33 results about "Computer algorithm" patented technology

The invention relates to the technical field of power system stability constraint optimization and computer algorithms, and provides an energy storage fault ride-through optimization method considering optical storage access weak power grid stability constraint, which comprises the following steps: collecting power grid operation data to generate a dynamic enhancement data set; constructing and correcting a digital twinborn body on line; generating a guide vector field and initializing an optimization framework; executing hybrid iteration to generate a candidate strategy; an optimization process is fed back through simulation evaluation; verifying a decision output control instruction after convergence; and deploying an instruction and realizing online updating. According to the method, the characteristics of the power grid are accurately modeled by using the digital twin, optimization search is guided in combination with the guide vector field, the non-convex optimization problem caused by stability constraints is effectively processed through a hybrid iteration strategy, and the voltage and frequency recovery capability in the fault ride-through process is improved.

The invention relates to the field of computer algorithms and material engineering, in particular to a two-phase titanium alloy grain level stress prediction method based on GCN-LSTM. Firstly, a GCN module is used for extracting high-dimensional spatial features from crystal grain nodes and connection relations thereof; then, an LSTM module is adopted to carry out time sequence modeling on grain stress data which are preprocessed and spliced into a time sequence, and the hidden state of the last time step of the sequence serves as a dynamic feature; and then fusing the features of the two parts element by element, and mapping the fused features into a grain-level stress prediction value through a full connection layer. The stress data predicted for microstructures of different texture types are reversely reconstructed into a three-dimensional visual image which is highly consistent with a crystal plasticity finite element calculation result, the method has a remarkable advantage in calculation speed, and more accurate local information is provided at the same time. The method provides efficient and accurate technical support for microstructure design, alloy performance and preparation process optimization and structural safety evaluation of materials such as titanium alloy.

The present invention relates to a plain region wind turbine arrangement method based on a Web application system, comprising the following steps: (1) determining a prevailing wind direction; (2) setting parameters; (3) determining the position of a first wind turbine; (4) carrying out quincunx arrangement; and (5) completing the arrangement of wind turbines in the whole region. In the present invention, a computer algorithm and GIS technology are used, so that a large amount of terrain data can be processed and analyzed, and a region with high wind speed and stable wind flow can be rapidly recognized to determine an optimal arrangement position for wind turbine arrangement, thereby significantly improving the efficiency and quality of wind turbine arrangement.

The invention discloses a computer algorithm visualization teaching generation system based on a large model, and relates to the technical field of artificial intelligence-driven education. The work content of the system comprises the following steps: constructing a mapping relationship between algorithm categories and features, generating an understandable feature set, and labeling difficulty levels; guiding a user to select an algorithm category and program a basic label through a graphical algorithm classification graph; k rounds of dynamic questions and answers are adopted, questioning features are screened based on an information entropy gain ratio, and answer vectors are constructed in combination with user answers; through cosine similarity matching algorithm feature vectors, teaching content is recommended, difficulty is adjusted, or non-questioning features are supplemented and inquired; and converting the user data into a natural language text, calling a preset large model interface to generate a learning suggestion, and performing interactive visual display. According to the system, a whole-process closed loop of algorithm teaching from data acquisition and preprocessing to dynamic generation and personalized recommendation is realized, and the teaching precision and efficiency are improved.

The invention discloses a design system for automatically generating a fallen leaf sculpture based on computer algorithm logic, and relates to the technical field of fallen leaf sculpture design systems. Comprising a data acquisition and analysis module which collects fallen leaf information and environment information based on image acquisition and analysis; the intelligent interaction module is used for acquiring requirements of a user based on interaction with the user; the design generation module is used for generating a design scheme according to the requirements of the user; and the automatic scoring module is used for scoring according to the generated design scheme. The intelligent interaction module is combined with natural language processing and image recognition technologies, user requirements can be deeply understood, text description or image input can be converted into specific design parameters, the user participation degree and the design precision are improved, the design generation module utilizes a mathematical model and an algorithm, and the design efficiency is improved. And a fallen leaf sculpture design scheme meeting user requirements is automatically generated.

The invention provides a pipeline transaction bilateral contract matching method and system, belongs to the field of crossing of metering economics and computer algorithms, and is used for solving the problems of multi-parameter coupling, high research and development uncertainty and low matching efficiency of pipeline transaction contracts in related technologies. A core term is converted into a tensor model, a Markov chain is combined to quantify expected utility, multi-round intelligent matching is realized based on a fuzzy satisfaction function and a sub-scene convex optimization algorithm, a key parameter dynamic calibration mechanism is matched, a complete technical closed loop is formed, the matching accuracy and negotiation efficiency are objectively improved, and the negotiation efficiency is improved. And reliable technical support is provided for complex pipeline transactions.

