360results about How to "Computationally efficient" patented technology

The invention discloses a complex terrain wind resource assessment method based on measured data correction of an anemometer tower, and the method comprises the steps: simulating a complex terrain wind field based on a mesoscale WRF mode, and obtaining the mesoscale data of an innermost layer nested domain containing a wind power plant; according to the mesoscale data obtained in the step S1, microscale computational domain boundary inflow information is extracted, and initial prediction field information of the complex terrain wind field is obtained based on a mesoscale-microscale coupling mode; according to the anemometer tower position and the flow field characteristics, determining an anemometer tower reference height used for data correction and a corresponding observation wind speed and turbulence intensity; and S3, correcting the WRF-CFD numerical simulation result obtained in the step S2 by adopting the related data of the anemometer tower determined in the step S3 to obtain corrected wind speed and turbulence information of the wind field of the complex terrain. According to the method, the medium-micro scale coupling numerical simulation result can be improved, and the accuracy of wind resource evaluation is greatly improved.

The invention relates to a structural parameter construction method for reducing vibration of a transformer. The method comprises the following steps: acquiring vibration characteristics and working condition data of the transformer; constructing a genetic algorithm model based on the objective function; candidate solution vibration performance verification based on finite element simulation; constructing a hybrid optimization strategy based on a genetic algorithm and finite element simulation; verifying and optimizing the scheme under a multi-dimensional working condition; outputting a vibration calculation result and evaluating a scheme. According to the structural parameter construction method for reducing the vibration of the transformer, the preliminary schemes are screened by applying a fast convergence genetic algorithm, and the candidate schemes are subjected to high-precision verification in combination with finite element simulation, so that the defects of a traditional vibration calculation method in the aspects of efficiency and accuracy are overcome; and the design change can be quickly responded, and the vibration performance is optimized, so that the high-standard requirements of modern power equipment on the aspects of safety and reliability are met, and powerful technical support is provided for the design and improvement of the transformer.

The invention provides a privacy computing security system based on a domestic cryptographic algorithm. The privacy computing security system comprises a key management module, a data encryption module, a homomorphic encryption module, a differential privacy module, an intelligent threat detection module and an access control module. The key management module generates a key by adopting an anti-quantum computing algorithm based on a learning and sampling problem LWE, and performs distributed storage and management by utilizing a block chain technology; the data encryption module performs data encryption and decryption by using an SM4 algorithm; the homomorphic encryption module executes arithmetic and logic operations in a data encryption state; the differential privacy module dynamically protects data privacy; the intelligent threat detection module monitors and detects abnormal activities in real time based on a deep learning model; and the access control module manages user access authority. According to the method, multiple security technologies are integrated, so that the anti-quantum computing capability, data privacy protection and computing efficiency are improved, and the method is suitable for data processing scenes needing high security and privacy protection.

The invention relates to the technical field of civil engineering, and particularly discloses a tunnel early-high-strength rock anchoring and shotcreting synergistic effect bearing arch active support design method which comprises the following steps: determining a rock anchor bearing arch acting load and establishing a rock anchor bearing arch calculation model; calculating to obtain the most unfavorable section displacement and stress of the rock anchor bearing arch; verifying whether the displacement of the rock anchor bearing arch meets the requirement; a safety evaluation method of the pre-stressed anchor rods is provided, and the safety of the pre-stressed anchor rods is evaluated according to a rock anchor bearing arch calculation result; establishing a sprayed concrete calculation model; calculating to obtain the most unfavorable section displacement and stress of the sprayed concrete; a sprayed concrete safety and durability evaluation method is provided; active support parameters are determined according to the calculation result of the rock anchor bearing arch and the calculation result of the sprayed concrete. By means of the method, the safety and durability of rock-anchor-shotcrete active supporting under different supporting parameters can be simply, rapidly and accurately calculated, reference is provided for tunnel engineering design adopting active supporting, and good engineering value is achieved.

