141results about How to "Solve balance problems" patented technology

The invention provides a predictive maintenance management method and system for an industrial robot, and relates to the technical field of equipment maintenance management, and the method comprises the steps: obtaining multi-modal heterogeneous data of the industrial robot, carrying out the intelligent preprocessing, obtaining first preprocessing data, carrying out the cross-modal correlation fusion of the first preprocessing data, generating fusion data, and carrying out the prediction of the industrial robot; extracting complementary redundant information and constructing a semantic feature map; constructing a health state prediction model, adding the semantic feature map into the health state prediction model, mapping the semantic feature map to an embedding space through linear transformation, extracting time sequence information, carrying out feature interaction to obtain interaction features, and carrying out transformation and feature enhancement through a feedforward neural network layer to obtain health state probability distribution; comprehensive health state distribution is generated through Bayesian reasoning fusion, an optimal maintenance strategy is generated in combination with a detection model, an abnormal mode and a key turning point, collaborative maintenance is conducted on the industrial robot, a maintenance result is uploaded to a server, and the current state is stored.

The invention relates to a parameter updating method based on low-rank decomposition, and aims to solve the problems of high consumption of computing resources and difficulty in balancing model performance and complexity when large-scale financial data is processed in the prior art. According to the method, the pre-training model is determined, the source data set is obtained, and the source data set is utilized to train the pre-training model to obtain the source model; fixing parameters of all layers of the source model, and inserting a preset number of data processing layers into the source model; and obtaining a training data set, training the inserted data processing layer by using the training data set, updating parameters of the data processing layer in an incremental mode, and finally obtaining a target model. The method is suitable for processing a scene of a large-scale data set, the problems that in the model training process, computing resource consumption is too large, and training time is too long are solved, the practicability and response speed of the model are remarkably improved, and meanwhile the performance and adaptability of the model on specific tasks are improved.

The invention belongs to the technical field of biological feature recognition, and relates to a Transform-based gene data mining method, which comprises the following steps of: loading gene expression data from a file, and preprocessing; inputting the data into a designed model for training and evaluation; the designed model comprises a CNN (Convolutional Neural Network) and an improved Transform model; the improved Transform model comprises an encoder and a classifier; the encoder adopts a multi-head self-attention mechanism, a convolutional self-attention mechanism and a feedforward neural network; processing the data by using the trained model, and storing the fusion attention weight obtained by the coding layer in the data processing process; and finally, averaging the fusion attention weights of all batches, calculating the comprehensive attention weight of each gene at different time points, and identifying the most important gene by calculating and analyzing the attention score of each gene. According to the method, the problems of scarcity and imbalance of gene data can be solved, the risk of overfitting is reduced, and the precision of gene data analysis is improved.

The invention discloses a transformer area side energy storage type electric energy quality comprehensive treatment method, which comprises the steps of monitoring and data analysis, voltage out-of-limit control, power out-of-limit control, reverse transmission prevention control, voltage reactive power control, source network load storage coordinated optimization, distributed photovoltaic absorption, comprehensive line loss reduction and the like. The transformer area operation parameters are monitored in all directions, the big data analysis technology is used for analyzing and processing real-time detection data, the functions of transformer area side voltage out-of-limit control, power out-of-limit control, reverse transmission prevention and the like are achieved, and the transformer area side electric energy quality can be effectively improved; the distributed photovoltaic bearing capacity and the access capacity of the alternating current charging pile of the electric vehicle are improved, the comprehensive line loss rate is reduced, the comprehensive line loss can be reduced by 10%, the distributed photovoltaic bearing capacity can reach 150%, the access capacity of the alternating current charging pile of the electric vehicle can be improved by 200%, and 100% consumption of the distributed photovoltaic is achieved.

The invention belongs to the field of aircraft control, and discloses a composite guidance aircraft guidance control method and system considering flight time falling angle constraint, and the method comprises the steps: inputting target values of flight time and a terminal falling angle according to a specific task requirement; pre-planning a flight path; in the flight process, estimating the current remaining flight time of reaching the target in real time, and performing feedback adjustment on the flight time error; in a flight approaching target stage, calculating a falling angle error in real time according to the attitude and speed of the aircraft, and correcting the flight attitude; through a nonlinear optimal control algorithm, two constraints of flight time and a falling angle are comprehensively balanced; executing mechanisms such as engine thrust, control surface angle and attitude control spray pipes of the aircraft are adjusted in real time according to a composite guidance algorithm instruction; and when the aircraft is about to arrive at the target, final falling angle correction is performed to ensure that the aircraft hits the target at an accurate angle. According to the method, the balance problem between the flight time constraint and the falling angle constraint is effectively solved, and the guidance precision and the task success rate of the aircraft are remarkably improved.

