101 results about "Target distribution" patented technology

The application discloses an abnormal early warning method and device of a distributed photovoltaic power generation system and electronic equipment. The method comprises the following steps: obtaining current performance data, current environmental interference data and performance index data of a target distributed photovoltaic power generation system at a current time, and then determining a current initial performance score of the target distributed photovoltaic power generation system at the current time; based on the current initial performance score, detecting whether the performance of the target distributed photovoltaic power generation system has a target abnormal fluctuation at the current time; if the target abnormal fluctuation exists, determining an abnormal reason, and correcting the current initial performance score based on the abnormal reason to obtain a current target performance score of the target distributed photovoltaic power generation system at the current time; and based on the current target performance score, performing abnormal early warning on the target distributed photovoltaic power generation system. The application solves the technical problem of inaccurate abnormal early warning of the distributed photovoltaic power generation system in the related art.

This invention discloses a low-voltage centralized meter reading and maintenance training system and method for power grids, belonging to the field of power grid simulation. The system includes a host computer, a metering module, a fault simulation module, and a cross-regional control module. The host computer generates training task control commands and sends them to the fault simulation module. The fault simulation module sends fault control signals to the cross-regional control module and the metering module. The cross-regional control module disconnects the target meter from the original distribution area and connects the target meter to the target distribution area when the fault control signal indicates a fault setting; and disconnects the target meter from the original distribution area and switches the target meter line back to the original distribution area when the fault control signal indicates a fault recovery. The metering module generates metering data and sends it to the host computer so that the host computer can generate training results. The fault simulation module also drives the corresponding relay to operate according to the switching status information of the cross-regional control module to simulate training. By implementing this invention, the problem of insufficient scenario coverage in existing technologies can be solved.

The application belongs to the technical field of unmanned aerial vehicle cluster cooperative control and multi-agent deep reinforcement learning, and particularly relates to a multi-agent deep reinforcement learning multi-unmanned aerial vehicle capturing method based on a distributed dynamic environment, which comprises the following steps: 1. constructing a network and setting parameters; 2. collecting experience data; 3. sampling data based on a priority-based experience sampling mechanism; 4. constructing a target action and a target distribution, and calculating a next state action under the sampled data; 5. fusing the distribution output of a multi-value network; 6. calculating the loss of a prediction value network and performing parameter updating, and performing delayed updating on a prediction strategy network; 7. performing soft updating on a target value network and a target strategy network through a soft updating mechanism; 8. judging whether a target is captured through a multi-unmanned aerial vehicle cooperative capturing and dynamic optimization algorithm, and outputting a comprehensive report of multi-unmanned aerial vehicle cooperative capturing. The method realizes the triple promotion of capturing precision, noise resistance and cooperative decision efficiency.

The present application relates to the technical field of data processing, and especially relates to a kind of urban distribution network operation load intelligent optimization method, in the process of predicting the operation load of target distribution network at future time, for any load node, the reference historical date corresponding to the load node is filtered out, which is similar to the temperature at future time, and the date type of the date at future time is the same, according to the fluctuation of power data in each reference historical date, the power prediction value of the load node at future time is obtained;According to the stability of power data at the same time in each reference historical date, the prediction credibility of power prediction value is obtained;According to the power prediction value of each load node at future time and its prediction credibility, the required power of target distribution network at future time is predicted, the accuracy of predicting the operation load of urban distribution network is improved, and then the intelligent scheduling of the operation load of target distribution network is realized.

The invention discloses a detection method and system for identifying environmental garbage based on unmanned aerial vehicle aerial photography and AI, and the method comprises the steps: carrying out the preliminary aerial photography of a seawall through an unmanned aerial vehicle, obtaining a seawall global image, and dividing the seawall global image into a plurality of seawall sub-regions; determining an aerial photography strategy adapted to each seawall sub-region according to the landform characteristics of the seawall sub-regions; sub-region images of the unmanned aerial vehicle corresponding to the aerial photography strategies are collected, and a target distribution set of seawall sub-regions is extracted from the sub-region images; carrying out AI identification on the target distribution set, and screening to obtain a garbage positioning set; and performing spatial distribution integration on the garbage positioning sets of all the seawall sub-regions to obtain garbage distribution characteristics, and mapping the garbage distribution characteristics to a seawall global map to obtain a visual garbage distribution report. According to the method, global aerial photography and region division are carried out on a seawall, adaptive partition aerial photography of the seawall is achieved, garbage in different regions is accurately positioned, positioning characterization information of all the garbage is formed, a visual garbage distribution report is generated in combination with a seawall global map, and efficient and reliable garbage detection is achieved.

