28 results about "Standard algorithms" patented technology

The invention discloses a multi-dimensional enterprise qualification evaluation method and system, and the method comprises the steps: obtaining multi-dimensional original data, and obtaining a standardized enterprise multi-dimensional feature data set through employing a data cleaning and normalization preprocessing technology; aiming at a standardized enterprise multi-dimensional feature data set, performing grouping optimization and weight calculation on indexes by utilizing an improved WP-PVC algorithm, and constructing a multi-dimensional evaluation index system; based on the multi-dimensional evaluation index system, a double-standard WP-PVC algorithm is adopted to carry out inter-index correlation analysis and score calculation, and an enterprise qualification comprehensive score result is generated; according to an enterprise qualification comprehensive scoring result, in combination with a multi-logarithm algorithm of random online sorting, calculating a matching degree between the enterprise and various science and technology projects, and outputting a project matching recommendation list and application success rate prediction; and automatically generating an enterprise qualification diagnosis scoring report based on the enterprise qualification comprehensive scoring result and the project matching recommendation list. According to the invention, comprehensive evaluation of enterprise qualification, accurate project matching and scientific application guidance are realized.

The invention relates to the technical field of electric power measurement online monitoring. The invention discloses a CVT error calculation method and device based on a virtual standard algorithm and a storage medium, and the method comprises the steps: collecting the voltage original waveform data of a plurality of CVTs in a homologous state in real time, and calculating the amplitude and phase of the data; constructing a steady-state data set; calculating an initial virtual standard; calculating an initial voltage ratio difference value and an initial voltage angle difference value; inverting a real-time virtual standard; calculating an overall virtual standard; calculating an instantaneous voltage ratio difference value and an instantaneous voltage angle difference value; and outputting a CVT state judgment result. According to the method, the accuracy of CVT error calculation is effectively improved, the state of the mutual inductor can be more accurately judged, and a powerful guarantee is provided for stable operation of a power system.

The invention discloses a robot optimal path planning method based on an improved Hemma optimization algorithm. A plurality of improvement measures are provided for problems possibly existing in path planning of a Hemma optimization algorithm. Firstly, a Circle chaotic mapping strategy is adopted to replace random initialization, so that the quality and distribution uniformity of an initial population are improved, and the global exploration capability is enhanced. Secondly, mathematical models of three core behavior stages of a standard HO algorithm are deeply optimized, and adaptive dynamic weight, a dynamic weighting strategy based on a current optimal solution and individual fitness and guided Levy flight direction adjustment are introduced; and finally, introducing a dynamic stage conversion and adaptive exploration intensity mechanism DPTAEI, and dynamically adjusting the participation proportion of the individual in different behavior stages and the intensity of the exploration behavior according to the real-time search progress of the algorithm. Through the improvements, the optimization precision, the convergence speed and the global search capability of the IHO algorithm in the aspect of robot path planning are remarkably improved.

The invention discloses a system for realizing file authorization sharing based on an SM2 proxy re-encryption algorithm, and the system comprises a client module which is used for file encryption, key generation and key exchange between users; the server module is used for storing a file ciphertext and a Capsule and carrying out key conversion; and the encryption algorithm module is used for realizing secret key generation based on SM2, file encryption based on SM4 and Hash calculation of SHA3. The method has the beneficial effects that national commercial password standard algorithms such as SM2, SM4 and the like are fully fused, and data encryption and proxy re-encryption functions in a domestic algorithm environment are realized on the basis of ensuring the system security. As an elliptic curve public key cryptographic algorithm autonomously designed in China, the SM2 algorithm has the characteristics of public algorithm structure, high security, excellent calculation efficiency and the like.