The present invention relates to the technical field of computer algorithms, and particularly to a coprocessor for the replacement process in a data fusion algorithm based on an auction algorithm. The coprocessor includes a coprocessor, and the internal circuit of the coprocessor contains a control logic and a computing unit. The control logic unit is used to control the data flow control of the entire computing unit and the data reading and writing with the storage cache. The computing unit is responsible for calculating a pair of data transmitted from a custom instruction, comparing whether the values read from two storage caches are the same, and sending the comparison result to the control logic. For an algorithm with repeated and regular operation steps, implementing it using a finite state machine saves a large amount of time compared to implementing it using a processor. At the same time, through reasonable design, the two data retrievals and comparisons of each group of numbers are synchronized, and optimization is carried out at the algorithm level, doubling the efficiency. By utilizing the characteristics of a dual-port cache, a direct interaction method between the peripheral device and the coprocessor is achieved, rather than accessing the on-chip storage through an ROCC interface.

This invention discloses an adaptive neurofuzzy system for diabetes analysis and integration, comprising the following steps: S1: inputting the dataset into a CIR-ANFIS model, where the model first standardizes the dataset; S2: calculating the causal coefficient corresponding to the prediction result for each feature using causal inference, and using this coefficient as the feature weight; S3: randomly selecting multiple different subsets, constructing an adaptive fuzzy inference system for each subset, and obtaining the prediction result of each inference system; S4: obtaining the prediction result of the entire model through ensemble learning. This invention relates to the field of computer algorithm technology. The beneficial effect of this invention is that by introducing causal inference into feature selection and using causal coefficients as weights to randomly generate data subsets for training, the model training cost is reduced, and better model performance is achieved.

The invention relates to a smooth dimming method, a controller and a uniform dimming system. The method comprises the following steps: when dimming is needed step by step, calculating the difference between the accumulated dimming quantity of the first n steps and the accumulated dimming quantity of the first (n-1) steps, and determining the dimming increment of the nth step; wherein the accumulated dimming quantity of the first n steps is an accumulation result of the dimming increment from the first step of the initial step to the current nth step, and n is greater than 1. And dimming according to the dimming increment of each step, so that the lamp smoothly and gradually changes to reach the target brightness. According to the method, the value participating in operation is amplified, so that the step value of dimming in each step is not fixed, the precision error caused by integer division and rounding in a computer algorithm is eliminated, accurate tracking with an ideal value is kept, real smooth dimming is realized, and the user experience is improved.

The invention relates to the technical field of computer algorithms, in particular to an agrochemical scene-oriented three-dimensional boxing optimization method and system, which comprises a data input and preprocessing module, an initial scheme generation module, an initial scheme generation module, a final scheme generation module, a final scheme generation module, a final scheme generation module and a final scheme generation module, wherein the data input and preprocessing module is responsible for receiving a container size and a list of articles to be boxed; a feasible reference boxing scheme is quickly generated; the genetic algorithm optimization module is the core of the system and is responsible for carrying out iterative optimization on the packing sequence of the articles so as to find the optimal arrangement, and the scheme output module is used for presenting the optimal scheme in the forms of data, statistical reports and three-dimensional visualization. According to the method, the space utilization rate is remarkably improved, the non-visual and more compact article arrangement sequence can be found through the global search capability of the genetic algorithm, space debris generated due to the improper placement sequence is effectively reduced, and compared with a traditional greedy algorithm, the space utilization rate is greatly improved.

The invention belongs to the technical field of computer algorithms, and discloses a target state identification and judgment method based on deep learning, and the method comprises the following specific steps: 1, collecting and manufacturing data needed by an open-source basic model according to the needs, and training a self-defined model needed by a user through opencv (computer vision technology); through the judgment of the system, a series of behaviors are carried out, the manpower consumption and the requirement for computing resources are reduced, so that the cost is reduced, the possibility of considering manual and machine judgment is more comprehensive, the situation of misjudgment caused by energy reduction is avoided, the generalization ability of the model is ensured, and the method is suitable for large-scale popularization and application. And meanwhile, the automation technology can also ensure the real-time performance of the data, and subsequent single-person operation can be performed, so that the privacy of the target user can be further ensured, the data leakage is prevented, and the data is safer.