The application discloses a distributed network node selection method and device and a readable storage medium, and relates to the technical field of communication, so that the selected distributed network node meets the demand of a terminal. The method comprises the following steps: selecting a target distributed network node according to first information; wherein the first information is a correspondence relationship among a PLMN ID, a distributed network node identifier and an access technology, or the first information is a correspondence relationship between a DNID and an access technology. The embodiment of the application can make the selected distributed network node meet the demand of the terminal.

The application discloses a single-core optical fiber data acquisition method and system, and belongs to the technical field of data acquisition. The data acquisition system comprises a main controller, a single-core optical fiber and a plurality of distributed terminals. The main controller broadcasts a data acquisition instruction, triggers all the distributed terminals to synchronously start data acquisition and calculate data length. The main controller establishes a synchronous link with a target distributed terminal through a polling addressing mode. The target distributed terminal sequentially uploads a state packet containing data length, an acquisition data packet and a reporting end signal. After receiving the end signal, the main controller closes the current synchronous link and then sends an addressing instruction of the next target distributed terminal to all the distributed terminals. The previous steps are repeated until the data of all the distributed terminals is converged to the main controller. The data acquisition method accurately schedules the exclusive time length of each distributed terminal to the single-core optical fiber, thereby improving data acquisition efficiency.

The present disclosure describes a method for conditioning and preprocessing raw cosmic ray data to extract features and generate a binary string representing the inherent randomness in the data. Measurable characteristics of cosmic ray particles, such as arrival times and amplitudes, are processed to create random binary sequences. These binary strings are then used to train a generative adversarial network (GAN) framework. In the GAN framework, the generator creates random sequences resembling the target distribution, which matches the entropy of the conditioned cosmic data. The discriminator evaluates the generated sequences by comparing them to the conditioned cosmic data and assigns a randomness score that characterizes the quality of the generated sequences. This adversarial process ensures the generation of high-quality random sequences that are statistically indistinguishable from the conditioned input data.

The present application relates to the technical field of bioinformatics and artificial intelligence, in particular to a virtual cell construction method and system, the method comprising: taking single cell gene expression matrix and perturbation condition data as input data; constructing an encoding network based on a structural causal model to obtain latent representation, and constructing a perturbation variable according to the perturbation condition data, modeling the latent representation and the perturbation variable to obtain decoupled latent representation; constructing a continuous time evolution path from an initial distribution to a target distribution based on a flow matching model, and determining state changes according to the decoupled latent representation; numerically solving the continuous time evolution path to output virtual cell expression data. The present application is used to solve the problems of causal aliasing, insufficient distribution out-of-distribution generalization ability, unstable generation process and difficulty in counterfactual reasoning in the existing single cell perturbation prediction method.

The application discloses a key filling method for a quantum local area network, the quantum local area network comprising a first control station, a quantum key filling machine and a key distribution center, the first control station and the quantum key filling machine being in communication connection, and the method comprising: the quantum key filling machine sending a key filling request to the first control station. The first control station determines a target distribution strategy from preset distribution strategies according to the type of the key filling request, the preset distribution strategies comprising a first preset key distribution strategy and a second preset key distribution strategy. The first control station distributes the obtained quantum symmetric key to the quantum key filling machine and / or the key distribution center according to the target distribution strategy to perform key filling, wherein the quantum symmetric key distributed based on the first preset key distribution strategy is a directional key, and the quantum symmetric key distributed based on the second preset key distribution strategy is a local area network key. Thus, the problem that the quantum key is single and cannot provide diversified services is solved.