The present application belongs to the field of highway engineering information technology, in particular to a multi-standard EBS decomposition method and system based on highway engineering design information, the method comprising the following steps: S1, obtaining highway engineering design results and extracting design data; S2, performing data conversion on the design data according to a configuration file to obtain structured intermediate data; S3, converting the structured intermediate data into one or more EBS standard data according to an EBS standard algorithm. Based on this idea, the efficiency of data delivery is greatly improved, and the difficulty of data import for designers is reduced, and designers no longer need to consider different EBS standards, and design data can quickly generate data of different EBS standards.

The invention relates to the field of data processing, in particular to a correlation analysis method for gas chromatography detection data, which comprises the following steps of: extracting peak shape characteristics of each peak, and constructing peak shape characteristic penalty terms among different peaks according to peak shape characteristic differences; and calculating the DTW distance of the local chromatograms to which the corresponding data points belong at the corresponding time point pairs by combining the difference condition between the corresponding signal intensities of the local chromatograms to which the different data points are located at the time point pairs and a dynamic time warping algorithm. Aiming at the peak overlapping problem of a standard DTW algorithm in gas chromatographic data correlation analysis, the sensitivity of the DTW algorithm to the peak shape characteristics is improved by introducing a self-adaptive multi-characteristic fusion penalty term based on the peak shape characteristics in distance calculation, so that the contribution of different compounds in overlapped peaks can be distinguished more accurately, and the accuracy of the gas chromatographic data correlation analysis is improved. Therefore, the correlation between the compounds is evaluated more accurately, and the influence of peak overlapping on a correlation analysis result is reduced.

This invention relates to the field of digital urban planning and intelligent path optimization technology, and discloses a method for optimizing urban path network replacement points based on an improved Dijkstra algorithm. First, a county-level facility-road network coupled graph model is constructed, and facility load levels and population weights are labeled. The standard Dijkstra algorithm is used to calculate the initial coverage rate and load rate. Based on the load level and coverage blind spots, a load-blind spot coupled gravitational field model is constructed, and AI adaptive weights are used to generate candidate replacement point heatmaps. Coverage gain, blind spot attraction, and load diversion factors are introduced to construct a multi-dimensional cost function for the improved Dijkstra algorithm, and the coefficients are dynamically adjusted using AI adaptive weights. The comprehensive cost is calculated by traversing the candidate points, and the point with the minimum comprehensive cost is selected as the optimal replacement point. The process is iterated until a termination condition is met, and then the solution is output. This solves the problem of not being able to automatically locate the optimal replacement point position that balances coverage improvement and load diversion.

A reinforcement learning method for real-time control security of distribution networks based on quadratic programming includes the following steps: Offline training of the DRL agent: Constructing a DRL agent using the Actor-Critic algorithm architecture, modeling the distribution network optimization control problem as a Markov decision process, defining the state space, action space, and multi-objective reward function, and training the DRL agent for distribution network optimization control through multiple rounds of exploration and learning in a simulation environment; Online execution and immediate safety correction. Through rapid checking supported by a physical model and quadratic programming correction, provable mathematical safety guarantees are provided for each online control action, fundamentally solving the core problem that standard DRL algorithms cannot inherently guarantee that actions meet the physical safety constraints of the power grid. This method, while ensuring the decision-making speed and policy autonomy of the DRL agent, generates reliable and safe actions in real time, achieving computationally efficient and automatically intervened real-time safety control of the distribution network.

The invention belongs to the technical field of data security protection, and particularly relates to an intelligent manufacturing data security protection method based on a post-quantum technology, which comprises the following steps of: dividing a production monitoring image into a plurality of non-overlapping blocks with specified sizes through a block truncation algorithm based on an absolute distance, and obtaining a bitmap, a low quantization value and a high quantization value of each non-overlapping block, the specified size is the preselected size with the maximum comprehensive effect value; according to a preset key matrix and a weight matrix, embedding secret information into the bitmap of each non-overlapping block through a block hiding algorithm to obtain a ciphertext bitmap of each non-overlapping block; and coding the low quantization value, the high quantization value and the ciphertext bitmap of each non-overlapping block, and encrypting and storing a coding result based on an NIST anti-quantum cryptography standard algorithm. By means of the method, efficient integration of compression, encryption and watermark embedding can be achieved, and the overall performance can be improved to the maximum extent on the premise that the image quality is guaranteed.