The invention belongs to the field of artificial intelligence and deep learning, and provides a small sample continuous learning method and system based on adaptive adaptation layer selection. The small sample continuous learning method based on adaptive adaptation layer selection comprises the following steps: pre-training a singular value of a linear weight; freezing a pre-training linear weight matrix corresponding to the knowledge sensitive component; adaptively determining an adaptation layer; multiplying the adapter matrix based on the adaptation layer by the training sample features of the current incremental adaptation training stage to obtain redundancy capacity features; and the small sample playback data is obtained again, singular value decomposition, adaptive layer adaptive determination and incremental adaptive training operation are performed in sequence based on the updated pre-training linear weight matrix, and learning is stopped until the continuous learning model reaches a set requirement, so that the trained continuous learning model is utilized to execute a classification task. According to the method, dynamic adapter selection for minimizing old knowledge interference is realized, and the classification accuracy of a small sample continuous learning model is guaranteed.

The invention discloses a prototype-based federated medicine multi-modal Hash retrieval method, system and equipment and a medium, belongs to the technical field of federated learning and multi-modal Hash retrieval, and aims to solve the technical problem of how to effectively guarantee the privacy and security of medical data in a multi-modal Hash retrieval process. The technical scheme adopted by the invention is as follows: the method comprises the following steps of: constructing a medical multi-modal data set; constructing a federal medicine multi-modal Hash retrieval model based on the prototype: constructing the federal medicine multi-modal Hash retrieval model based on the prototype by utilizing a neural network and a deep learning technology; model training: training a federal medicine multi-modal Hash retrieval model based on a prototype by utilizing the final data set; the method for constructing the federal medicine multi-modal Hash retrieval model based on the prototype comprises the following specific steps: performing medical multi-modal fusion; carrying out prototype parameter reinforcement learning; a hash retrieve query.

The invention relates to the technical field of image processing, and discloses a container loading and unloading positioning identification method based on machine vision. The method comprises the following steps: firstly, obtaining a to-be-processed container image, and carrying out noise reduction processing, binarization processing and edge detection on the to-be-processed container image to obtain a processed container image; secondly, HOG features of the processed container image are extracted, and an HOG feature vector set is obtained; a final SVM classifier is obtained through training, the HOG feature vector set is input into the final SVM classifier for classification, and container recognition is completed. And after container identification is completed, obtaining a container top image, processing the container top image to obtain a container corner fitting lockhole image, and positioning the position of the container corner fitting lockhole by using a convolutional neural network to realize container loading and unloading identification and positioning. According to the method, the container image is processed, the purpose of container loading and unloading positioning identification is achieved, and the method is accurate and objective.

The invention relates to a block chain transaction method supporting privacy protection and identity tracking, and belongs to the technical field of block chain application. The specific process of the method is as follows: a financial management institution FMA generates a public key / private key pair for member registration and anomaly analysis according to a security parameter lambda, and group sending is performed on public keys; deploying a recharging contract and a payment contract on the block chain; each consumer ui registers to the FMA through a mobile device to become a member user of the transaction system, and the consumer holds a group signature key gski returned by the FMA after successful registration; the payment service operator cj registers to the FMA to become a member before providing service, and after successful registration, the payment service operator holds the FMA to return an identifier pid of each product terminal managed by the payment service operator; and the consumer calls a payment contract to carry out order payment based on the signature key gski and the identifier pid of the product terminal, and finally, the method further comprises an anomaly analysis link.