The invention discloses a free-form surface three-axis ball-end cutter equal approximation error finish machining tool path generation method which comprises the following steps: firstly, importing a free-form surface model to be machined, and setting data such as the radius, the line spacing, the approximation error maximum allowable value and the precision of a ball-end cutter; secondly, a group of section planes are planned according to the row spacing to intersect with the curved surface, the intersecting line serves as a cutter contact curve, and an equal-bow-height-error cutter contact iterative search method for driving cutter contact adjustment through the geometric distance is provided for the cutter contact curve on the section planes; the maximum distance between a cutter cutting envelope surface and a cutter contact track line is used as an approximation error, and an adaptive discrete method is adopted to carry out approximation error calculation; and finally, the cutter location points of the equal-bow-height-error cutter contact points serve as initial values, an equal-error cutter location point calculation method of step length self-adaptive adjustment iteration is provided, approximation errors between the cutter location points are all within an allowable range, and therefore the free-form surface three-axis ball-end cutter equal approximation error finish machining cutter path is obtained.

The invention discloses a feature classifier-based thinking chain reasoning mathematical problem solving method and system. The method comprises the following steps of: (1) acquiring a mathematical problem set, and selecting forward and reverse thinking chain examples to splice to form a new set; (2) respectively inputting the new set elements into a model for reasoning to construct a word-level reasoning path spanning tree, and selecting an attention weight matrix after pooling difference processing as node features for storage; (3) traversing all the generated reasoning path spanning trees, and screening nodes meeting requirements to construct a feature classifier training set; (4) training a feature classifier by using a support vector machine algorithm; and (5) through the trained feature classifier, participating in path selection in a pre-training language model reasoning process, and obtaining a relatively accurate reasoning process and answers. By means of the method, adjustment and control of finer granularity of the reasoning path of the pre-training language model can be achieved, accurate reasoning solving of the pre-training language model on mathematical problems is facilitated, and the generalization level of the pre-training language model is improved.

The invention relates to the technical field of voice recognition, in particular to a mixed recognition processing method and device, equipment and a medium, and the method comprises the steps: recognizing command word data based on a command word recognition model, selecting command word data with an error rate lower than a preset range, generating a corresponding phoneme embedding representation, and forming a phoneme embedding dictionary; determining a mixed recognition command word corresponding to the current command word, and generating a mixed recognition list; identifying an audio embedding sequence corresponding to the current command word; obtaining a phoneme embedding sequence of each mixed recognition command word in the mixed recognition list based on a phoneme embedding dictionary; and calculating the similarity between an audio embedding sequence and each phoneme embedding sequence to obtain an identification result. The method and the device can improve recognition accuracy and reduce mixed recognition of command words.

The invention discloses an indoor environment performance optimization design method and system for a tall and large space building based on CFD and a multi-objective optimization algorithm, and the method comprises the steps: building a parameterized analysis model through combining with a BIM model, carrying out the digital simulation analysis of an indoor light environment and energy consumption through employing Honeybee Radio and Honeybee Entry plug-ins in Rhino and Grasshopper environments, determining optimization parameters and objectives, and carrying out the optimization of the indoor environment and energy consumption. And a BIM model and an IDF file corresponding to the optimal schemes are exported, the uniformity of the indoor airflow organization is evaluated based on FFD software, and parameters of the optimal schemes are determined. Compared with a traditional indoor environment optimization method, the high and large space building indoor environment performance optimization and evaluation method is efficient, accurate and economical, and has higher accuracy, higher adaptability and wider applicability. Natural lighting, building energy consumption and indoor three-dimensional thermal comfort can be considered at the same time, and optimization of the indoor environment performance of the tall and large space building is achieved.