The embodiment of the invention provides an electromechanical simulation environment construction method and device, computer equipment and a medium, and the method comprises the following steps: generating a configuration description file, and programming the configuration description file to an embedded computer; obtaining core algorithm data, packaging the core algorithm data, transmitting the packaged core algorithm data to the embedded computer, and obtaining standard algorithm data and programming the standard algorithm data to the embedded computer; the excitation system is connected with an airborne software interface protocol through the Ethernet, and the embedded computer is connected with the excitation system through the Ethernet; bus data are transmitted to an embedded computer through an excitation system by means of an airborne software interface protocol; and receiving a simulation instruction from the excitation system through a debugging signal interface device of the embedded computer, and sending state simulation result data generated by the embedded computer to the excitation system. According to the scheme, the electromechanical simulation environment is constructed, so that the operation conditions of the electromechanical system under various flight conditions and system states are effectively simulated.

The application discloses a scheduling control method for automatic transmission clutch input rotating speed regulation, and comprises the following steps: 1, algorithm software receives signals; 2, identifying the running condition when the clutch input rotating speed needs to be regulated: the algorithm software identifies the current running condition according to the positive and negative values of the power source torque, the positive and negative changes of the power source torque value, whether the clutch input rotating speed needs to be up-regulated or down-regulated, and whether the clutch input rotating speed regulation needs to cross the current shaft rotating speed; 3, reading the preset configuration: the algorithm software will be pre-configured with the standard algorithm selected according to all the conditions in step 2, and all the configurations will be read in this step; 4, according to the condition identified in step 2, the standard algorithm used is calculated by using the configuration in step 3, and then the standard algorithm in the standard library is called to regulate the speed. The application realizes the decoupling of the running condition control and the speed regulation algorithm when the clutch input rotating speed needs to be regulated.

The invention relates to the technical field of artificial intelligence and engineering project management, and particularly discloses a project group performance intelligent assessment method and device. The method is especially suitable for a project group management scene, and examination work is carried out from multiple dimensions of task completion, organization coordination, cross-project collaboration, research, development, innovation and the like. The method comprises the following steps: acquiring three types of basic data including characters, images and structured data; semantic decoding is carried out through a large language model, image recognition is carried out through a convolutional neural network, structured data is processed through a standardized algorithm, and multi-source data preprocessing is achieved; extracting static features based on a multi-layer sensing network, and extracting dynamic time sequence features based on a long short-term memory network; and a big language model is utilized to generate an interpretive performance comment, and finally a comprehensive assessment report is output. The system is fused with a multi-mode AI model, has high scoring accuracy and high interpretability, and is particularly suitable for intelligent performance evaluation under a multi-project collaborative management situation.

The application discloses a fuel dispenser data security encryption transmission management system and relates to the field of data transmission management, which is used to solve the problem that the dynamic change of security priority and performance priority leads to frequent priority change, reduces data security and transmission efficiency, and causes waste of computing resources. The system classifies users according to the carrying capacity of the user's vehicle tank and the user interaction frequency, collects the mean value of the fuel dispenser transmission data, the mean value of the transmission rate, the data security transmission probability and the similarity between the transmission data and the original data of different categories of users, sets the fuel dispenser simple algorithm and the fuel dispenser standard algorithm, determines the security algorithm matched by different types of users, and then performs user allocation prediction analysis through a time series model to dynamically adjust the standard user allocation, improve the efficiency of data transmission, enhance the security of data transmission and reduce the delay during the peak period.