The invention relates to a bioelectrical impedance spectroscopy noninvasive blood glucose detection method, and relates to the technical field of noninvasive blood glucose detection. The method comprises the following steps: firstly, acquiring a bioelectrical impedance spectrum of the forearm of a human body by using a bioelectrical impedance sensor, then, reducing the difference of bioelectrical impedance between different subjects and sessions by using a proposed baseline correction method, and finally, expanding and balancing a sample based on an Optuna hyper-parameter optimization algorithm. Frequency and feature selection and regression model establishment are integrated into one evaluation index, and overall optimization of hyper-parameters is achieved. Specifically, the problems of small sample size and large blood glucose extreme value estimation deviation are simultaneously solved by using a data generation method based on K nearest neighbor in combination with a Clark error grid evaluation index and sample density weighting. Secondly, according to prior information of a data structure, using sparse group minimum absolute shrinkage with a weight proportion threshold value and a selection operator to simultaneously select frequency and characteristics which contribute to modeling to the greatest extent; and finally, an ensemble learning algorithm XGBoost is selected and used to establish a final model. The overall optimization method improves the robustness of the model and the accuracy of the estimation result.

The utility model discloses an acarus killing instrument which comprises a main body, and a stirrer chamber is defined by the main body; one end of the speed reducing mechanism is in transmission connection with the driving motor; the stirrer element is arranged in the stirrer chamber and comprises a stirring main body and a core shaft, a mounting groove is formed in one end of the stirring main body, the core shaft is arranged in the mounting groove, one end of the core shaft is in transmission connection with the other end of the speed reducing mechanism, and the other end of the core shaft is connected to the groove bottom of the mounting groove; the other end of the stirring main body is suspended in the stirrer chamber; and the supporting structure is arranged on the main body and extends into the mounting groove, and the supporting structure is arranged on the central spindle in a sleeving manner and is supported on the inner circumferential wall of the mounting groove. Therefore, through the arrangement of the acarus killing instrument, the weight of the mandrel can be increased and the weight distribution of the stirrer element can be changed through the supporting structure, so that the problems of shaking and dynamic balance unbalance caused by the suspension arrangement of the other end of the stirrer element are effectively solved.

The invention discloses a shock absorber control method and device based on excitation frequency and a vehicle, and belongs to the technical field of vehicle control. The shock absorber control method comprises the steps that the vertical acceleration of a vehicle body and the sprung and unsprung relative displacement of a shock absorber are obtained; according to the vertical acceleration of the vehicle body and the sprung and unsprung relative displacement of a shock absorber, initial ceiling damping force and initial ground ceiling damping force are determined respectively; acquiring a current driving mode of the vehicle, determining a frequency division point according to the current driving mode, and performing high-pass and low-pass filtering on the initial ceiling damping force and the initial ground ceiling damping force according to the frequency division point to determine a final ceiling damping force and a final ground ceiling damping force; and the final ceiling damping force and the final ground ceiling damping force are summed to obtain final damping force, control current needed for achieving the damping force at the current speed is determined according to the current speed of the shock absorber and the final damping force, and the shock absorber is controlled according to the control current needed for achieving the damping force at the speed.

The invention discloses a multi-modal Hash retrieval method, system and equipment based on a multi-view center structure and a medium, belongs to the technical field of artificial intelligence and multi-modal Hash retrieval, and aims at achieving the technical purpose of obtaining balance between intra-class compactness and inter-class separability in the multi-modal Hash retrieval process. According to the technical scheme, the method comprises the following steps: constructing a multi-modal data set; constructing a multi-modal Hash retrieval model based on a multi-view center structure; training the model; wherein the construction of the multi-modal Hash retrieval model based on the multi-view center structure specifically comprises the following steps: modal specific prototype learning: respectively extracting refined features from corresponding modals by using an image modal depth multilayer perceptron and a text modal depth multilayer perceptron; calculating the average value of the refined features of the image modality and the text modality to obtain a modality specific prototype, and further obtaining the unique features of the image modality and the unique features of the text modality; carrying out multi-modal integrated prototype learning; and performing multi-view semantic enhanced hash learning.

The invention discloses an end-to-end cervical cell classification integrated framework. The system mainly comprises four modules: an enhancement module for expanding and preprocessing an original data set; the fusion module is used for training an improved primary learner on the data set and fusing, outputting and generating a new data set; the purification module is used for purifying the new data set to obtain an integration result of the primary learner and retaining misclassified samples; and the relearning module is used for carrying out relearning by using a secondary learner and carrying out final classification. In addition, a self-adaptive data enhancement method is provided in the training stage of the primary learner and the secondary learner. According to the method, through stage-by-stage fine-grained optimization, the problems that existing cervical cell data sets are unbalanced in category distribution and rare in number are solved, and meanwhile, the classification precision is remarkably improved by emphatically learning easily-confused image features through an integrated framework. Experiments show that the method can effectively assist in cervical cancer screening, the workload of pathologists is greatly reduced, and the method has good application value and huge social benefits.

