Abstract: A communication networking method applicable to wide-area decentralized charging piles includes: initializing the total number of wide-area decentralized charging piles and coordinate parameters thereof; initializing related parameters of a hybrid learning network, and predicting and judging optimal networking nodes of the charging piles by using the hybrid learning network; and performing connection according to the optimal networking nodes, so as to form a communication network of the wide-area decentralized charging piles. With regard to the communication networking applicable to the wide-area decentralized charging piles, the communication networking method evaluates a channel environment between the wide-area decentralized charging piles, and screens out optimal master nodes according to the quality of a communication environment between the charging piles, so as to form a communication networking scheme of the wide-area decentralized charging piles.

Abstract: Disclosed are a service demand-driven routing scheduling and dynamic selection method and system for active distribution network. The method includes: evaluating a physical importance index and an information importance index of each service traffic according to a physical influence and an information demand of each issued service traffic, comprehensively taking into account the physical importance index and the information importance index to obtain a comprehensive importance index, and ranking the comprehensive importance index to obtain a ranked service traffic set; quantizing the real-time performance and the reliability of a route link and generating a route distance matrix; inputting the ranked service traffic set and the route distance matrix into a route scheduling optimization model, and generating a route scheduling scheme of the overall service traffic based on a principle of service traffic importance and route path performance matching.

Abstract: A multi-time scale voltage control method for an active distribution network is provided. The method comprises: establishing a voltage optimization approach taking into account a large scale of distributed power supplies to realize cooperative dynamic control in case of a voltage violation generated when the distributed power supplies are incorporated into a distribution network; under a long time scale, establishing a voltage control model for controlling a capacitor bank based on voltage sensitivity analysis to realize drastic voltage regulation in case of the voltage violation by means of reactive power compensation; and under a short time scale, establishing a distributed voltage control model, and considering the problem of voltage violation, solving an optimal control strategy online by fully using active and reactive power outputs of the distributed power supplies to realize quick voltage regulation.

Abstract: Disclosed in the present invention is a crystal oscillator based on duty ratio measurement, comprising a first inverter, a resistor, a first load capacitor, a second load capacitor, first to fourth switches, a quartz crystal, a buffer, a sampling and holding module, a first comparator, a second comparator, a phase conversion module, a digital control module, and an energy injection module. One end of the quartz crystal is used for signal injection, a signal at the other end of the quartz crystal is sampled and processed, information representing phase error accumulation, i.e., a signal of which the duty ratio is continuously changing, is obtained by means of the first comparator, and finally the duty ratio is measured by means of the phase conversion module and the second comparator, so as to obtain an accurate moment of phase switching.

Abstract: Disclosed in the present invention is a crystal oscillator based on duty ratio measurement, comprising a first inverter, a resistor, a first load capacitor, a second load capacitor, first to fourth switches, a quartz crystal, a buffer, a sampling and holding module, a first comparator, a second comparator, a phase conversion module, a digital control module, and an energy injection module. One end of the quartz crystal is used for signal injection, a signal at the other end of the quartz crystal is sampled and processed, information representing phase error accumulation, i.e., a signal of which the duty ratio is continuously changing, is obtained by means of the first comparator, and finally the duty ratio is measured by means of the phase conversion module and the second comparator, so as to obtain an accurate moment of phase switching.

Abstract: An electric-thermal integrated energy control method is provided. The method comprises predicting renewable energy and multivariate loads in an integrated energy system based on a pretrained SA-PSO-BP neural network; constructing an objective function of the integrated energy system, and adding power network constraints and heat network constraints for optimal scheduling; and obtaining an optimal solution of the objective function by means of a SA-PSO algorithm based on prediction results of the renewable energy and the multivariate loads, and controlling the integrated energy system according to the optimal solution of the objective function; wherein, a training process of the SA-PSO-BP neural network comprises: training a BP neural network by means of a feature training set, and iterating and updating weights and thresholds in the BP neural network in the training process by means of the SA-PSO algorithm to obtain the SA-PSO-BP neural network.

