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Algorithm design is a specific method to create a mathematical process in solving problems. Applied algorithm design is algorithm engineering. Algorithm design is identified and incorporated into many solution theories of operation research, such as dynamic programming and divide-and-conquer. Techniques for designing and implementing algorithm designs are algorithm design patterns, such as template method pattern and decorator pattern, and uses of data structures, and name and sort lists. Some current day uses of algorithm design can be found in internet retrieval processes of web crawling, packet routing and caching. Mainframe programming languages such as ALGOL, FORTRAN, COBOL, PL/I, SAIL, and SNOBOL are computing tools to implement an "algorithm design"... but, an "algorithm design" is not a language. An a/d can be a hand written process, e.g. set of equations, a series of mechanical processes done by hand, an analog piece of equipment, or a digital process and/or processor. One of the most important aspects of algorithm design is creating an algorithm that has an efficient run time, also known as its big Oh. Steps in development of Algorithms Problem definition
Recommendation algorithm design based on big data in e-commerce platform
InactiveCN119398866AImprove shopping experienceCommerceOther databases clustering/classificationData compressionPersonalization
The invention belongs to the technical field of e-commerce, and particularly relates to a big data-based recommendation algorithm design in an e-commerce platform, which comprises the following steps: completing data preprocessing based on data collection and preprocessing; constructing user portraits to generate personalized user portraits, and classifying the users by using a clustering algorithm to find group features of the users; analyzing the user similarity and the commodity similarity, and calculating the similarity between the users; carrying out user-based collaborative filtering and article-based collaborative filtering, and carrying out dimensionality reduction processing on user and commodity features by using an SVD or latent semantic model; modeling user behaviors by using a neural network, and performing data compression and feature extraction by using an auto-encoder; the user feedback data is collected for continuous optimization and iteration of the model, and online learning and A / B test are adopted to adjust the recommendation strategy, so that the method has the effects of realizing more accurate and personalized commodity recommendation, and improving the shopping experience of the user and the sales conversion rate of the platform.
Owner:HUBEI OIN NETWORK TECHNOLOGY CO LTD
Solid state disk power consumption optimization method and system based on load prediction
ActiveCN120610668AInput/output to record carriersHardware monitoringControl engineeringReinforcement learning algorithm
The invention discloses a load prediction-based solid state disk power consumption optimization method and system, and particularly relates to the technical field of solid state disks, and the method comprises the following steps: S1, data acquisition; s2, constructing and training a load prediction model; s3, load prediction; s4, power consumption optimization: optimizing the power consumption of the solid state disk by adopting a multi-objective optimized dynamic power consumption adjustment algorithm according to a load prediction result; and S5, feedback adjustment: monitoring actual power consumption and performance parameters of the solid state disk after optimization in real time, and adjusting the load prediction model and the dynamic power consumption adjustment algorithm in combination with a reinforcement learning algorithm. According to the solid state disk power consumption optimization method and system based on load prediction, a set of complete and efficient solid state disk power consumption optimization scheme is formed from load prediction model construction, dynamic power consumption adjustment algorithm design and feedback adjustment mechanism optimization; and a new technical thought and a new practice direction are expected to be provided for reducing energy consumption and improving performance of the solid state disk.
Owner:SHENZHEN QUANTIAN TECH CO LTD
Nuclear power enclosed bus intelligent monitoring model based on big data
The invention relates to a nuclear power enclosed bus intelligent monitoring model based on big data. The model specifically comprises a plurality of technical links such as data acquisition, cleaning preprocessing, feature extraction and selection, modeling and algorithm design, health condition evaluation and monitoring and the like. The intelligent monitoring module designed by the invention realizes comprehensive, real-time and intelligent monitoring of the operation state of the enclosed bus through integrating a plurality of links such as data acquisition, cleaning, feature extraction, modeling prediction and the like; real-time monitoring and early warning functions are realized by combining an Internet of Things technology and a cloud computing platform; a user is helped to quickly know the equipment state and make a scientific and reasonable operation and maintenance decision through display and decision support functions; potential faults are found in time through comprehensive monitoring and intelligent evaluation of the operation state of the enclosed bus, and effective measures are taken for processing, so that the safety and reliability of equipment are enhanced, and long-term stable operation of a nuclear power station is guaranteed; the intelligent monitoring model adopts a modular design and is easy to adapt to different monitoring requirements and scenes.