The energy-saving control system comprises a hardware layer and an algorithm layer, the hardware layer comprises executing mechanisms such as a compressor unit, an evaporator and a condenser, a sensor module and a PLC, and the algorithm layer comprises an upper computer algorithm module; according to the energy-saving control method, system operation data are collected through the sensor module and input into the upper computer algorithm module after being preprocessed, local agent decision making is achieved through multi-agent reinforcement learning MARL, global collaborative optimization is completed in combination with a collaborative genetic algorithm CGA, decision consistency is guaranteed through conflict detection and a coordination mechanism, and energy-saving control is achieved. And finally, the PLC controller executes the control instruction and realizes closed-loop feedback updating. The temperature stability, the energy efficiency ratio and the equipment reliability are comprehensively considered, global optimal control is achieved, energy consumption is effectively reduced, the overall operation efficiency of the refrigeration house group is improved, and the method is suitable for the fields of food, medicine, industrial cold chain storage and transportation and the like.

The present invention discloses a method for automatically printing nameplates without vehicle allocation during PDI based on computer algorithms, which relates to the technical fields of industrial automation and information processing. The method includes: S1, collecting and transmitting PDI inspection information to a central processing system in real time based on the vehicle identification number; S2, the central processing system parsing and verifying the integrity and consistency of the received PDI inspection information; S3, updating the vehicle status based on the verification result and synchronizing it to the nameplate printing terminal; S4, generating and executing a nameplate printing instruction according to the synchronized vehicle status. This method for automatically printing nameplates without vehicle allocation during PDI based on computer algorithms improves the overall reliability and stability of the production line, forms a complete process closed-loop, facilitates tracing and optimization of possible problems during the production process, provides data support for subsequent quality control and production management, and monitors and synchronizes the PDI inspection information flow in real time to solve the printing error problem caused by information delay.

The invention relates to the technical field of computer algorithms, in particular to a calculation method and system for solving a large-scale multi-objective optimization problem. According to the technical scheme, the method comprises the following steps that an initialized population meeting the problem solving requirement is generated according to input parameters, variables to be optimized of each individual in the population are anchor variables and anchor point variables instead of variable data needed for solving the problem, and the number of the variables is greatly smaller than the number of the variable data needed for solving the problem; when the problem of large-scale multi-objective optimization is solved, variable complex correlation can be better coped, optimization efficiency is improved, optimization precision and difficulty are flexibly controlled, visual and effective result display is provided, and the method has remarkable advantages in multiple aspects.

The invention discloses an efficient infrared small target detection method for a night inspection task of an unmanned aerial vehicle, and relates to the field of computer algorithms. The method comprises an infrared small target detection algorithm, a shuffling attention module and a loss function. The infrared small target detection algorithm is composed of a backbone network, a high-resolution feature pyramid and three different-scale detection heads, and layered detection is achieved through multi-scale feature extraction and fusion. The shuffling attention module adopts a double-branch parallel structure, enhances channel and spatial dimension key features, and inhibits background interference; a loss function is improved based on YOLO, area weight is introduced, CIOU loss and Gaussian similarity measurement are combined, and small target classification and positioning precision is optimized. The method can effectively solve the problems of sparse small target features, complex background interference and the like in the night infrared image, improves the detection precision and real-time performance, is suitable for unmanned aerial vehicle oil and gas pipeline night inspection, can accurately recognize suspicious targets such as personnel and vehicles, and provides technical support for pipeline safety operation and maintenance.

The invention provides a chip atomic clock performance optimization method and test system, and the method comprises the steps: starting a tested atomic clock, reading an internal preset parameter set of the atomic clock through an upper computer, and monitoring the working state of the tested atomic clock; after the atomic clock is locked, starting a frequency measurement module, and calculating frequency stability as a target function according to change; the upper computer remotely adjusts the working parameters of the measured atomic clock; basic variable parameter setting and detection data acquisition are completed through control variables; establishing an optimization model, and determining working parameters of the atomic clock at the working non-sensitive points; the upper computer outputs a remote working parameter to the tested atomic clock, further remotely adjusts a control parameter, constructs a control parameter frequency stability model, and determines an optimized control parameter; the stability of the atomic clock is optimized through an upper computer algorithm optimization platform, the stability of the measured atomic clock serves as an optimization target, and the performance index optimization efficiency of the atomic clock is improved by controlling iterative optimization of sensitive parameters.