Abstract: An image defogging method based on dark channel prior is provided, including: acquiring a dark channel image and a light channel image of a haze weather image according to a haze weather image; selecting pixel values in the light channel image and calculating an atmospheric light value A; obtaining a transmittance image based on the light channel image and the atmospheric light value A; obtaining a restored image of defogging based on the transmittance image and the atmospheric light value A. By using the pixel values of the light channel to distinguish whether pixel points comply with the dark channel prior, calculating the transmittance of image areas that comply with the dark channel prior and those that do not, so as to avoid the situation where the image defogging effect is not good due to inaccurate transmittance estimation, making the defogging of images containing high brightness areas more clear.

Abstract: The present invention discloses a method for constructing an intelligent computation engine of an artificial intelligence cross-platform model based on knowledge self-evolution. The method comprises: determining source and target moments; dividing a discrete manufacturing system data set; initializing a dynamic discrete manufacturing system model; preprocessing data and constructing a task pool; constructing a meta learning framework; migrating a trained neural network to new tasks; iterating until convergence and storing model parameters; and testing in a new environment. This invention shortens the convergence time of model parameters, significantly benefiting the training of dynamic discrete manufacturing models subject to temporal disturbances in actual production.

Abstract: Parameter optimization method for nonlinear vibration model of complex device, comprising: 1) constructing various structures of complex device into tree structure, to form tree-shaped complex device model subsystem, and carrying out sign convention for dynamic analysis; 2) establishing complex device dynamic model to obtain dynamic relationships among all parts of complex device; 3) according to contact and collision conditions in advancing process of physical complex device, adding constraint relationships among parts in dynamic simulation software; 4) on basis of dynamic simulation software, establishing virtual prototype model of complex device, and determining target parameter and optimization target; 5) simulating vibration characteristics of complex device for different levels of pavement spectrums and different vehicle speeds; 6) adding required input point and output point for virtual prototype model; 7) on basis of optimization algorithm of numerical solution in small sample deep learning, obtaining

Abstract: A multi-inductor common-ground on-chip millimeter wave single-pole double-throw radio frequency switch is provided. The radio frequency switch includes a first radio frequency port, a second radio frequency port, a third radio frequency port, a first switch arm and a second switch arm. Access points of output matching circuits in the two switch arms are respectively connected with a first compensation inductor and a second compensation inductor. The first compensation inductor, the second compensation inductor, and a first coupling inductor connected with the first radio frequency port are multiplexed to be grounded to a second coupling inductor.

Abstract: A monolithic optoelectronic integrated circuit is provided, including: a substrate including photonic integrated device region and a peripheral circuit region; a first GaN-based multi-quantum well optoelectronic PN-junction device including a first P-type ohmic contact electrode and a first N-type ohmic contact electrode; and a first GaN-based field-effect transistor, where the first GaN-based field-effect transistor includes a first gate dielectric layer disposed on the surface of the substrate and having a first recess, a first gate filled within the first recess, and a first source and a first drain that are disposed the opposite sides of the first gate, where the first source is electrically connected to the first P-type ohmic contact electrode, the first drain is configured to be electrically connected to a first potential.

Abstract: A universal test chiplet for testing a plurality of chiplets to be tested is provided. The universal test chiplet includes a chiplet test control circuit module, a test data distribution circuit module, a memory test configuration circuit module, and a chiplet test interface circuit module. The chiplet test control circuit module is configured to provide test data and configure test modes for the chiplets to be tested. The test data distribution circuit module is configured to distribute the test data required by each of the chiplets to be tested from a test data bus. The memory test configuration circuit module is configured to provide test circuits for memories of the chiplets to be tested and automatically generate a test vector. The chiplet test interface circuit module is configured to transmit the test data to the chiplets to be tested in any direction through chiplet test interfaces.

Abstract: A downlink channel estimation method based on a co-prime array in asymmetric massive MIMO architecture is provided. First, an uplink and downlink asymmetric receiving and transmitting system model based on a co-prime array is established, and a deviation of the frequency domain direction caused by array broadband signals is observed; then, uplink receiving is performed to estimate an uplink channel, and channel parameters such as the number of paths, the angle of arrival and the path gain are recovered; and finally, a downlink channel is reconstructed based on the channel parameters recovered according to the uplink channel. By means of the high angular resolution of the co-prime array, the problem that a recovered uplink channel cannot be directly used for pre-coding of a downlink channel is solved.

