly improved, the clinical requirements for atrial fibrillation detection are met, and reliable technical support is provided for early diagnosis of atrial fibrillation.

The present application relates to the technical field of intelligent corn straw harvesting, and specifically discloses a straw chopping length detection method and system combining a neural network and image processing, the method comprising: acquiring original images with various morphological characteristics; constructing a YOLOv5 neural network model; outputting the boundary box of the straw target and the reference object; and generating a straw region of interest image; performing image processing on the straw region of interest image and extracting the straw edge; determining the pixel area occupied by the straw based on the straw edge; calculating the pixel length of the straw based on the least-enclosing-rectangle fitting; converting the pixel length of the straw into actual physical dimensions based on the reference object calibration; correcting the actual physical dimensions based on the curvature compensation model; and accurately measuring the length of the chopped corn straw based on YOLOv5 and image processing. The straw region of interest is located by YOLOv5, the target is accurately segmented by traditional image processing, and the original image is processed by the length calculation algorithm, so that the length of the straw can be accurately predicted.

The application relates to an AR glasses binocular calculation algorithm, which is applied to AR glasses provided with left and right light machines, an eye camera and a master control module, and comprises the following steps: S1, initialization and test image projection, after system initialization and ghost image displacement correction are completed, the left and right light machines respectively project binocular calibration images to the eye camera; S2, center calibration positioning, left and right eye field images are acquired through the eye camera, and left eye center coordinates and right eye center coordinates where the binocular calibration images in the left and right eye field images are respectively extracted through an image recognition algorithm; S3, binocular alignment deviation calculation, the position alignment deviation of the left and right eyes is calculated according to the left eye center coordinates and the right eye center coordinates acquired in step S2; S4, dynamic light machine position adjustment, taking the center coordinates of the eye camera as the reference, the left and right light machines are adjusted in the horizontal direction and the vertical direction; and S5, iterative optimization, steps S2-S4 are repeated until the binocular alignment or the maximum iteration number is reached.

The invention discloses a construction method of an unmanned aerial vehicle multi-spectral remote sensing basic model based on agricultural application, and relates to the technical field of intelligent agricultural equipment, and the method comprises the following steps: S1, collecting a multi-band remote sensing image of a rice region through a multi-spectral camera carried by an unmanned aerial vehicle; s2, calculating an anti-flooding vegetation index, and generating a vegetation coverage rate initial value according to the anti-flooding vegetation index; s3, extracting a rice plant area image, and inputting the rice plant area image into the trained rice state recognition model; s4, judging whether the flooding stress probability is greater than a flooding threshold value or not; and S5, determining the rice growth potential grade based on the vegetation coverage rate initial value or the corrected vegetation coverage rate. According to the method, through the anti-flooding vegetation index and the self-adaptive calculation algorithm in the turbid water body, the strong absorption interference of the water body in the near-infrared band is effectively stripped, so that the initial value of the vegetation coverage rate can truly reflect the survival state of underwater vegetation, and the situation that part of flooded healthy rice is misjudged as poor growth or death is fundamentally avoided.

The present technology relates to an imaging system. The imaging system can comprise at least one processor configured to apply a projection precomputation algorithm and an x-ray tomography image reconstruction system. The projection precomputation algorithm can be configured to: generate a projection operator matrix that can be used to calculate a plurality of voxels from a plurality of projection measurements before the plurality of projection measurements is acquired and store the projection operator matrix in memory. The projection operator matrix can be at least one of: a compressed matrix, a multi-iteration projection operator matrix, and a combination thereof. The x-ray tomography image reconstruction system can be configured to apply the projection operator matrix to generate a reconstructed three-dimensional image of at least an internal portion of a selected object under a surface of the selected object when the plurality of projection measurements is acquired.

The invention provides a budget target measurement and calculation method and system based on multi-scene dynamic analysis. The method comprises the steps of total budget amount measurement and calculation and total project amount measurement and calculation. The budget total amount calculation comprises historical scene calculation: calculating a historical scene budget total amount and an index value through a plurality of modes based on budget subjects; cost regulation scene measurement and calculation: according to the cost regulation index basic information, each cost regulation index value and the total regulation cost amount are measured and calculated through a cost regulation calculation algorithm; calculating an industry benchmarking scene, comparing with index data of the same industry based on a benchmarking method, and displaying the current position of the company in the industry and the deviation of a benchmarking value; the project total amount calculation comprises the steps of calculating the available amount of the project and determining the project which can be included in the budget range; positioning the problem and adjusting the direction based on the comparison of the measurement and calculation values of the scene targets and downward drilling; and based on different business requirements, calculating a multi-version multi-scene budget target calculation value, and selecting a version conforming to a company development target to guide the company to carry out annual budget.