The invention discloses an accelerator for accelerating the reasoning process of an unstructured sparse large language model and an operation method of the accelerator. The accelerator comprises a processor module, a direct memory access module, a memory controller module, a DDR memory module, an interconnection bus module, a calculation core module and a router module. The interconnection bus module is connected with the direct memory access module, the memory controller module and the computing core module; the processor module is connected with the direct memory access module; the DDR memory module is connected with the memory controller module; the router module is connected with the computing core module and the adjacent router module; and the calculation core module obtains to-be-calculated data from the off-chip DDR memory module through the interconnection bus module. According to the method, the limit that data reuse is carried out only along a single row or a single column on a traditional systolic array is broken through, cross-row and cross-column data reuse is achieved, the pressure of hardware equipment is relieved, the positions of non-zero elements are coded through bit masks, and the calculation efficiency is improved.

The invention provides a fluid simulation data prediction and noise reduction method, system and device, and relates to the technical field of fluid simulation, and the method mainly comprises the steps: 1, constructing a simulation model; the simulation model comprises an auto-encoder, a denoising model and a decoder which are arranged in sequence; the auto-encoder is used for encoding condition input data and mapping the condition input data to a potential space to obtain characterization data; the denoising model is used for introducing noise into the representation data and converting the representation data into target data through denoising processing; the decoder is used for decoding the target data and mapping the target data to a functional space to obtain simulation result data; and step 2, inputting initial condition data of fluid dynamics into the simulation model, and outputting corresponding prediction result data. According to the scheme, the space noise reduction and output generation operation is completed in the potential space, the operation efficiency can be improved, the operation cost can be reduced, the output can be smoother, and therefore the quality and stability of the output are improved.

The invention relates to the technical field of attendance management, and discloses an electronic class board attendance system for palm vein recognition, which comprises a palm vein data acquisition module for irradiating the palm of a user through a near-infrared light source and acquiring a palm vein image; the image optimization processing module is used for performing optical modeling optimization, noise removal and quality enhancement on the acquired palm vein image; the deep learning recognition module is used for extracting palm vein features and performing identity matching; the attendance record storage module is used for storing and managing user attendance data; and the control and communication module is used for managing cooperative work of all the modules and performing data interaction with an external attendance database. Through the technical scheme of combining near-infrared illumination and the light transmission equation, the palm vein feature image is accurately extracted, the effect of optimizing palm vein contrast and detail definition is achieved, the problems of palm vein feature edge blurring and detail loss are solved, and the image processing quality is improved.

The invention discloses a matrix modeling analysis method and device for a heat exchange network, equipment and a medium, and relates to the field of optimized operation of heat exchangers. Firstly, a temperature transfer matrix of a single heat exchanger is constructed; according to the temperature transfer matrix of the single heat exchanger, temperature transfer matrixes of the multiple heat exchange network units are constructed; constructing a matrix model of the target heat exchange network according to the temperature transfer matrix of each heat exchange network unit; identifying an effective heat transfer coefficient of each heat exchanger in the target heat exchange network based on the measured data; and calculating outlet temperatures of the target heat exchange network under different working conditions based on the matrix model of the target heat exchange network and the effective heat transfer coefficient of each heat exchanger in the target heat exchange network. According to the method, the heat exchange network is analyzed and calculated in a mode of constructing the temperature transfer matrix for direct calculation, a circulating process is not needed, the calculation complexity is reduced, efficient analysis and calculation of the heat exchange network are realized, and a basis is provided for operation optimization of an industrial system.

The invention discloses a scale-effect-free mine dynamic disaster fine monitoring and dynamic early warning method, which comprises the following steps of: arranging a multi-point micro-seismic monitoring network on a coal mine working face, and continuously acquiring and preprocessing micro-seismic signals; an innovative analysis positioning algorithm is adopted to accurately analyze the accurate position and time information of the micro-seismic source; in combination with signal features and positioning data, a four-dimensional joint kernel density estimation and confidence interval theory is innovatively applied, a rock burst risk assessment model is constructed, and a danger level classification standard is determined; and the system calculates risk indexes in real time and dynamically issues early warning. According to the invention, the precision, timeliness and reliability of monitoring and early warning of the dynamic disasters in the mining area are obviously improved, and key technical support is provided for safe production of a coal mine.

