191 results about "Similarity criterion" patented technology

Systems, methods, devices, and computer readable storage media described herein provide techniques for generating and / or repairing query language (QL) queries. In an aspect, an embedding is determined based on a request to generate a QL query. The embedding is compared to a layer embedding(s) of a deep data map to determine a similarity between a layer embedding and the embedding satisfies similarity criteria. A prompt is provided to a large language (LLM) to cause the LLM to generate the QL query, the prompt comprising a description of an item associated with the layer embedding. In another aspect, an alert indicating an undefined variable of the QL query is received. A query embedding associated with the QL query is compared to the layer embedding(s) to determine a candidate variable. The candidate variable is substituted in for the undefined variable, and a response comprising the repaired QL query is generated.

A disclosed method for incident dependency prediction includes identifying, for a newly-occurring network incident of interest, one or more similar historical incidents; obtaining causal dependency data for the one or more similar historical incidents, the causal dependency data identifying one or more historical responsible incidents responsible for causing the similar historical incidents; identifying candidate root cause incidents each occurring within a recent time interval and satisfying similarity criteria with a corresponding one of the one or more historical responsible incidents; and transmitting a prompt to an incident dependency prediction model, the prompt requesting prediction of a root cause incident responsible for causing the newly-occurring network incident of interest based on feature information for each of the candidate root cause incidents and for the incident of interest.

The invention relates to the technical field of fishways, in particular to a fishway overall model test method which comprises the following steps: S1, establishing a fishway overall model design scheme based on a preliminary design scheme; s2, a fishway overall model is manufactured based on the fishway overall model design scheme, the fishway overall model is designed to be a normal model, the fishway overall model is designed according to a gravity similarity criterion, and geometric similarity, water flow motion similarity and dynamic similarity checking is conducted on the fishway overall model design scheme; and S3, performing a fishway overall model test on the basis of the fishway overall model, and optimizing the fishway overall arrangement structure scheme so as to obtain a final fishway overall structure scheme. According to the fishway overall model test method, the fishway overall arrangement structure scheme is optimized, so that the final fishway overall structure scheme is obtained, and a theoretical basis is provided for fishway overall optimization.

A seismic wave identification method based on deep learning comprises the following steps: step 1, acquiring seismic wave signals to obtain original data, and performing center interception and normalization processing to obtain unified signals; 2, decomposing a unified signal by using CEEMDAN to obtain a plurality of orders of intrinsic mode functions and residual components, carrying out coarse graining processing on each order of mode function according to a preset time scale parameter to divide into subsequences, constructing a similarity criterion through a fuzzy membership function, calculating fuzzy entropy values of the subsequences, and integrating the fuzzy entropy values into a feature matrix; and 4, inputting the feature matrix after the dimension reduction into a CTCM-1D-CNN model optimized by a tribe competition and member cooperation algorithm, predicting the type of an output seismic wave, and completing seismic wave identification. Therefore, the design has good seismic wave identification precision and stability.

The invention belongs to the technical field of remote sensing image processing, and particularly relates to a hyperspectral lithology intelligent identification method based on fuzzy clustering, which comprises the following steps: acquiring a geological map of a research area, vectorizing the geological map of the research area, and acquiring initial lithology distribution vector data; preprocessing the hyperspectral data; performing data dimension reduction on the preprocessed hyperspectral data by using principal component analysis transformation to obtain dimension-reduced data; clustering the dimension-reduced data by adopting a spatial fuzzy C-means clustering algorithm, and segmenting a clustering result based on a neighborhood similarity criterion to obtain the clustering result; and according to the initial lithology distribution vector data, determining the lithology category with the maximum proportion in different clustered patches from the clustering result, and taking the category as the lithology category corresponding to the clustered patches to obtain an intelligent lithology identification result. According to the method, the influence of human interference factors can be effectively reduced, and the lithology identification precision and the mineralization-related geological element identification capability are improved.

The invention discloses a wind tunnel-pool combined loading floating fan distributed hybrid test method, which comprises the following steps of: establishing a floating fan multi-body / multi-physical field collaborative reduced scale criterion, dividing a floating fan into two independent physical models and two independent numerical models, and placing the two independent physical models and the two independent numerical models in different laboratories; integrating a physical model, a numerical model, a loading system and a measurement system, and building a floating fan physical-numerical distributed hybrid test platform; and carrying out data interaction and closed-loop control on the physical-numerical hybrid test platform. A fan and a floating platform are adopted as two relatively independent test substructures, test loading or computer simulation can be carried out in different laboratories by establishing different similarity criteria and geometric scale ratios, a collaborative online test and pneumatic-hydrodynamic load loading under the coupling action of wind, waves and flow are carried out through network interaction data, and the test efficiency is improved. The technical problems of environment load high-precision simulation and dynamic coupling response in a reduced scale model test are solved.

An audio output device case includes a display device. While the display device is disabled, the display device and an exterior of the audio output device case meet similarity criteria. The audio output device case detects an occurrence of a first event. In response to detecting the occurrence of the first event and in accordance with a determination that the display device is disabled, the display device is enabled. A dynamic visual element corresponding to the first event is displayed via a first portion of the display device. The dynamic visual element changes over time. While the display device is enabled, a second portion of the display device, distinct from the first portion of the display device, and the exterior of the audio output device case meet the similarity criteria.