The invention provides a recommendation method and device based on hypergraph and multi-behavior contrast learning, equipment and a medium, and the method comprises the steps: obtaining interaction data of a user and an article, carrying out the preprocessing, and obtaining user behavior data and article attribute data; constructing a hypergraph for reflecting multi-behavior interaction and semantic information between the user and the article; obtaining feature representations of the user and the article based on the hypergraph, and enhancing the feature representations of the user and the article through multi-behavior contrast learning; and performing feature fusion based on the enhanced features, and performing target behavior prediction and recommendation. According to the method, information is enhanced through the hypergraph, and the relevance between the articles and the relevance between the users are captured. According to the method, more abundant and real feature representation is obtained based on feature comparison learning of behavior enhancement, and feature fusion is performed among different behaviors, so that the problems of data sparsity, behavior imbalance and the like are effectively solved, the recommendation accuracy and efficiency are improved, the user time is saved, and the user experience is improved.

The invention relates to a stone CT image segmentation method and device based on deep learning and mixed loss, and belongs to the field of medical image analysis. Preprocessed data are sent to an encoder of a 3D Unet of a segmentation model, step-by-step convolution and maximum pooling calculation are carried out on an input kidney stone CT image, and the input of each step of calculation is the output of the previous step; the preprocessed data are partitioned and flattened into sequence vectors, the sequence vectors are sent into a ViT encoder of a segmentation model for self-attention calculation, and global features of a calculus CT image are obtained; the obtained global features are sent to a global feature decoder of a segmentation model decoder, deconvolution decoding calculation is carried out step by step, and a plurality of feature maps with different channel numbers are obtained; a feature map obtained through the last convolution and pooling calculation is sent to a 3D Unet decoder of a segmentation model decoder, and deconvolution calculation is carried out successively; according to the method, the position and form of the calculus in the calculus CT image can be accurately identified, and the segmentation effect is improved.

The invention relates to the technical field of tire manufacturing, in particular to a puncture-resistant tread rubber composition for bicycles and electric vehicles, a mixing method and a tire. According to the composition, a rubber base material and an auxiliary system are carefully selected, and aramid short fibers subjected to surface treatment are combined, so that the puncture resistance of the material is remarkably improved, good elasticity and aging resistance are kept, and good balance between the puncture resistance and the elasticity is realized.

The invention discloses a preparation method of a biochar soil conditioner based on agricultural and forestry waste, and relates to the technical field of agricultural resource utilization and soil improvement, the method comprises the following steps: S1, selecting suitable raw materials based on physicochemical characteristics of specific agricultural and forestry waste, and performing pretreatment, the method comprises the following steps: S1, pretreating raw materials, S2, carrying out high-temperature pyrolysis on the pretreated raw materials to form biochar, S3, regulating and controlling the mixing ratio of the biochar to an additive based on target soil trace element and organic matter requirements, and S4, carrying out curing and grinding treatment on the mixed material to obtain a conditioner finished product. According to the preparation method of the biochar soil conditioner based on the agricultural and forestry wastes, the soil microbial activity is enhanced, the remediation and long-term stability of a soil ecosystem are promoted, the resource utilization of the wastes is realized, and the biochar soil conditioner has good ecological benefits and sustainability; and the problems of soil nutrient balance and fertility durability can be solved by optimizing and regulating the supplement proportion of trace elements and organic matters.

The invention relates to a direct-current power transmission device suitable for new energy transmission and a control method and equipment thereof, which are applied to a converter station of a transmitting end system, the converter station comprises at least one transmitting line, and each transmitting line comprises a converter transformer and a converter connected with the converter transformer. The direct-current power transmission device comprises a voltage support module which is connected in parallel between a converter transformer and a converter and has an energy consumption function, and the voltage support module is also used for providing reactive power required by operation for the converter and adjusting the voltage of the alternating-current side of the converter. The direct-current power transmission device provides reactive power required by operation of a diode in a current converter through a voltage supporting module, and by adjusting the voltage of the alternating-current side of the diode in the current converter, the direct-current output power of a converter station is adjusted, the controllability of the converter station is enhanced, and the total cost of a sending end system is reduced; when the direct current side of the converter transformer breaks down, energy consumption can be input in time by adopting the voltage supporting module, so that the power of a sending end system reaches a balanced state.