The invention discloses a degradation conversion rate calculation method and system based on an epoxy resin alcoholysis model, and belongs to the technical field of thermosetting epoxy resin degradation and recovery. The method comprises the following steps: pouring epoxy resin to cure and mold, carrying out an epoxy resin alcoholysis degradation experiment at different temperatures, and recording degradation conversion rates at different moments; constructing an epoxy resin geometric model, and analyzing to obtain a degradation conversion rate differential expression containing reaction rate constants and geometric parameters; solving the differential equation to obtain a reaction rate constant, and fitting by using an Arrhenius formula to obtain degradation activation energy; analyzing a transesterification process of the epoxy resin and the alcohol solvent and a diffusion process of the alcohol solvent in the epoxy resin, and establishing a degradation conversion rate expression which does not contain geometric dimension parameters; and substituting degradation reaction activation energy, and fitting to determine a degradation conversion rate expression which does not contain geometric dimension parameters. The invention aims to provide a reference for the degradation process analysis of the large-size epoxy resin with a complex shape.

The invention discloses a Chiplet-based matrix chain multiplication accelerator and an acceleration method. The matrix chain multiplication accelerator comprises a first matrix multiplication module, a first external memory interface and a nonlinear processing module, and a second matrix multiplication module and a second external memory interface which are connected with each other through Chiplet. The method comprises the following steps: acquiring operator data of a Transform network and preprocessing the operator data to obtain a matrix chain data stream; based on the matrix chain data stream, performing initialization processing on a matrix chain multiplication accelerator to obtain an initialized matrix chain multiplication accelerator; and inputting the matrix chain data stream into the initialized matrix chain multiplication accelerator for matrix multiplication operation to obtain attention matrix data. According to the embodiment of the invention, the utilization rate of the processing element can be improved, so that the memory access times and the data transmission delay are reduced, and the calculation efficiency is improved. The method can be widely applied to the technical field of computer hardware acceleration.

The invention discloses a medium metasurface reverse optimization method based on a space coupling mode theory, and relates to the field of optics, and the method comprises the following steps: building a cut-off waveguide array based on a metasurface, calculating a guided mode and a propagation constant of each waveguide according to the cut-off waveguide array, and coupling adjacent waveguides through a coupling matrix, a waveguide array is obtained; an input light field is coupled into a waveguide array, propagation of light in waveguides is simulated based on a spatial coupling mode theory model, and near-field intensity distribution is converted into far-field intensity distribution by using a Rayleigh-Sommerfeld diffraction theory; and calculating the difference between the target intensity and the far-field intensity through a loss function, evaluating the effect of the current metasurface design, and gradually adjusting the geometric parameters of the waveguide unit through an optimization algorithm. According to the method, the problems of efficient modeling and optimization in metasurface design are solved through the space coupling mode theoretical model.

The invention provides an image enhancement system and method and a medium. The system comprises (N-1) row cache FIFO (First In First Out) which are connected in series, N row cache registers, a Demosaic module, a G component cache FIFO and a G component cache register. According to the invention, by reasonably controlling the read-write of the row cache FIFO and the register, at least five pixel points are output all the time under the condition that any number of pixel data is transmitted for each row of image data of each clock, so that the calculation requirement of the Demosaic algorithm is met. Under the condition of balancing and optimizing the combinational logic series to be executed in each clock period and the occupation of the total register, in the pipeline design of the Demosaic algorithm, the finiteness of hardware internal resources and the time sequence convergence problem of high clock frequency are fully considered, and by combining the combinational logic series optimization and the pipeline series optimization, the time sequence convergence problem of the high clock frequency is fully solved. In this way, better occupation of various resources of the FPGA is achieved, and efficient calculation is achieved. Based on the calculation strategy provided by the invention, the image enhancement process is finally realized, and the high-quality color display image is obtained.