Owner:HEZE UNIV
Power load model parameter identification method based on improved deep reinforcement learning
PendingCN119129367Areduce biasImprove fitting accuracyData processing applicationsBiological modelsLoad modelSimulation
The invention discloses a power load model parameter identification method based on improved deep reinforcement learning, and belongs to the technical field of power load identification. The method comprises the following steps: determining a to-be-identified power load parameter based on a complete comprehensive load model considering power distribution network impedance and reactive compensation; then designing a power load parameter identification model based on a bidirectional gating cycle unit depth deterministic strategy gradient algorithm of priority experience playback; circuit data are collected for model training, and the trained model is used for parameter identification. On the basis of an existing power system mechanism model and a data driving model, the load model parameters are identified by improving the deep reinforcement learning model, and verification shows that the method can accurately identify the power system load model parameters, can improve the fitting precision of the power system load model, and has a good application prospect. The operation strategy of the power grid is optimized, and the operation cost is reduced.
Owner:CENT CHINA BRANCH OF STATE GRID CORP OF CHINA +1
Intelligent bid evaluation expert extraction and management system
PendingCN119597917Asave storage spaceadapt to diversitySemantic analysisBiological modelsData compressionTable (database)
The invention discloses an intelligent bid evaluation expert extraction and management system, and relates to the technical field of expert extraction systems. Comprising a data cleaning and compression module, a database logic and table relation design module, an expert information collection standard and automation module, an information real-time updating and principal management module, an extraction algorithm design module, a safety and authority management module and a real-time monitoring and auditing function module. Through a self-adaptive sparse auto-encoder and a dynamic clustering technology in the data cleaning and compression module, abnormal values in a bid evaluation expert database can be detected and cleaned, data compression is performed by adopting a self-adaptive dictionary coding algorithm, and the storage efficiency and query performance of the database are improved; based on a multi-modal information fusion and reinforcement learning method, accurate collection, dynamic updating and intelligent management of expert information are realized. The randomness and fairness of the bid evaluation expert extraction process are ensured by using a mode of combining deep reinforcement learning and a quantum random number generator in an extraction algorithm design module.
Owner:FUJIAN YILI ELECTRIC POWER TECH CO LTD
Flight ad hoc network distributed routing method based on multi-agent reinforcement learning
PendingCN119316336Aimprove performanceParticular environment based servicesVehicle-to-vehicle communicationEngineeringControl delay
The invention belongs to the field of unmanned aerial vehicle communication, and discloses a flight ad hoc network distributed routing method based on multi-agent reinforcement learning, and the method comprises the steps: building four network performance models: energy consumption, packet delivery rate, throughput and end-to-end time delay; establishing a node interaction mechanism; establishing a Markov decision process, defining definitions of a state space, an action space and a space state transition probability, and designing a reward function; based on an improved multi-agent depth deterministic policy gradient algorithm DE-MADDPG, designing a flight ad hoc network distributed routing method based on multi-agent reinforcement learning; each unmanned aerial vehicle modifies a running protocol and a protocol parameter according to local network information of each node, optimizes a main network and a subnetwork of the system, and improves the overall performance of the network. The method mainly solves the problems that a traditional flight ad hoc network protocol is not high in adaptive capacity, and the network environment is not matched with the protocol. Compared with a traditional method, the method has the advantages of being low in control delay, high in control precision and good in performance.