This invention provides a method and system for intelligent observation and planning of transportation infrastructure based on multi-aircraft collaboration, relating to the field of UAV intelligent observation technology. The method includes acquiring disaster scene, target distribution, and UAV resource information; determining sensor configuration schemes; calculating target urgency and prioritizing them for allocation; constructing access maps to generate observation sequences; planning unobstructed flight paths; controlling UAVs to execute observation tasks; and generating damage assessment results. This method achieves efficient multi-aircraft collaborative observation, improving the efficiency and accuracy of post-disaster transportation infrastructure assessment.

This invention provides a method and system for segmented monitoring of 10 kV line losses based on multi-source data. It relates to the field of distribution network line loss monitoring technology. The method includes: acquiring multi-source operational data of a target distribution network that includes at least target measurement data and topological characteristics; verifying the reliability of the target measurement data based on a preset system reference benchmark to select a reliable measurement dataset; constructing a line segmentation model based on topological characteristics to divide the network into several monitoring segments; and calculating the dynamic line loss index of each monitoring segment based on the model and the reliable measurement dataset. This invention significantly improves the accuracy and reliability of line loss calculation results from the data source.

The present disclosure discloses a programming method of a three-dimensional memory, a three-dimensional memory and a memory system. The programming method comprises: performing programming operation on a plurality of memory cell layers to be programmed in the three-dimensional memory according to a preset programming sequence; wherein when a first programming operation is performed on a first memory cell contained in a first memory cell layer among the plurality of memory cell layers to be programmed, a distribution of threshold voltage of the first memory cell is offset by a set amount from a target distribution; wherein the set amount is used to compensate for the offset of the target distribution of the first memory cell contained in the first memory cell layer caused by interlayer interference by a second programming operation on a second memory cell contained in a second memory cell layer among the plurality of memory cell layers.

This invention discloses a machine learning model integrating oral microbiome and clinical features and its application in predicting sarcopenia at high altitudes. The method targets high-altitude populations residing at altitudes >3500 meters, collecting oral microbiome 16S rRNA sequencing data, clinical features, and lifestyle data. Core predictive factors are selected through adaptive preprocessing and elastic network regularized regression, and a classification model is constructed using logistic regression. To address the sample imbalance problem in high-altitude areas, this scheme introduces a synthetic balanced sampling strategy based on target distribution doubling; simultaneously, Platt Scaling is used for two-layer probability calibration, combined with a dynamic threshold optimization mechanism based on F1-Score to improve discrimination accuracy. This invention is the first to integrate oral microbiome shaped by the high-altitude environment (such as…)… Selenomonas , Veillonella (etc.) are incorporated into the predictive model. Experiments show that the model achieves an AUC of 0.868 on the independent test set and has advantages such as being completely non-invasive, low-cost, and highly interpretable. This invention provides an efficient early screening program for sarcopenia in resource-scarce high-altitude areas.

The present application relates to the technical field of data acquisition, in particular to an intelligent logistics distribution data acquisition intelligent control system and method, which constructs an acquisition task graph based on vehicle trajectory prediction, task target distribution and historical path mutation record, labels path sensitive section and replaceable node cluster, and generates an acquisition plan candidate set with path fault tolerance structure. Through the sensor scheduling engine, the sensor acquisition type, data dimension redundancy and energy sensitivity are comprehensively considered, the acquisition task is implemented cross-modal peak-shaving sorting and redundancy compression, a multi-modal acquisition strategy table is formed, and support nodes such as material transfer, signing confirmation and perishable goods state critical point are identified. When the vehicle approaches the support node, the acquisition preparation mechanism is triggered and data acquisition is performed, after the acquisition is completed, the distribution task target is checked, and according to the checking result, the path sensitive structure and the acquisition strategy are dynamically adjusted, realizing the intelligent closed-loop control of data acquisition in asynchronous environment.