The invention relates to a desk computer algorithm operating system. The system comprises a video capture device, a first enhancement device, a second enhancement device, a third enhancement device, a component identification mechanism and a numerical value analysis mechanism. The system can dynamically select a search range for searching a reference coding block when intra-frame coding is performed on the whole picture according to the complexity of component value distribution of a key target in the picture.

The present invention provides a computer-aided color matching pattern design method, device, storage medium and equipment, which realizes a design method of converting and calculating a plurality of reasonably selected organizational structures, warp and weft yarn arrangements and yarn colors from a pattern pattern through computer algorithms and applications, and then generates corresponding color matching pattern designs; the present invention changes the original many-to-one design thinking into a one-to-many restrictive design, greatly improves the success rate of color matching pattern design, improves design efficiency, greatly reduces design labor and time costs, and has more choices and greater room for development, and is more adaptable to the current market's requirements for small batches and multiple colors, which brings great benefits to fabric design. While maintaining stable development, the textile industry has taken the opportunity to increase design research and development and make good accumulation. The present invention will bring good news to design developers.

The application provides a computer algorithm processing method and device, and relates to the technical field of computers. The application utilizes the powerful semantic understanding and generation capability of a large model, combines retrieval enhancement generation, code generation, test configuration generation, cloud computing, automated testing and intelligent correction technology, and through a large model related to retrieval enhancement generation, unified expression, intelligent interface mapping and adaptive program generation, standardized test configuration generation, intelligent test feedback and correction, realizes an end-to-end automated process from algorithm original description materials including multi-source original data and algorithm text description documents to adaptive codes running efficiently and stably on a target cloud platform, significantly reduces the complexity, error rate and time cost of algorithm integration, deployment and operation, and has low dependence on manpower.

Systems, methods, and computer algorithms disclosed herein enable dynamic adjustment of data structures in data sources used for Artificial Intelligence (AI) assisted data analytics, especially when Natural Language Processing (NLP) is used. This method includes a dynamic creation of attribute fields, definition of their names, and content based on existing datasets. Such transformation of the underlying data aims to enhance performance of NLP-based data processing by making it better match human language.

The invention discloses a double-inductance circularly polarized antenna design method based on an implicit particle swarm algorithm, and belongs to the crossing field of a radio frequency front end of a wireless communication system and a computer algorithm. In the antenna design process, structural parameters are used as position initialization of a solution space, an initial group is divided into a group A and a group B, the speed of the group A is updated, the position of the group A is updated according to the speed of the group A, and global search is carried out. And for the other half group B, perturbation is carried out on the positions of the group B near the global optimal position, and local optimal search is carried out. After the number of times of iteration specified by hidden generation is reached, executing hidden generation operation, randomly replacing the random dimension of a quarter particle in the group A with the corresponding dimension of the historical optimal position, updating the globally optimal solution and the globally optimal position, stopping updating at the set maximum number of times of iteration, and returning to the optimal solution. A better optimization effect can be achieved in a shorter number of iterations, and local optimum in an antenna design process is avoided.

A method and system for controlling the state of stress in deposited thin films are disclosed. According to the method and system, various process parameters, including: process pressure; substrate temperature; deposition rate; and ion-beam energies (controlled via the ion beam current, voltage, signal frequency and duty cycle) are varied using a step-by-step methodology to arrive at a pre-determined desired state of stress in thin films deposited using PVD. The method may be expressed as a computer algorithm, whereby the step-by-step procedure to obtain a pre-determined stress state, is coded for more efficient development and control of deposition processes. Alternatively, a closed-loop controlled PVD deposition system allows a pre-determined stress state of a thin film to be obtained quickly and efficiency using a feedback loop, algorithm and one or more sensors to monitor the substrate thin film stress and various process tool parameters.

The invention discloses a mechanical arm motion trail simulation verification method based on a virtual scene, relates to the technical field of simulation verification, and solves the problems that in the prior art, visual experience of actual operation is lacked, and corresponding training and evaluation methods are time-consuming and not objective enough. According to the invention, a virtual scene and a computer algorithm are utilized, an efficient, objective and low-cost training scheme is provided for a mechanical arm operator, and the limitation of traditional training is solved. According to the virtual scene designed by the invention, a complex working scene can be quickly generated, personalized training is supported, and the adaptability and the strain capacity of operators are improved. In terms of evaluation, a traditional mode is high in subjectivity and lacks uniformity. The similarity is obtained by comparing the motion path with the standard path, the evaluation coefficient is generated by combining the collision condition and the like, and the method is objective and accurate on the basis of data. According to the method, the debugging risk of the mechanical arm can be remarkably reduced, the trajectory planning efficiency and reliability are improved, and the method is particularly suitable for high-precision or high-risk scenes.