Owner:NANJING UNIV OF SCI & TECH +1
Modeling and compensating method for dynamic composite hysteresis of piezoelectric actuator under time-varying large load
ActiveCN119511731Aachieve compensationimplement the buildSustainable transportationAdaptive controlPiezoelectric actuatorsTime control
The invention belongs to the field of characteristic measurement of piezoelectric actuators, and relates to a modeling and compensating method for dynamic composite hysteresis of a piezoelectric actuator under a time-varying large load. A dynamic hysteresis characteristic test system of the piezoelectric actuator is built to collect load and displacement signals. Based on an improved asymmetric slope Prantl-Ishlinskii algorithm, carrying out modeling on asymmetry and zero drift characteristics of hysteresis rings, fitting static hysteresis rings of force-bit and electricity-bit, and superposing the static hysteresis rings to form a static composite hysteresis model; a dynamic composite hysteresis model is established according to the wide-frequency-domain excitation requirement of the driver, and an ASI parameter controller is designed based on an LSTM algorithm to dynamically regulate and control the slope and the threshold value of the model; a parameter controller fault-tolerant mechanism is designed to restrain model instability caused by sudden disturbance and control over-regulation, and high-precision real-time hysteresis prediction is ensured; and calculating the real-time control voltage and compensating the dynamic hysteresis by solving the inverse model of the dynamic composite hysteresis model and inputting the expected displacement.
Owner:DALIAN UNIV OF TECH
Automatic algorithm design method for solving vehicle path planning problem by using large language model
The invention relates to the field of automatic algorithm design, in particular to an automatic algorithm design method for solving a vehicle path planning problem by utilizing a large language model, which comprises the following steps of: S1, constructing an AutoDH framework, and defining a decision form of an intelligent agent; s2, defining heuristics in an LLM pool, an improvement pool and a disturbance pool; s3, acquiring state information of the CVRPs, and intelligently selecting a heuristic mode through two-stage MDP; s4, designing a reward mechanism fusing solution quality improvement, heuristic time cost and LLMs API calling cost; and S5, training the intelligent agent to optimize the solution of the CVRPs. The method can intelligently select the most cost-effective heuristic algorithm according to the state information of the current CVRPs, and improves the flexibility and adaptability of algorithm design.
Owner:NORTHWEST UNIV
Industrial control system safety protection algorithm design method
ActiveCN119576288Aprevent leakagePrevent tamperingError detection/correctionVersion controlAttackBusiness process
The invention provides a safety protection algorithm design method for an industrial control system, which is used for determining a safety protection target and range, determining a key component and a business process and defining a protection boundary. And then risk assessment and threat modeling are carried out, potential threat and attack vectors are identified, and asset vulnerability and risk influence are assessed. Designing a security protection algorithm framework, selecting proper security technology and algorithm, and determining architecture and module composition. Identity authentication modules, data encryption and integrity protection modules, intrusion detection and defense modules and the like are designed in detail, and authentication modes, key management modules, integrity verification modules, intrusion detection algorithms, response strategies and the like are designed. And then realizing and integrating an algorithm, and programming in the system to realize and guarantee the cooperative work among the modules. And the performance and the security of the algorithm are optimized through a function and security test. And finally, deploying the algorithm to the industrial control system, continuously monitoring the operation state and the security situation of the industrial control system, dynamically adjusting the strategy and parameters, and effectively guaranteeing the security of the industrial control system.
Owner:THREE GORGES INTELLIGENT CONTROL TECHNOLOGY CO LTD
Self-adaptive storage tank concentration quantification tracking control method for continuous stirring reaction kettle system
PendingCN119126553ASolve the problem of state constraintsGuaranteed normal operationAdaptive controlNeural network systemAutomatic control
The invention relates to the field of automatic control, in particular to a self-adaptive storage tank concentration quantitative tracking control method and device for a continuous stirring reaction kettle system. Firstly, a mechanism model of a continuous stirring reaction kettle system is established; converting the mechanism model into a state constrained non-strict feedback nonlinear system model; establishing a neural network system to carry out approximation on a nonlinear term and a coupling term in the state-constrained non-strict feedback nonlinear system model, and designing a virtual controller in combination with an adaptive adjustment algorithm; based on the virtual controller, designing an actual neural network adaptive quantization controller; based on the actual neural network, a controller is adaptively quantized, and a control signal is obtained; the control signal acts on the continuous stirring reaction kettle system, the expected storage tank concentration is tracked through the storage tank concentration output by the continuous stirring reaction kettle system, and the control target is achieved. According to the invention, good performance and stability can be provided during the operation period of the continuous stirring reaction kettle system.