The invention provides a parking visual positioning method and system based on parking space semantic information and a vehicle-mounted terminal.The method comprises the steps that an aerial view image of a vehicle in a parking environment and a global parking space semantic map are obtained, and the global parking space semantic map is constructed according to the parking environment; inputting the aerial view image into a parking space detection model for parking space detection, and obtaining first parking space semantic information under an image coordinate system; according to the relative position relation between the vehicle and the parking space in the aerial view image, global coordinate conversion is carried out on the first parking space semantic information, second parking space semantic information under a global coordinate system is obtained, and the global coordinate system is constructed based on the parking environment; and matching the second parking space semantic information with the global parking space semantic map, and determining the position of the vehicle in the parking environment. Parking visual positioning is carried out based on the corresponding parking space semantic information of the vehicle in the current parking environment, the position of the vehicle in the parking environment can be accurately determined, and the accuracy of vehicle positioning during parking is improved.

The invention discloses a fracturing crack dynamic inversion method fusing optical fiber strain monitoring and crack propagation simulation, and belongs to the technical field of oil and gas field exploitation, and the method comprises the steps: building a state control equation based on a state variable, and predicting the crack width distribution of a next time step according to the built state control equation; calculating a covariance matrix of a next time step prediction error of the state control equation according to the covariance matrix of the system error of the crack propagation model; establishing an observation equation of the distributed optical fiber strain, and calculating the optical fiber strain corresponding to the state variable of the next time step; according to the monitored optical fiber strain data and the optical fiber strain corresponding to the state variable of the next time step, establishing a state updating equation of slit width distribution; and updating the state of the crack unit, and after updating is completed, entering the prediction of the crack width distribution of the next time step again until a set end moment is reached, so that a physical mechanism is fused and strain data is observed.

The invention discloses a turbulent boundary layer wall surface pressure pulsation prediction method based on deep learning, and belongs to the field of noise prediction, and the method comprises the steps: training a neural network based on unsteady and steady flow simulation data of wall surface grid points to obtain a turbulent boundary layer wall surface pressure pulsation prediction model; a large batch of samples are obtained through one-time simulation calculation, the cost of sample obtaining can be obviously reduced, a large amount of time is saved, and therefore the prediction precision and timeliness of the deep learning model are guaranteed; the nonlinear relation between the turbulent boundary layer parameters and the wall surface pressure pulsation frequency spectrum is established through a deep learning method, a clear mathematical formula is not needed, and meanwhile the difficulty of mathematical requirements is reduced; compared with a traditional prediction method, the method provided by the invention is higher in applicability, wider in application field and higher in generalization ability; in addition, through simulation verification, the method has the advantages of being accurate in result, small in error, efficient in calculation and the like.

The invention relates to the technical field of electric power fault detection, and discloses a fault monitoring system and method based on an electric power acquisition terminal, and the method comprises the steps: constructing a non-linear relation between the power consumption and the temperature through analyzing the historical power consumption data of a user and the weather temperature; the method comprises the following steps: dividing a user electricity consumption day into a plurality of time periods, and setting a time interval threshold value; and in each time period, data are acquired through the electric power and temperature acquisition devices, an electric quantity and temperature scatter diagram is constructed, and nonlinear data fitting is carried out. Thirdly, the similarity between the temperature nonlinear relational expressions of different time periods is calculated, the time periods are divided into sets, and a temperature retrieval set is established; and searching a corresponding electric quantity relation set by matching the temperature nonlinear relational expression of the user in the current time period, and judging whether electric power fluctuation and fault exist or not according to the priority ranking and the relation similarity.

The invention discloses a multi-fault risk assessment and early warning method for a power battery, and the method comprises the steps: requesting the recent life cycle data of an in-service electric vehicle power battery from a cloud server, carrying out the data preprocessing, and obtaining a temperature value of any single battery in the power battery through an interpolation method; differentiating the voltage value and the temperature value of any battery monomer to obtain a fault discrimination signal; establishing a multi-fault risk discrimination model based on the fault discrimination signal to calculate absolute fault degree scores corresponding to different faults of the battery; performing statistics on data distribution of various battery faults and fault degree scores, determining a fault grading range according to a distribution result, and drawing a multi-fault risk early warning graph; and carrying out early warning on results in a specific fault grading range according to severity. According to the method, various faults of the power battery can be evaluated and separated, battery maintenance and overhaul reference can be provided for a vehicle owner in time according to the multi-fault risk early warning graph, calculation is simple, deployment is convenient, and the method has practical application value.