This invention discloses a method and electronic device for determining the photovoltaic (PV) access capacity of a distribution network. The method includes: obtaining the current configuration strategy of the target distribution network; determining a PV access capacity influence factor for the target distribution network under the current operating scenario based on the current configuration strategy, wherein the PV access capacity influence factor is used to quantify the degree of influence of the current configuration strategy on the actual PV access capacity of the target distribution network; determining the coupling coefficient of the target distribution network; and determining the actual PV access capacity of the target distribution network under the current operating scenario based on the PV access capacity influence factor and the coupling coefficient. This invention solves the technical problem in related technologies where incomplete consideration of factors leads to low accuracy in assessing the actual PV access capacity of the distribution network when facing complex distribution network operating scenarios.

1. Name of the product in this design: Graphical User Interface for Displaying Sonar Detection Information in Electronic Equipment. 2. Purpose of this design: An electronic device. 3. The key design feature of this product is its graphical user interface. 4. The picture or photo that best illustrates the key design points: Design 1 front view. 5. Design 1 is designated as the basic design. 6. Purpose of the graphical user interface: After the sonar is introduced into the water, it emits ultrasonic waves to the surrounding area (within a range of 130°×20°) through the sonar head, and acquires and displays environmental information and target distribution within the underwater sound wave range in real time. 7. Human-computer interaction method of graphical user interface: Design 1's main view is the sonar acquisition operation interface. By clicking various control buttons, sonar images are acquired. The sonar acquisition results can be viewed in real time on the interface. Clicking the hexagonal icon in the upper right corner enters the "Sonar Settings" interface of the changing state diagram of Design 1; Design 2's main view is the sonar acquisition operation interface. By clicking various control buttons, sonar images are acquired. The sonar acquisition results can be viewed in real time on the interface. Clicking the hexagonal icon in the upper right corner enters the "Sonar Settings" interface of the changing state diagram of Design 2.

The application provides a design method and device of a super-deep cold component thermal cutoff part and related equipment, and comprises the following steps: establishing a design domain of a thermal cutoff part on a main support structure connected with a liquid nitrogen cavity and an outer Dewar cavity; obtaining a target distribution position of the thermal cutoff part through thermal coupling topological analysis; performing parameterized modeling at the target distribution position; performing parameter optimization to obtain a target shape of the thermal cutoff part; and checking the thermal cutoff part with the target shape at the target distribution position. The design method optimizes the distribution position and shape of the thermal cutoff part, specifically, the optimal distribution position of the thermal cutoff part is determined by using a structure topological optimization method, and the optimal shape of the thermal cutoff part is determined by using a structure parameter optimization method, so that the heat from the outside is as low as possible to be transmitted to the superconducting coil.

Embodiments of the present disclosure relate to apparatus, methods, devices and computer readable storage media for handover in scenarios when source and target distributed units are co-located. The method comprises, at a first device, the first device sending an indication to a second device to use a deferred handover for a handover of a third device from the second device to a fourth device, the fourth device being co-located with the second device, wherein by using the deferred handover, at least a part of downlink data buffered at the second device is to be transmitted to the third device before performing the handover of the third device.

This invention relates to the field of dry coal sorting technology, and more particularly to a method for identifying the target distribution state of coal gangue in dual-energy X-ray transmission images. The technical solution includes the following steps: acquiring transmission images of the material to be sorted as it passes through a dual-energy X-ray transmission imaging device, selecting a low-energy image as the input image; labeling the targets in the input image to construct a dataset; constructing a target detection model based on deep learning, training it using the dataset, enabling the model to identify independent targets and different numbers of overlapping and adhered targets in the image. This invention significantly improves the detection accuracy of overlapping and adhered coal gangue targets through refined dataset construction and multi-strategy model optimization; furthermore, it quantitatively characterizes the material distribution state based on multi-dimensional parameters and combines machine learning to accurately identify six distribution forms; finally, the identification results are used for adaptive control of the sorting system, effectively improving sorting efficiency and operational stability.

A hardware random number generator (HW-RNG) for drawing samples from a multivariate target distribution through simulation of a Markov chain is disclosed. The HW-RNG (100) has a pipeline architecture operating in cycles. The HW-RNG comprises sets of p-bit devices (112-1; 112-2; 112- N), a programming unit (150) to program the sets of p-bit devices according to a corresponding set of adaptive proposal distributions, selection circuitry (121) to select one of the sets of p-bit devices, a sampling circuit (130) configured to produce a candidate sample from the proposal distribution associated with a selected one of the sets of p-bit devices, and a scheduling unit (140). The scheduling unit (140) is configured to accept the candidate sample with an acceptance probability, and recompute at least one of the proposal distributions that is conditionally dependent on the accepted candidate sample. A programming phase for each set of p-bit devices lasts for x cycles, and there are N > x sets of p-bit devices.