Owner:JIANGNAN UNIV
Abnormity detection and response method and system based on intelligent perception driving
ActiveCN119544388ARespond quicklyReduce data dimensionalityBiological modelsSecuring communicationResponse processInformation security
The invention provides an anomaly detection and response method and system based on intelligent perception driving, and is particularly applied to cloud service information security monitoring. The method comprises the following steps: acquiring multi-type data in real time and fusing the multi-type data through Kalman filtering and weighted average; constructing a self-encoding network to carry out feature extraction and dimension reduction, detecting abnormity through a reconstruction error and setting a dynamic threshold value; a reinforcement learning optimization algorithm is introduced, a dynamic response strategy is designed, and a reward mechanism is defined, so that the response effect is improved; designing an automatic response process, including alarm, isolation and repair measures; migrating the optimized self-encoding network knowledge to a new scene by adopting a transfer learning technology; a cloud-edge collaborative architecture is constructed, and data are analyzed in a centralized manner and synchronized in real time. According to the method, the real-time performance and accuracy of information security monitoring are effectively improved, potential threats can be quickly responded, the security risk is reduced, and the method is suitable for various information security monitoring scenes.
Owner:CHINA JILIANG UNIV
Inverse fuzzy dynamic optimal self-adaptive aeration control method based on sewage treatment
ActiveCN119644755ASolve the problem of low control precisionSolve the acquisition problemSustainable biological treatmentAdaptive controlMulti objective optimization algorithmMunicipal sewage
The invention belongs to the field of urban sewage treatment, and provides an inverse fuzzy dynamic optimal self-adaptive aeration control method based on sewage treatment. Comprising the steps of dissolved oxygen concentration kinetic model construction, inverse fuzzy dynamic multi-objective optimization algorithm design, evaluation network and long-term utility function setting, execution network design, actual controller design, execution error function determination, execution network and actual controller parameter optimization and aeration pump control. According to the method, the optimal set value of the dissolved oxygen concentration is obtained through calculation of the inverse fuzzy dynamic multi-objective optimization algorithm; an execution network is designed by utilizing a judgment network and a long-term utility function, and unknown dynamic information of the dissolved oxygen concentration kinetic model is identified; optimization of an execution network and an actual controller is realized through the evaluation network and the execution error function; through the actual controller with the optimal parameters, self-adaptive control over the aeration pump is achieved, the control precision of the aeration degree is improved, and operation energy consumption is effectively reduced.
Owner:BEIJING UNIV OF TECH
Double-layer double-target optimization scheduling method based on large language model
The invention relates to a double-layer double-objective optimization scheduling method based on a large language model, and the method comprises the steps: building a double-layer double-objective optimization model in a server, and building an upper-layer model and a lower-layer model for an AISTS problem based on a plurality of different variables, different constraint conditions and different objective functions; and prompting a dual-objective optimization model of adjustment and algorithm evolution to form a two-stage method based on LLM, the method can overcome the defects that a traditional algorithm needs to design the algorithm manually and adjust parameters manually, the calculation cost is high, the efficiency is low, complex problems are difficult to effectively decompose and coordinate double-layer optimization, a dynamic collaborative optimization framework is lacked, and the flexibility of algorithm combination is low.
Owner:NAT UNIV OF DEFENSE TECH
Big language model enhanced reinforcement learning training method for key automatic driving scene stable decision
The invention discloses a large language model enhanced reinforcement learning training method for key automatic driving scene stable decision, and the method comprises the steps: constructing an LLM-based vehicle decision intelligent agent, and providing a high-level guidance strategy through a chain thinking technology and a knowledge experience pool; then, jointly constructing a dynamic intervention mechanism based on the environmental risk sign and the decision boundary parameter, thereby determining an LLM guidance opportunity; finally, through expert guidance algorithm design, the prior knowledge of the LLM is effectively integrated into the deep reinforcement learning strategy network by adopting an adaptive exploration-imitation fusion loss function. The DRL model is better in performance in a vehicle driving decision-making task and shows higher generalization ability in various scenes, and the robustness, the sample efficiency and the overall generalization level of the DRL model can be remarkably improved.