The invention discloses a depth regression method and device based on angle compensation, equipment and a medium, and the method comprises the steps: creating a basic regression model which comprises an encoder, a projection layer and a prediction layer, training the basic regression model through an angle compensation loss function, and obtaining a depth regression model; and finally, inputting verification set data to the deep regression model to verify the model performance, thereby solving the technical problems that a large amount of training data is generally needed and the effect is often lower than that of other task types due to the fact that the sample distribution of the regression task is generally continuous and unbalanced, such as age, power consumption, physiological indexes and the like.

The utility model discloses a kind of mine dump truck antenna support, comprising: support assembly, vertical pole, support base, transition base, buffer base, buffer pad, antenna installation support;Support assembly is frame structure, support assembly is provided with assembly connecting end head in bottom, vertical pole lower end is hinged with support base, vertical pole upper end is hinged with assembly connecting end head;Transition base is hinged in support assembly lower part, transition base, assembly connecting end head are located at the both sides of support assembly respectively;Antenna installation support is connected in support assembly top, buffer base is connected in support assembly, buffer base is located between antenna installation support, transition base, buffer pad is installed between support assembly, buffer base. The utility model can effectively solve the balance and stability problem of antenna in driving and unloading process, provide reliable guarantee for high-precision positioning of unmanned mine dump truck.

The invention relates to a direct current and even harmonic load balancing and modeling method based on piezoelectric impedance. The method comprises the following steps: step 1, sampling a voltage value V1 flowing through a sampling resistor RA1 of a positive half-cycle waveform of a measured electric energy meter unit and a load resistor RZ1, and a voltage value V2 flowing through a sampling resistor RA2 adopting a balance meter as a balance impedance EUT2 and a load resistor RZ2; 2, judging whether the effective values of the voltage value V1 and the current value V2 are equal or not; if not, adjusting the resistance value of the balance impedance through the microprocessor corresponding to the load resistor, and returning to the step 1; the device is reasonable in design, compact in structure and convenient to use.

The invention discloses a detection method, device and equipment based on visual detection of defects and a storage medium, and relates to the technical field of image processing, and the detection method based on visual detection of defects comprises the following steps: obtaining to-be-processed image data and carrying out data preprocessing to obtain defect image data; defect detection processing is conducted on the defect image data based on a defect detection model, surface defect detection data are obtained, a loss function is added to the defect detection model, and the defect detection model is obtained by improving a YOLO model; and screening the surface defect detection data to obtain a surface defect detection result. According to the invention, the accuracy of defect detection is improved.

The present disclosure relates to the technical field of intelligent robots, and specifically provides a robot, a control method and device thereof, and a storage medium. A robot control method includes obtaining first attitude information of a robot and determining second attitude information of a standing surface according to the first attitude information, determining a target dynamic equation according to a dynamic equation of the robot and a dynamic equation of the standing surface, establishing a control optimization task of the robot based on the target dynamic equation, obtaining target torques of each joint of the robot based on the first attitude information, the second attitude information and the control optimization task, and controlling movements of each joint of the robot according to the target torques. In the present disclosure, through dynamic analysis and optimization control of the attitude of the robot and the attitude of the standing surface, the balance problem of the robot on a dynamic standing surface is solved, the balance control of the robot on the dynamic standing surface is realized, the application scenario of the robot is expanded, and the control stability of the robot is improved.

The invention discloses a hardware resource management method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring hardware resource demand information of an application system, and determining at least one hardware server based on the hardware resource demand information; adding the hardware server into the shared cluster, and setting a corresponding resource label and a corresponding taint label for the hardware server; acquiring a deployment configuration file corresponding to the application system, and deploying the application system into the shared cluster based on the deployment configuration file; the deployment configuration file comprises a node selection label and stain tolerance; and when the application system is operated, if the node selection tag is matched with the resource tag and the stain tag is matched with the stain tolerance, scheduling the application system to a hardware server for operation. According to the method and the device, on the premise of not additionally increasing hardware resources, the isolation of the resources and the network among the application systems in the shared cluster is improved, and the balance problem between the isolation and the cost during hardware resource management is solved.