This paper proposes a baseline-length-constrained high-precision relative positioning method for BeiDou, comprising the following steps: First, establishing a double-difference relative positioning model using the pseudorange and carrier phase raw observations of the reference station and the rover station; Second, obtaining a strictly baseline-length-constrained objective function based on the double-difference relative positioning model according to the least squares criterion; Third, employing an integer ambiguity search space amplification strategy to achieve effective ambiguity search, and accurately estimating the rover station's position relative to the reference station. This invention utilizes the often underutilized baseline length information of dual antennas in real-world scenarios to improve the relative positioning solution performance, exhibiting higher reliability compared to the traditional unconstrained case. The method employs an integer ambiguity search space amplification strategy, thereby extending the standard LAMBDA algorithm to baseline-length-constrained relative positioning, achieving effective integer ambiguity search.

The application provides a diffusion model driven image three-dimensional reconstruction method, system and medium, the method comprising: acquiring an input RGB image, generating a multi-view image consistent with the input RGB image based on a conditional diffusion model; extracting a dense point cloud from the multi-view image based on a standard MVS algorithm, preprocessing the dense point cloud to obtain a preprocessed dense point cloud; spatially projecting any two images of different views based on the preprocessed dense point cloud to obtain projection coordinates; constructing a geometric consistency loss function, analyzing the projection coordinates based on the geometric consistency loss function, and calculating the projection error of different views; correcting the projection coordinates to obtain a reconstructed image; by generating consistent multi-view images, combining the standard MVS algorithm to obtain accurate point cloud data, and further introducing a geometric consistency loss function to constrain the three-dimensional projection logic between generated images, the modeling accuracy and stability are significantly improved.

The invention relates to the technical field of data processing, in particular to an intelligent storage method for gas chromatography detection data, which comprises the following steps of: dividing data points into different categories according to a clustering result of a K-means algorithm on the gas chromatography data points, analyzing an average chromatogram of each category, and judging category components of the average chromatogram; and according to the obtained category components, adding corresponding category labels to different category data points, and based on the category components, dynamically managing the storage data of each category data point. The invention provides an improved distance measurement method aiming at the problem of neglect of scale sensitivity and peak shape similarity of Euclidean distance measurement in gas chromatography data classification application of a standard K-means algorithm, so that characteristic value difference and peak shape similarity can be comprehensively considered; therefore, the capability of distinguishing different types of signals in the gas chromatographic data, especially peaks with similar shapes and large amplitude difference, is improved, and more intelligent data classified storage is realized.

The present application relates to the technical field of energy storage, and provides a three-phase active power independent configuration method for a converter based on a minimum norm solution, constructs the correlation between three-phase current and voltage, establishes a linear equation set according to the KCL current constraint condition and the correlation, solves the linear equation set through a minimum norm solution standard algorithm, generates three-phase current sine reference values based on the output angle of a grid phase-locked loop, separates positive and negative sequence components through a signal delay method, obtains positive and negative sequence voltages by using a double-current loop feedforward decoupling control algorithm, generates voltage values through Park inverse transformation, generates PWM signals to drive the conduction or turn-off of converter power switching tubes according to the voltage values, and outputs three-phase voltages. The present application realizes independent and flexible configuration of three-phase active power and automatic minimization of reactive power, guarantees the real-time performance of control and engineering compatibility, adapts to complex scenarios such as distributed energy access and unbalanced load compensation, and improves the stability of power grid operation and energy utilization efficiency.

The invention discloses a computer system encryption method for software development, which comprises the following steps of: 1, realizing the functions of large number storage and basic arithmetic operation based on an RSA (Rivest-Shamir-Adleman) algorithm; step 2, performing power modular operation and multiply modular operation, wherein an operation mode of the multiply modular operation adopts M (A * B); the method comprises the following steps: step 1, carrying out prime number screening and Fermat prime number testing, step 2, carrying out prime number testing on a number which may be a prime number, calculating a secret key, and carrying out encryption operation, step 3, carrying out prime number screening and Fermat prime number testing, and step 4, carrying out prime number testing on the number which may be the prime number. 5, the functions of RSA key generation and encryption and decryption are achieved, and the encryption and decryption processes are standard RSA algorithms; 6, secret key generation testing, system performance analysis and improvement optimization are carried out; compared with the prior art, the method has the advantages that the asymmetric key is applied to encrypt any file, so that the application of the asymmetric key is not limited to the internet, the data after asymmetric encryption is converted into the text, any file can be safely transmitted in almost any mode, and the asymmetric key is generated according to the required digit.