Owner:ZHEJIANG UNIV OF TECH
Intelligent storage space optimization method based on digital twinning technology
The invention relates to the technical field of data processing, in particular to an intelligent storage space optimization method based on a digital twin technology. The method comprises the following steps: collecting original data, and preprocessing the original data to obtain preprocessed data; constructing a digital twinborn model based on the preprocessed data; based on a digital twin model, a self-adaptive probability space distribution optimization algorithm under multi-factor guidance is introduced, a storage space layout is designed, and the storage space layout is dynamically adjusted in combination with original cargo data. The technical problems that a traditional storage space layout mode is low in storage space utilization rate and unbalanced in resource allocation due to the fact that the accuracy of processing and analyzing storage environment, goods information and the like is low are solved.
Owner:JIANGSU HONGXUE INFORMATION TECH CO LTD
Sound source localization method and system based on improved adaptive beam forming
PendingCN119511200Asuppress noisesuppress interferencePosition fixationNoise monitoringSound sources
The invention relates to the technical field of signal processing, in particular to a sound source localization method and system based on improved adaptive beam forming. A microphone array is used for collecting sound source signals, and a signal receiving model is established; designing an improved adaptive filtering beam forming algorithm, and optimizing a cost function; solving an optimal weighting vector through a minimization cost function, and introducing an adaptive updating mechanism to dynamically adjust the weighting vector; selecting a reference microphone, calculating time difference of arrival and distance difference of other microphones, and establishing a distance difference equation from the sound source to the receiver; and solving a sound source coordinate and calculating the distance between the center of the microphone array and the sound source. According to the invention, through innovative algorithm design and a self-adaptive mechanism, the precision and stability of sound source localization are significantly improved, and especially, the method shows strong anti-interference capability and adaptability in a complex noise environment. The method can effectively improve the equipment maintenance efficiency in the substation equipment noise monitoring, reduces the fault risk, and provides reliable guarantee for the safe operation of a power grid.
Owner:ELECTRIC POWER RES INST OF GUANGXI POWER GRID CO LTD
Electronic plant air conditioner control method for setting PID parameters based on fuzzy algorithm
The invention discloses an electronic plant air conditioner control method for setting PID parameters based on a fuzzy algorithm. The method comprises the steps that a design scheme is preliminarily determined according to plant design indexes, and a schematic diagram of a control system is planned; establishing a mathematical model; carrying out PLC control program design and configuration programming; designing a fuzzy controller; fuzzy design of input and output variables; defining an input and output membership function; establishing a fuzzy control table and rules; designing a system fuzzy reasoning algorithm; setting defuzzification output; designing a Simulink system control block diagram, and establishing a real-time control working space; and the communication between the MATLAB and the PLC is realized. According to the method, the control experience of a person is summarized into a group of conditional statements described qualitatively by utilizing a fuzzy logic function of Matlab software, and the conditional statements are quantified by utilizing a fuzzy set theory, so that the controller can accept the experience of the person, simulate an operation strategy of the person and overcome uncertain factors of the person, and the system has higher reliability.
Owner:SHANGHAI BAOYE GRP CORP
Distributed elastic consensus optimal control method under denial of service attack of multi-agent system based on zero-sum game
PendingCN121325963AVehicle position/course/altitude controlPosition/direction controlGraph theoreticAttack
The invention provides a zero-sum game-based distributed elastic consensus optimal control method under denial of service attack of a multi-agent system, and the method specifically comprises the steps: firstly, constructing a multi-agent formation model in which a leader and a plurality of followers cooperatively move through graph theory knowledge and a multi-agent second-order state equation; secondly, in order to reduce the influence of denial of service attack on communication topology, a time-varying weight distributed elastic observer is provided to estimate the state of a leader, and the attacked condition of the leader is considered; then, by constructing an augmentation system, a distributed consistency tracking problem with a leader is converted into a local tracking problem between each follower and a virtual leader thereof; and finally, in order to solve the zero-sum game problem, introducing a Hamiltonian-Jacobian-Ansaxophone equation to realize optimal control input under maximum external disturbance, and realizing algorithm design by using single-evaluation reinforcement learning with experience playback and combining a gradient descent method.