The invention provides a ginseng compound beverage and a preparation method thereof, and relates to the field of food preparation and processing. The ginseng compound beverage is prepared by taking 0.8 g of ginseng, 5.0 g of fried hippophae rhamnoides leaves, 5.0 g of medlar, 0.7 g of astragalus membranaceus and 0.5 g of gastrodia elata as raw materials, adding 15mL of plant water extract, 0.7500 g of flavoring agent erythritol, 0.3000 g of xylitol, 0.0450 g of acesulfame potassium, 0.0075 g of DL-malic acid, 0.0375 g of edible salt and 0.0080 g of taurine according to a material-liquid ratio of 1: 40g / ml, and adding water to 150mL. Meanwhile, the bitter taste of the raw materials such as the ginseng and the scorched taste of the fried hippophae rhamnoides leaves are eliminated, so that the beverage is fragrant in sense and the cost is reduced. The prepared beverage is simple in process and has the effects of resisting oxidation and reducing uric acid.

The utility model provides a magnetic suspension permanent magnet synchronous motor, which comprises a motor casing and a motor rotor, and is characterized in that an A-end protective bearing assembly, an A-end radial magnetic bearing assembly, a motor stator, an axial magnetic suspension bearing assembly, a B-end radial magnetic bearing assembly and a B-end protective bearing assembly are sequentially arranged in the motor casing; the motor rotor sequentially penetrates through the A-end protection bearing assembly, the A-end radial magnetic bearing assembly, the motor stator, the axial magnetic suspension bearing assembly, the B-end radial magnetic bearing assembly and the B-end protection bearing assembly, and an inner cavity cooling fan assembly and a thrust disc are sequentially arranged at the end, close to the B-end protection bearing assembly, of the motor rotor; according to the utility model, the thrust disc and the inner cavity cooling fan assembly are placed at one end of the motor rotor close to the B-end protection bearing assembly, so that the problem of balance of two ends of the rotating shaft after the A end of the motor is loaded can be solved.

The present application proposes a control method, a control device and a microgrid for a microgrid, and relates to the field of microgrid technology. The control method for the microgrid includes: obtaining the current energy storage data of multiple sub-microgrids in the monitoring area, the current power consumption data of each load and the historical grid load data; determining the real-time power demand corresponding to each sub-microgrid according to the power consumption data; determining the energy storage state corresponding to each sub-microgrid according to the energy storage data; predicting the future grid load trend according to the historical grid load data; generating the corresponding power dispatching parameters and operating constraints of the sub-microgrid according to the real-time power demand, energy storage state, future grid load trend and the preset microgrid power model; and controlling the power output of each sub-microgrid according to the power dispatching parameters and operating constraints. The present application can jointly control multiple sub-microgrids in the area to comprehensively improve the comprehensive benefits of the power system.

The present invention relates to a three-level converter SVPWM method and system based on multi-vector synthesis, the method comprising: dividing a three-level space voltage vector diagram into a plurality of sectors; controlling the duty ratio of a small vector and a middle vector in each sector to be equal, obtaining the constraint conditions of the small vector and the middle vector, combining the constraint conditions of the small vector and the middle vector, calculating the duty ratio of the output voltage vector in each sector; according to the duty ratio of the output voltage vector, combining the preset output voltage vector arrangement sequence, obtaining the output state of the three-phase bridge arm voltage in the three-level converter and the driving signal of each phase switch tube. The present invention uses multi-vectors to synthesize space vectors, and only needs to simply divide the space vector diagram into six sectors, and calculate the time for the synthetic vectors in the six sectors to act respectively, which significantly reduces the amount of calculation, and the implementation process is simple. By controlling the time for the small vector and the middle vector to act in each sector, the balance problem of the three-level midpoint voltage is solved.

The invention provides a transient algorithm optimization method for current mode hysteresis control based on a Buck converter, which improves the transient response effect of the Buck converter under hysteresis control while simplifying an inductive current sampling circuit and improving the overall efficiency of a system. Through the rapid detection of the output current and the inductive current, the rapid recovery of the output voltage is realized by using an improved transient control algorithm.