The application relates to the field of encrypted data collaborative processing, and discloses a privacy protection-oriented encrypted data collaborative processing system and method, wherein the privacy protection-oriented encrypted data collaborative processing method comprises the following steps: converting clear data of each subject into cipher text through secure multi-party computation, and accessing a system through a trusted execution environment; performing parallel computation on the cipher text data through a privacy computation special acceleration chip of a Chiplet architecture; combining a chip and a software platform to integrate a national encryption algorithm, an international standard algorithm and a federal learning framework, and constructing a cipher text computation processing environment; uniformly scheduling chip and memory resources through a privacy computation all-in-one machine server, forming a cipher text computation resource pool; homomorphically decrypting the computation result, and outputting the decrypted data to a user through a unified operation interface and a data flow circulation platform to generate a decrypted structured data set. The application has the advantages of improving computation efficiency and reducing operation cost.

The invention provides a model-driven algorithm test method and system, a computer and a storage medium, and the method comprises the following steps: carrying out the standardization processing of a non-standard algorithm demand, and generating a structured algorithm demand document; based on the standardized algorithm requirement document, utilizing a large language model to generate test data information meeting the test sufficiency requirement; analyzing an algorithm source code structure corresponding to the algorithm demand, and constructing a meta-model of the measured algorithm; loading the meta-model of the measured algorithm, importing test data information, completing transformation from the meta-model to an instantiated test model, and forming a test case set; converting the test case set into executable test scripts in batches based on an extensible style sheet conversion language template; and executing the test script in the algorithm test engine. Through the model driving test technology and the algorithm test engine, automatic verification of the test case is completed, and the test result is collected, so that the intelligence and automation level of algorithm test is effectively improved.

The invention discloses an unconventional oil and gas well production index library construction method, device and equipment and a medium. The invention relates to the technical field of unconventional oil gas. The method comprises the steps that mine production data and mine engineering data of a target oil and gas well are obtained; for each target oil and gas well, determining an instantaneous dynamic index, an accumulated dynamic index and a derived dynamic index corresponding to the target oil and gas well according to the mine production data and the mine engineering data on the basis of a preset standard algorithm and a pre-constructed production index moment; according to the instantaneous dynamic index, the accumulated dynamic index and the derived dynamic index corresponding to the target oil and gas well, a production index matrix corresponding to the target oil and gas well is determined, and an unconventional oil and gas well production index library is constructed according to all the production index matrixes; a uniform oil and gas well production dynamic index system can provide a consistent data basis for big data analysis, scientific support is provided for efficient development of unconventional oil and gas resources, and sustainable development of the energy industry is promoted.

The invention belongs to the technical field of aviation maintenance management, and discloses an airplane regular maintenance dispatching method, system and device, and the method comprises the steps: carrying out the staged processing of a maintenance task; dynamic construction of maintenance worker features; performing intelligent dispatching calculation; task execution and feedback: dynamically constructing maintenance worker portraits including authorization, work types, belonging areas, work content preferences and stage preferences, and combining with an improved weighted distribution algorithm to realize task matching, so that accurate adaptation of maintenance worker qualification, areas and task requirements is ensured; the method is advantaged in that the work content preference value and the stage preference value are utilized to improve the matching degree of the personnel and the task, the rework rate caused by mismatching of the personnel and the task is reduced, a traditional dispatching mode depending on artificial experience is converted into a standardized algorithm, dispatching efficiency fluctuation caused by empirical personnel loss is avoided, and enterprise high-salary talent retention cost is reduced.