Owner:WUHAN TEXTILE UNIV
Double-base ISAC clock synchronization algorithm design and system based on LoS reference path
The invention belongs to the technical field of unmanned aerial vehicle communication perception integration, discloses a double-base ISAC clock synchronization algorithm design and system based on an LoS reference diameter, and aims to solve the problem of measurement errors caused by clock asynchronization of a transmitting end and a receiving end. And a receiving end receives a communication signal based on an LoS path and a sensing signal based on a non-line-of-sight (NLoS) path through a communication and sensing integrated design. The invention provides a clock synchronization algorithm based on LoS reference path assistance, and the time delay and Doppler frequency of the signal are measured by using the propagation characteristics of the LoS signal, so that the clock skew and Doppler frequency skew are accurately estimated. According to the algorithm, communication and sensing signals are combined, the clock skew of the receiving end is dynamically adjusted and compensated, asynchronous error accumulation is reduced, and sensing precision and system performance are remarkably improved. Simulation results show that the method effectively enhances communication and sensing functions of the system in application scenarios such as low-altitude economy.
Owner:YANGTZE DELTA REGION INST (QUZHOU) UNIV OF ELECTRONIC SCI & TECH OF CHINA
Digital twinning construction method based on multi-source point cloud data fusion
The invention relates to the technical field of digital twinning, particularly provides a digital twinning construction method based on multi-source point cloud data fusion, and solves the problems of low multi-source point cloud data fusion precision, low calculation efficiency and poor adaptability to complex scenes in the prior art. The method comprises the following steps: S1, preprocessing multi-source point cloud data: carrying out data denoising and coordinate unified processing on the point cloud data of each source; s2, designing a point cloud data fusion algorithm: performing feature extraction and description, feature matching and fusion decision and weighted fusion calculation on the preprocessed point cloud data to obtain fused point cloud data; s3, constructing and optimizing a digital twinborn model: performing triangular mesh generation, model optimization processing, texture mapping and attribute addition on the fused point cloud data, and constructing the digital twinborn model; the digital twinning construction method based on multi-source point cloud data fusion can effectively solve the problems that multi-source point cloud data fusion is low in precision, low in calculation efficiency and poor in adaptability to complex scenes.
Owner:HUBEI CENT CHINA TECH DEV OF ELECTRIC POWER +1
Planning algorithm design fusing intention and target trajectory prediction
According to the invention, a planning algorithm design fusing intention and target trajectory prediction is realized, and the state information of the vehicle under the Frenet coordinate system is obtained in real time through mutual conversion between the Cartesian coordinate system and the Frenet coordinate system; determining a driving reference line of the vehicle by using the global path, and predicting a driving track of the dynamic obstacle by fusing a driving intention and a target track prediction network model; planning a track and a speed by adopting a dynamic planning and quadratic planning algorithm; and integrating the tracks of the current frame and the planning frame through a polynomial splicing technology, and transmitting the integrated track to a track tracker.
Owner:GUILIN UNIV OF ELECTRONIC TECH
Intelligent heuristic algorithm generation method for unmanned aerial vehicle inspection path planning
PendingCN121349125AInternal combustion piston enginesVehicle position/course/altitude controlUncrewed vehicleBuilding inspection
The invention discloses an intelligent heuristic algorithm generation method for unmanned aerial vehicle routing inspection path planning, belongs to the technical field of unmanned aerial vehicle autonomous navigation and intelligent optimization, and aims to plan a routing inspection path with the total cost as low as possible on a building routing inspection three-dimensional point set for an unmanned aerial vehicle. Aiming at the problems of high path planning complexity and low efficiency of artificial design of a heuristic algorithm in a building coverage inspection task, the method comprises the following steps: firstly, constructing a constraint model of an unmanned aerial vehicle inspection scene, and converting multi-objective optimization requirements such as building coverage rate, total detection time and flight path length into a heuristic algorithm design problem; compared with a traditional manual design method, the method enables the heuristic algorithm to reach or exceed the design level of field experts on indexes such as building coverage integrity, path length and calculation efficiency, and provides an efficient path planning solution for intelligent inspection of the unmanned aerial vehicle.