The present application relates to the technical field of computer algorithm field, especially to a kind of mass spectrum peak detection analysis method and its device.The mass spectrum peak detection analysis method specifically includes the following steps: step S1: mass spectrum data is regarded as three-dimensional point cloud, and mass spectrum data is divided into window;Step S2: point cloud data extraction is carried out in each window area, and point cloud data is pretreated;Step S3: the point cloud data after pretreatment is analyzed based on the end-to-end multi-task network of deep learning.By the present application, 3D analysis of mass spectrum data can be realized, and the accuracy of mass spectrum peak quantitative analysis can be effectively guaranteed.

The application discloses an automatic calculation method for hydraulic balance of a heating pipeline. The method comprises the following steps: automatically extracting the connection relationship, length and load of a pipe section in a heating system diagram; calculating flow and flow velocity, and initially selecting a pipe diameter of each pipe section from a database according to a preset flow velocity range; identifying a most unfavorable loop based on topological analysis, and determining the final pipe diameter of each pipe section of the loop by optimization with the closest preset economic specific friction resistance as a target, and calculating the total resistance of the loop; taking the total resistance as a benchmark to calculate the average specific friction resistance of the remaining parallel loops, and determining the final pipe diameter of each pipe section of the loops according to the average specific friction resistance; and finally calculating the imbalance rate of all parallel loops, and outputting the hydraulic calculation results containing the final pipe diameter, resistance and total resistance of the system. The application realizes full-process automation from a design drawing to hydraulic calculation and optimization design, deeply integrates classical fluid mechanics theory, design specifications and computer algorithms, and can efficiently and accurately guarantee the hydraulic balance of a heating system at a design source.

The application relates to a high-speed consensus method based on a blockchain, which sequentially comprises a Request stage, a Pre-prepare stage, a Prepare stage, a Commit stage and a Reply stage, the Pre-prepare stage and the Prepare stage are reconstructed, a master node puts a transaction into a cache pool; the master node polls a secondary node and selects an optimal secondary node; the master node generates a cache pool access token and sends the token to the optimal secondary node; the optimal secondary node finds the transaction in the cache pool by means of the cache pool access token; the optimal secondary node downloads the transaction, carries out transaction digest calculation, transaction digest comparison and comparison result broadcast work; after the optimal secondary node completes the work, the master node is replied, and the master node deletes the corresponding transaction in the cache pool; then, the next round of consensus is carried out. The computer algorithm power consumption and the network resource consumption of the stage are reduced, so that the time consumption of the stage can be reduced, the consensus performance of the blockchain can be improved, and the number of concurrent transactions of the blockchain can be improved.

The invention provides a computer algorithm processing method and device, and relates to the technical field of computers. According to the method, the powerful semantic comprehension and generation capability of a large model is utilized, and the technologies of retrieval enhancement generation, code generation, test configuration generation, cloud computing, automatic test and intelligent correction are combined; through retrieval enhancement generation, unified expression, intelligent interface mapping and adaptive program generation, standardized test configuration generation, and intelligent test feedback and correction related large models, algorithm original description materials including multi-source original data and algorithm text description documents are converted into multi-source original data and algorithm text description documents. Through the end-to-end automatic process of the adaptive codes efficiently and stably running on the target cloud platform, the complexity, the error rate and the time cost of algorithm integration, deployment and operation and maintenance are remarkably reduced, and the degree of dependence on manpower is low.

The application relates to a quality evaluation method and device of image / video data, and relates to the technical field of image quality evaluation. The method comprises the following steps: receiving a media file to be evaluated; obtaining an objective score corresponding to the media file to be evaluated; inputting the media file to be evaluated and the objective score into a target evaluation model which has been trained, to obtain a subjective score corresponding to the media file to be evaluated; the target evaluation model is obtained by training an evaluation model according to sample media files, subjective scores of the sample media files and objective scores of the sample media files; the target evaluation model outputs a corresponding subjective score based on the input media file; the subjective score refers to the score of image quality given by a human observer; the objective score refers to the score of image quality given by a computer algorithm; and the subjective score is output. The application can meet the evaluation requirements of large scale and automation.

The invention relates to a computer device. The computer device comprises a memory, a processor and an intelligent parsing computer algorithm operating system. The computer device is intelligent in control and reliable in operation.