18 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 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 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 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 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 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 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.

The embodiment of the invention provides a numerical value matching method and device, computer equipment and a medium, and relates to the field of computer algorithms, and the method comprises the following steps: based on a data matching table, carrying out binary coding on each first matching numerical value and a corresponding second matching numerical value in the data matching table to generate a coding numerical value, a plurality of coding values are obtained; sorting the plurality of coding numerical values and then storing the coding numerical values in a data structure of a memory; in a numerical value matching process, receiving a to-be-matched first matching numerical value, and searching a coding numerical value associated with the to-be-matched first matching numerical value in the data structure; and extracting a second matching numerical value corresponding to the to-be-matched first matching numerical value from the searched coding numerical values. According to the scheme, the problem that a large amount of memory is occupied due to direct storage of the data matching table is solved.