The invention discloses a method and device for detecting the center position in a laser spot image, and the method comprises the steps: obtaining a laser spot image which is a fuzzy circle / circular ring light spot, and solving the center-of-gravity coordinate of the fuzzy circle / circular ring light spot as an initial center position; calculating radial distances from the initial circle center position along a plurality of different directions of the fuzzy circle / circular ring light spot, and calculating an average value of the radial distances in the different directions as an average radius; based on the average radius, utilizing a least square method to fit a new circle center position; and taking the new circle center position as an initial circle center position, repeating iterative calculation until the difference between the current fitting new circle center position and the previous fitting new circle center position is smaller than a preset threshold value, and determining the current fitting new circle center position as a final circle center position. The method is more accurate in circle center position detection and higher in calculation speed.

The invention provides a rail transit environment vibration directional control method and system using a wedge-shaped tree array. According to the method, ground surface vertical vibration caused by passing of a train beside a certain ballast track is calculated by constructing a semi-analytical three-dimensional dynamic response model, simulation of the tree vibration reduction measure effect is achieved by coupling the wedge-shaped tree array into the model, and the tree vibration reduction measure effect is achieved by adjusting parameters of the wedge-shaped tree array. The wedge-shaped tree array with the expected vibration reduction effect is obtained, and then design parameters of wedge-shaped tree array vibration reduction measures are obtained. The wedge-shaped tree array is arranged between a track structure and a target vibration control area, and the selection and arrangement mode of tree characteristics such as tree species, tree height and tree diameter can be optimally designed according to a target vibration reduction frequency band and an expected vibration reduction effect. The invention overcomes the limitation of the traditional vibration isolation technology on cost and implementation, provides a wedge-shaped tree array vibration reduction measure which is low in cost and easy to arrange and meets the environmental protection requirement, and has good popularization and application potential.

The invention discloses an unsupervised anomaly detection method for time series data, and relates to the technical field of anomaly detection of the time series data, which comprises the following steps of: filling a current null value by using an average value of a forward value and a backward value of the current null value data, and performing data normalization processing on numeric data in a data set. The method comprises the following steps: normalizing data to standard normal distribution with a mean value of 0 and a standard deviation of 1, and separating a training set and a test set from a given time sequence data set; according to the unsupervised anomaly detection method for the time series data, potential representation is performed on the data through a beta-VAE encoder, a long-term and short-term memory network module is adopted to estimate the long-term correlation of the potential representation, the forward and backward dependency relationship of the data is captured, and time series prediction is performed on the data. And finally, through average fusion of prediction results and reconstruction of a beta-VAE decoder, a reconstruction error is calculated to detect time sequence abnormity. The method has excellent anomaly detection performance on a plurality of public time series data sets.

The invention relates to a water resource pressure assessment method integrating social economy and climate change. Relates to the technical field of drought basin water resource pressure assessment. The method comprises the following steps: acquiring a historical value and a predicted value of social economic data, and correcting the predicted value of the social economic data to obtain a corrected predicted value; calculating the potential evapotranspiration of the drainage basin in different scenes based on the meteorological data of the historical scenes and the corrected future climate mode data; calculating a future drainage basin water resource quantity based on a correlation between drainage basin rainfall and the water resource quantity; according to the variation trend of the drainage basin drought index in the historical scene and the future scene, drought intensity characteristics are extracted; constructing a drainage basin water resource pressure index calculation formula; and according to the calculated water resource pressure index of the water resource area, standardization is carried out to obtain a standardization index, and according to the standardization index, the water resource pressure change trend of different scene areas is evaluated. According to the method, the quantization and evaluation problem of the drainage basin water resource pressure under the complex condition is solved.