The application discloses a kind of digital archives distribution method and system based on dynamic optical fragments, it is related to digital archives security distribution technical field, the method includes: digital archives are handled and initial optical feature coding is generated;Based on dynamic fragment generation rule, initial optical feature coding is disassembled into multiple groups of dynamic optical fragments, and the number of fragments, distribution position, encryption parameter of dynamic optical fragment are dynamically adjusted with distribution node and time;Trust evaluation model is constructed, and the trust level of target distribution node is determined;According to trust level, the corresponding dynamic optical fragment combination and decryption permission of target distribution node are matched.The application utilizes the non-reproducible and dynamic adjustment characteristics of dynamic optical fragments, combined with node trust evaluation, greatly improves the security and controllability of digital archives distribution, and is suitable for the distribution scene of high security level digital archives.

This application provides a method, apparatus, server, and medium for batch data import using a distributed database, relating to the field of data processing technology. The method employs a data loading executor to obtain task configuration information for batch data loading tasks targeting a target business database using a stream-batch integrated computing engine; the data loading executor generates a control file based on the task configuration information; the data loading executor pulls batch business data from the target business database based on the task configuration information and generates data files based on the batch business data; and the data loading executor executes preset data loading commands according to the control file to write the data files to the target distributed database. This saves resources and improves data import efficiency in batch task scenarios.

Systems and methods are provided for identifying compounds in a combinatorial synthesis library (CSL) having particular molecular properties. The CSL is accessed using an autoencoder comprising an encoder and a decoder. The encoder maps compounds in the CSL into latent codes in a learned latent space. The decoder retrieves molecular structures of the compounds using such codes. A policy selects a batch of latent codes, and identifies a plurality of compounds from the batch of latent codes using the decoder. Molecular properties of these compounds are determined, and a reward function value for each compound is determined using the molecular properties. A probability density under a target distribution is determined using the reward function values, in which latent codes are sampled from the CSL by the autoencoder with probabilities proportional to the harmonic reward function values. Policy parameters are updated using at least one difference between the probability density and the target distribution using an alpha-divergence based objective function.

A hardware random number generator (HW-RNG) and related method are disclosed. The HW- RNG comprises a sample generation stage, adapted to produce primary samples from a plurality of primitive probability distributions, a sample processing stage and a control unit. The sample generation stage includes sets of programmable p-bit devices, a programming unit to adjust the mean values for each set of p-bit devices, and a distinct sampling circuit for each set of p-bit devices. The sample processing stage comprises function logic blocks and selection circuitry configured to route at least one subset of the primary samples to a corresponding function logic block. The control unit is configured to obtain information relating to a composition of basis distributions representative of a target distribution, instruct the function logic block to perform at least arithmetic operation identified by the information, instruct the programming unit to program the sets of p-bit devices according to the composition of basis distributions, and generate the select signal to operatively couple the function logic block to sampling circuits that produce primary samples of random variables defined by the composition of basis distributions.

This invention discloses a method, apparatus, device, and storage medium for detecting defects in distribution network cables. Its features include: generating a high-frequency, short-time excitation signal using an avalanche transistor circuit and injecting the high-frequency, short-time excitation signal into a cable simulation model of the target distribution network cable; acquiring scattered signal parameters of the cable simulation model based on at least one preset signal acquisition port; generating a time-frequency domain optimal excitation waveform corresponding to each scattered signal parameter; and sequentially injecting each time-frequency domain optimal excitation waveform into the cable simulation model to determine the distribution network cable defect corresponding to the cable simulation model. This invention can effectively eliminate interference caused by cable topology, achieve high-sensitivity detection of weak defects, and can be safely implemented without power outages, effectively identifying real defects in the distribution network power supply.