Owner:ANHUI UNIV
Intelligent algorithm integration application platform for typical structural member of airplane
InactiveCN119312902AImprove design efficiencyImplement integrated managementGeometric CADDatabase management systemsData accessAirplane
The invention belongs to the technical field of structural engineering knowledge management, and relates to an aircraft typical structural member intelligent algorithm integration application platform which is associated with a knowledge base and a database of typical structural members and comprises an application end and a management end. The application end comprises a part type selection module, a positioning element selection and parameter input module, a model preview and installation module and a model evaluation scoring module; the management end comprises a design knowledge and data access module, an algorithm management module and a template management module; a designer can call an algorithm designed by an algorithm designer at any time to complete and verify the model in the process of designing the model, and an algorithm designer can verify and correct the algorithm through a newly designed model, so that dual optimization of the model and the algorithm is realized, and the algorithm design efficiency is improved. The design efficiency of typical structural parts and functional algorithms is effectively improved, resources are saved, and meanwhile integrated management of the functional algorithms and models is achieved.
Owner:XIAN AIRCRAFT DESIGN INST OF AVIATION IND OF CHINA
Deep learning based method for integrating demand forecasting and scheduling of online ride-hailing at hub
InactiveUS20250067564A1Instruments for road network navigationEnsemble learningEngineeringPearson Correlation Test
A deep learning based method for integrating demand forecasting and scheduling of online ride-hailing at a hub is provided. The method includes: S1, performing data processing: performing missing value filling, outlier processing and normalization processing on the historical orders of online ride-hailing and relevant feature data of the urban transportation hub; S2, performing feature screening: primarily screening the relevant features by means of a Pearson correlation test and box plot analysis, calculating an influence degree of data of each feature on the orders of online ride-hailing by using an XGBoost algorithm, and secondarily screening the features; S3, performing model construction: constructing an integrated model for demand forecasting and scheduling decision of online ride-hailing at the urban transportation hub; and S4: performing algorithm design: designing a decision tree and deep learning combination algorithm, and calculating the number of online hailed rides to be scheduled.
Owner:CHANGAN UNIV +2
Seed screening method and system based on laser radar technology
The invention provides a seed screening method and system based on a laser radar technology, and relates to the technical field of agricultural automation, and the method comprises the steps: extracting geometric features and defect features from optimized point cloud data; extracting mildew and insect pest spectral features from the optimized spectral data; a multi-dimensional feature set is obtained; calculating seed plumpness, roundness and surface roughness based on the optimized point cloud data; calculating a sag index and a crack feature based on point cloud edge detection; fusing the geometric features, the defect features and the pest spectral features to generate a comprehensive score; a machine learning model is utilized to execute final grading, and a first probability predictor based on laser radar features and a second probability predictor based on pest spectral features are trained respectively; and inputting the probability outputs of the two predictors into a second-layer grading model of the meta-learning architecture, and outputting a final quality grade. According to the method, efficient and accurate seed screening is realized through automatic process and algorithm design.
Owner:CHENGDU VOCATIONAL COLLEGE OF AGRI SCI & TECH
Online teaching programming system and teaching recommendation method based on large language model assistance
The invention discloses an online programming system based on large language model assistance and a teaching recommendation method, the system comprises a base model acquisition module, a problem decomposition module, an abstract modeling module, an algorithm design module, a code analysis and assistance module and an evaluation module, and is used for helping students to finish a programming task of teaching design online. And performing problem decomposition, abstract modeling and algorithm design on actual problems by using a large language model, and solving the problems encountered by students during programming. Based on the system, the invention further designs a teaching recommendation method, multi-modal data in the information classroom teaching process is collected, a dynamic three-level teaching interaction diagram of the space-time environment, knowledge resources and cognitive behaviors is established through man-machine, life and teacher-student interaction behaviors, and accurate teaching recommendation and intervention strategies of the human-in-the-loop are provided. According to the invention, a three-dimensional comprehensive teaching field for learning environment intellectual computing is established in a programming scene, and a guarantee is provided for high-quality modern education development.