The invention provides a lightweight large model operation method based on end-side deployment. The lightweight large model operation method comprises the following steps: acquiring equipment operation data and storing a model file in a mixed precision format according to quantization precision supported by terminal equipment; determining a mixing precision quantification strategy and carrying out strategy analysis on the equipment operation data; a Key-Value cache file obtained through model reasoning in the historical dialogue is reserved; calculating a semantic embedding vector of the second user request, calculating a cosine similarity between the semantic embedding vector and the first V vector, and judging whether the second user request has a similar intention or not according to a calculation result; and if yes, performing incremental reasoning on the second user request by multiplexing the Key-Value cache file. By monitoring the state of the terminal equipment in real time, dynamically adjusting the quantization level, multiplexing the cache data of the semantic related requests and merging batch request reasoning, the effects of balancing the energy consumption and performance of the terminal equipment, reducing repeated calculation and improving the service time of the equipment and the user experience are achieved.

The invention discloses an industrial robot visual positioning grabbing method for an aircraft rib plate, and the method comprises the steps: collecting a left visual image and a right visual image of the aircraft rib plate, recognizing the type of the aircraft rib plate and a rib plate feature circle in the images through a pre-trained YOLOV5-SEG detection segmentation model, and carrying out the mask segmentation of the feature circle of the aircraft rib plate; contour pixel point separation, skeleton refinement, smoothing processing and ellipse fitting are carried out on the mask, and an airplane rib plate characteristic ellipse contour and a circle center are positioned; binocular depth estimation is carried out on the airplane rib plate characteristic ellipse contour and the circle center to reconstruct three-dimensional space points of a rib plate characteristic circle under a camera coordinate system, and a space normal vector of an actual rib plate characteristic circle is estimated; and establishing an aircraft rib plate workpiece coordinate system under the robot base coordinate system, and visually guiding the industrial robot to carry out positioning grabbing. According to the method, the problems of low feature recognition accuracy and difficult positioning of the aircraft rib plate can be solved, so that the automation degree and the accuracy of the assembly process are improved.

The invention relates to the technical field of civil engineering, and particularly discloses a railway tunnel high-performance active support system design method considering a space-time effect, which comprises the following steps: S1, establishing a tunnel early-strength and high-strength sprayed concrete layer calculation model; s2, determining calculation parameters required by the sprayed layer calculation model according to the tunnel early-high-strength sprayed concrete layer calculation model; s3, influence factors of surrounding rock deformation pressure borne by the tunnel early-strength and high-strength sprayed concrete layer are determined; s4, establishing a surrounding rock deformation pressure calculation method of the tunnel early-strength and high-strength sprayed concrete layer considering the surrounding rock level; and S5, establishing a surrounding rock deformation pressure calculation method of the tunnel early-strength and high-strength sprayed concrete layer considering the rock mass quality index. By adopting the railway tunnel high-performance active support system design method considering the space-time effect, the safety of the tunnel early-strength and high-strength sprayed concrete layer under different time, geological conditions, construction levels and support design parameters can be simply, quickly and accurately calculated.

The invention provides a neural network hardware implementation method and system based on an incomplete specified function, and the method comprises the steps: carrying out the quantification of the input data and weight of a neural network, and obtaining a position index of a non-zero weight; traversing the training set, and obtaining a plurality of data sets related to the non-zero weight according to the position index of the non-zero weight based on an incomplete specified function; performing logic minimization on the basis of the plurality of data sets, generating a Boolean logic expression based on an incomplete specified function, and determining a flash memory logic array scale and internal port connection lines according to a cube of the Boolean logic expression and logic variables in the Boolean logic expression; the flash memory logic array is constructed according to the scale of the flash memory logic array and the internal port connecting line, and a peripheral circuit of the flash memory logic array is constructed, and the peripheral circuit is mainly used for processing output data of the flash memory logic array. According to the invention, power consumption and time delay in a neural network hardware implementation process are reduced.