This invention relates to the field of online power metering monitoring technology. It discloses a CVT error calculation method, device, and storage medium based on a virtual standard algorithm. The CVT error calculation method includes: real-time acquisition of raw voltage waveform data from multiple CVTs under the same source state, and calculation of their amplitude and phase; construction of a steady-state data set; calculation of an initial virtual standard; calculation of the initial voltage ratio difference and initial voltage angle difference; inversion of the real-time virtual standard; calculation of the overall virtual standard; calculation of the instantaneous voltage ratio difference and instantaneous voltage angle difference; and output of the CVT status judgment result. This method effectively improves the accuracy of CVT error calculation, enables more precise judgment of transformer status, and provides strong support for the stable operation of the power system.

The invention relates to the field of data management systems, and discloses a system for oil static metering calculation, data management and inventory checking, which comprises a data access and preprocessing module which can receive liquid level height, temperature and density original data transmitted by float-type, ultrasonic-type, radar-type and other external acquisition equipment through industrial communication protocols such as Modbus, 485 bus and the like. GB / T1885-1998 and GB / T19779-2005 national standard algorithms and API American standard algorithms are built in the system, calculation standards can be switched according to needs, a temperature compensation algorithm can be automatically adapted according to oil types, national metering specifications are strictly followed, personal errors caused by manual calculation are avoided, meanwhile, outrange data can be intercepted through a data validity verification function, abnormal data do not participate in calculation, and the system is high in reliability and high in reliability. It is ensured that the metering result is accurate and meets the industrial compliance requirement, and the problems that traditional manual measurement is limited in accuracy and not uniform in standard are solved.

The application provides a FFT acceleration and MIMO-OFDM four-dimensional sensing method with off-grid refinement, and belongs to the technical field of integrated sensing and communication. In order to solve the problems that the standard OMP algorithm has too large joint estimation calculation complexity in MIMO-OFDM echo sensing, and the estimation accuracy is limited to a grid, the steps of the application include the following steps: S1, OFDM echo preprocessing; S2, initializing an iteration control quantity; S3, performing fast dictionary matching to obtain an initial coarse estimation value; S4, refining the estimation value; S5, eliminating a residual error; S6, judging whether an iteration stopping condition is met; if the iteration is stopped, S7 is executed; otherwise, S3 is executed; and S7, outputting a four-dimensional sensing result.

The application provides a tunnel surrounding rock dynamic grading and early warning method and related equipment, through integration of two types of core data sources of static basic data and dynamic monitoring data, overall coverage of geological information is realized; with the aid of the space-time correlation binding mechanism of mileage coordinates and time stamps, the information barrier between static data and dynamic data is broken, ensuring accurate correspondence of different dimension data in spatial position and time dimension, providing a unified data basis for subsequent grading calculation; based on the dynamic weight distribution mechanism of the construction stage, the grading calculation can adapt to the geological characteristics in different periods of tunnel construction, the dynamic update of the quality grade of each tunnel segment surrounding rock is realized through the preset grading standard algorithm, the technical difficulty that the traditional fixed weight grading method cannot adapt to the dynamic evolution of surrounding rock in the whole construction process is solved, and the timeliness and accuracy of surrounding rock grading are significantly improved.

The application provides a model-driven algorithm test method, system, computer and storage medium, which comprises the following steps: normalizing non-standard algorithm requirements to generate a structured algorithm requirement document; based on the normalized algorithm requirement document, using a large language model to generate test data information meeting the test sufficiency requirement; parsing the algorithm source code structure corresponding to the algorithm requirement to construct a meta-model of the algorithm under test; loading the meta-model of the algorithm under test and importing the test data information to complete the conversion from the meta-model to an instantiated test model, forming a test case set; based on an extensible stylesheet transformation language template, batch converting the test case set into an executable test script; and executing the test script in an algorithm test engine. Through the model-driven test technology and the algorithm test engine, the automatic verification of the test case is completed and the test result is collected, thereby effectively improving the intelligentization and automation level of the algorithm test.