Owner:ZHEJIANG UNIV
Transformer area identification and user binding method based on special transformer acquisition terminal
The invention relates to the technical field of power system court management, and particularly discloses a court identification and user binding method based on a special transformer acquisition terminal, which comprises the following steps: separating harmonic interference generated by start and stop of an electric welding machine through a kurtosis index and time-frequency energy entropy fusion detection method, and extracting a fundamental voltage and a pure power signal; constructing a dynamic time bending model containing phase consistency and gradient feature constraint based on the fundamental wave voltage, and calculating voltage track similarity to judge electrical coupling; for the users with electrical coupling, dynamic weight power cross-correlation analysis is fused to generate a comprehensive decision value, and a space-time diagram neural network is utilized to update a transformer area topology structure online in combination with a historical topology change event, so that the dynamic determination of the transformer area to which the users belong is realized; through multi-dimensional feature fusion and anti-interference algorithm design, the problems of phase deviation and waveform distortion caused by electric welding machine harmonic waves are reduced, and the transformer area identification accuracy and real-time performance are improved.
Owner:SHENZHEN FRIENDCOM TECH DEV +1
MOMES and FBG fusion sensing system based on tunable laser array
ActiveCN119223334AImprove compatibilityUniform outputProgramme controlComputer controlSensor arrayConverters
The invention relates to the technical field of optical fiber sensing, in particular to an MOMES and FBG fusion sensing system based on a tunable laser array. A multi-wavelength tunable laser array light source is adopted to generate fast broadband frequency sweep laser, the fast broadband frequency sweep laser is split to M paths to be output through a multi-path planar optical waveguide shunt coupler, each path of output end is connected with N FBG sensor arrays and one MOMES sensor, and sensing signal reflected light is received by a corresponding photoelectric detector. After data processing is carried out through a photoelectric converter, a logarithmic amplifier, an analog-to-digital converter and an FPGA compatible algorithm platform, wave crests and wave troughs of reflection spectrum data of each wavelength point are searched at the same time; the wave crest data is used for demodulating the FBG sensor array, and the wave trough data is used for demodulating the MOMES sensor. According to the optical path structure and algorithm design of the system, synchronous demodulation of the FBG and the MOMES sensor is realized, and the compatibility and operation efficiency of the system are remarkably improved.
Owner:NANJING UNIV
Random access lead code and detection algorithm design based on low earth orbit satellite communication
The invention discloses a random access preamble and detection algorithm design based on low earth orbit satellite communication. Specifically, firstly, a novel lead code with a plurality of subsequences is provided, in order to enlarge the number of available lead codes in a wave beam, a ZCM sequence is introduced to form the subsequences, and orthogonal frequency division multiplexing is adopted for modulation and is sent to a channel. Subsequently, a timing advance (TA) detection algorithm is proposed. The first sub-sequence is used for decimal time delay detection, and the other sub-sequences are used for integer time delay detection. In addition, the peak detection ingeniously utilizes the variance of the power delay spectrum, so that the detection performance is improved. Finally, a simulation result shows that the lead code provided by the invention is almost not influenced by frequency offset, does not need pre-compensation, and is suitable for being applied to low-orbit satellite communication with relatively large frequency offset.
Owner:SUN YAT SEN UNIV
ChatGPT-python programming method
The invention discloses a ChatGPT-python programming method, particularly relates to the field of artificial intelligence, and comprises three steps of problem definition, algorithm design and code implementation. According to the method, project situations are described in detail through question definition, and ChatGPT is guided to generate project schematic diagrams; through a design algorithm, a calculation problem is elaborated, and ChatGPT is required to provide an effective solution; by implementing codes, generating a feasible programming solution according to a calculation theory, providing intelligent suggestions in each process, ensuring theoretical accuracy and engineering feasibility of a result through manual examination, and comparing by taking three-dimensional slope stability analysis as a case and combining with a calculation result of commercial software, a calculation result of the three-dimensional slope stability analysis is obtained. It is verified that the Python algorithm obtained through ChatGPT programming has good calculation precision, an innovative auxiliary means is provided for engineering calculation, and the huge application prospect of artificial intelligence in the field of civil engineering is shown.
Owner:ANHUI UNIV OF SCI & TECH