Abstract: Disclosed is an intelligent interactive decision-making method for a discrete manufacturing system. The method includes the following steps: step 1, establishing a production scheduling optimization model and strategy for discrete manufacturing for an actual application scene; step 2, training the scheduling strategy with existing production data on the basis of a deep reinforcement learning algorithm, and storing a state having a high reward in a training process in a memory; step 3, updating the state according to prior knowledge in the memory; step 4, inputting the updated state into a deep reinforcement learning network, obtaining a corresponding reward, and updating the memory according to the reward; and step 5, repeating step 4 until model parameters converge, and saving and putting the model into an actual production scene.

Abstract: Disclosed are an indoor non-contact human activity recognition method and system. The method comprises: collecting an indoor reflected signal by using an antenna array; filtering the reflected signal to obtain a noise-removed reflection signal; and inputting the noise-removed reflected signal to a pre-trained human activity recognition model, and determining a human activity category, the human activity recognition model being a pre-trained CNN network model based on a transfer learning algorithm. The recognition method and system have the advantages that: the antenna array is configured for collecting human actions to carry out activity recognition indoors, which can be applied to home-based care scenes; original data is denoised, so that most of high-frequency noises can be removed, and a phase change of the signal is reserved; a CNN structure is adopted for training so as to reduce a complexity of the system location-free sensing.

Abstract: A circuit for post-binding testing of a 2.5D chiplet includes an interposer-dedicated TAP controller, an interposer test interface circuit and a chiplet test output control circuit. A chiplet test configuration register and its corresponding instructions are newly added for the interposer-dedicated TAP controller. The interposer test interface circuit uses an output control signal of the chiplet test configuration register to select the opening or closing of a test signal channel between an interposer and a chiplet. The chiplet test output control circuit uses the chiplet test configuration register to output a control signal for control of a test data output of the chiplet on the interposer.

Abstract: A user matching and power distribution methods for a MIMO-NOMA downlink communication system is provided. The user matching method includes: dividing all users into a strong user group and a weak user group according to a channel gain sorting result; and sequentially selecting a user in the strong user group, calculating a correlation coefficient between the user and each user in the weak user group, selecting a weak user with the highest correlation coefficient as a weak user in a cluster where the strong user is located, and excluding matched users from respective user groups, until the matching between all strong users and weak users are completed. The present invention enables weak users in a cluster to experience less inter-cluster interference in scenarios where the channel correlation between users is relatively low, thereby improving the total throughput of the communication system.

Abstract: A reconfigurable MBIST method based on an adaptive March algorithm is provided. The reconfigurable MBIST method automatically reconfigures different algorithm circuits according to external environment and user instructions to satisfy detection requirements for different faults. The provided adaptive March algorithm is capable of adaptively reorganizing algorithms with different complexities, such that dynamic adjustments can be executed between time complexities of the algorithm and fault coverage rates to achieve a good balance, and the static fault coverage rates are high, thereby effectively improving dynamic fault coverage rates.

Abstract: Disclosed are a three-dimensional modeling system and modeling method based on multimodal fusion. The method includes: separately collecting feedback data of an electroencephalogram sensor, an electromyography sensor, an eye movement sensor, a gesture sensor, and a voice sensor, conducting multimodal fusion on the feedback data, obtaining multimodal-fused model data, matching the model data with a database instruction, obtaining and analyzing an instruction set, obtaining and identifying a relevant modeling parameter, obtaining a modeling method, automatically conducting modeling according to the modeling method, and obtaining a visual entity model.

Abstract: Disclosed is a complex device key position vibration characteristic parameter verification method, comprising following steps: 1) constructing a model of complex device parts; 2) establishing a complex device dynamic model in a simulation software; 3) in the advancing process of a physical complex device, obtaining connection modes and constraint relationships among parts; 4) pre-simulating a complex device model in a dynamic simulation software; 5) determining a vibration characteristic parameter of a complex device key position needing to be verified, and carrying out post-processing on the vibration characteristic parameter for different levels of pavement spectra and vehicle speeds; 6) using a neural network model, training a selected key position rigidity damping coefficient and the vibration characteristic parameter; 7) comparing and verifying the vibration characteristic parameter obtained in the simulation process of the complex device dynamic model with the vibration characteristic parameter obtained