The invention discloses a daily load curve clustering method based on a mixed distance improved FCM algorithm, and belongs to the technical field of data processing, and the method comprises the steps: collecting daily load data of a user at a sampling frequency of 5 minutes, carrying out the corresponding data preprocessing, analyzing the fluctuation characteristics of a daily load curve, and carrying out the clustering of the daily load curve; euclidean distance representing load curve power amplitude information and cosine distance representing load curve power fluctuation direction information are constructed respectively, and then an entropy weight method is adopted to construct a hybrid similarity distance (HSD) fusing the Euclidean distance and the cosine distance as a similarity criterion between daily power load curves; replacing the Euclidean distance in the FCM algorithm with the constructed HSD, then calculating a corresponding membership degree and a clustering center, iteratively updating the membership degree and the clustering center by using a target function based on an intra-class error weighted quadratic sum, and completing daily load curve clustering according to a preset maximum iteration number; and finally, determining the optimal clustering number and the corresponding optimal daily power load curve clustering result by using the sum of intra-class errors (SAE), thereby effectively solving the prominent problems of poor effect, low efficiency and the like of the traditional power load curve clustering method.

A method for verifying a user agent includes transmitting, by a core node, to a user agent, a predefined set of user requests. For each user request in the predefined set of user requests, the core node receives an embedding generated based on the user request, thereby receiving a plurality of embeddings based on the predefined set of user requests. The core node determines whether the plurality of generated embeddings satisfy a similarity criterion. The core node transmits, to the user agent, a task to generate a query plan and receives a query plan generated by the user agent for processing a user request identified in the task. The core node determines whether the query plan satisfies a query plan criterion, thereby producing query plan adequacy output. The core node determines whether to approve the user agent based on the similarity output and the query plan adequacy output.

The invention provides an adaptive image enhancement method and system based on a magnetic resonance imaging (MRI) image, and relates to the technical field of image processing, and the method comprises the steps: obtaining a global gradient map of the MRI image, and extracting an initial seed point set from the global gradient map according to a preset condition; gridding is carried out on the MRI image, and gradient information of the global gradient map is mapped to each block formed by gridding; calculating the comprehensive weight of each initial seed point in each block, screening the seed points according to a preset weight threshold value, and determining growth seed points in each block; for all the blocks, based on a set similarity criterion, carrying out region parallel expansion from the growth seed point, and terminating when the expansion meets a stop condition; when the adjacent blocks are overlapped, the adjacent blocks are combined, and the enhanced MRI image is finally output, so that the contrast ratio and the definition of the image are improved while the detail and edge information of the image are reserved.

The invention discloses a landslide surge physical model test drag force prediction method based on AM-LSTM, and the method comprises the steps: constructing a three-dimensional hydrodynamic coupling physical model of landslide surge for a target landslide region and a hydraulic structure structure based on Froude similarity criterion, and carrying out the prediction of the drag force of the landslide surge. The method comprises the following steps: acquiring dynamic data of dam surface drag force by setting test groups with different landslide mass volumes and water depths, constructing a data set containing time sequence features, performing normalization preprocessing, and dividing the data set into a training set, a test set, a feature data set and a label data set; a long short-term memory neural network LSTM layer and an attention mechanism AM layer are introduced, data are input for training, a long short-term dependency relationship between the data is captured, dynamic prediction of drag force is realized, and result visualization is performed. According to the method, the towing force sequential evolution rule caused by landslide surge is captured through the LSTM model with the attention mechanism, dynamic prediction of the towing force is realized, and the prediction accuracy is improved.

The invention discloses a tunnel-pile interaction experiment method and device based on a 3D printing technology, and belongs to the technical field of civil engineering underground structure tests. The method comprises the steps that the geometric and mechanical similarity ratio is determined according to an engineering prototype, a tunnel lining model and a pile group model are prepared through the 3D printing technology, and controllable adjustment of the rigidity of the tunnel model is achieved by adjusting the type, the filling rate and the internal structure of a printing material; controllable adjustment of the rigidity of the pile foundation model is realized by adjusting the size of the magnetic field; the model is placed in a soil body groove, the shield tunnel excavation process is simulated, and deformation data of a tunnel and a pile foundation are collected through a PIV technology and a sensor. Accurate control over the rigidity of the tunnel and pile foundation model is achieved through 3D printing, the influence of shield tunnel construction on the pile group foundation can be simulated under the condition that the similarity criterion is met, and the device has the advantages of being adjustable in structure, high in experiment efficiency and the like and can be used for researching a dense urban area tunnel-pile deformation coupling mechanism and optimizing related engineering parameters.

The invention relates to the technical field of icing wind tunnel tests, in particular to a propeller icing wind tunnel test working condition similarity matching method and a storage medium. A first calculation model is established based on a forward ratio similarity criterion of a propeller and a first similarity criterion, and a second calculation model is established based on a plurality of set similarity criteria. Then, basic parameters of the target propeller are obtained, and the basic parameters comprise the size of the target propeller, the first angular speed, the first incoming flow wind speed and the scaling ratio of the icing wind tunnel test on the target propeller; and inputting the first angular velocity and the scaling proportion into a first calculation model to obtain a scaled second angular velocity. And finally, inputting the basic parameters and the second angular velocity into a second calculation model to obtain test working condition parameters of the target propeller in the icing wind tunnel test. Therefore, the design period of similar matching of the propeller icing wind tunnel test working conditions is shortened, and the quality of the scaled test working condition data is ensured.

The invention provides a bridge deck reduced scale model design method and experiment system in a plateau environment, and the design method comprises the steps: building a multi-factor coupling similarity criterion based on a similarity principle, physical parameters affecting the prototype structure performance of a bridge deck, and plateau environment parameters; determining a dynamic stress similarity ratio model based on a multi-factor coupling similarity criterion and the plateau environment parameters; based on the dynamic stress similarity ratio model and the section shape and size of the bridge deck prototype structure, performing scale design on the bridge deck prototype structure to obtain an initial scale model; and performing simulation experiment and simulation verification on the initial scale model based on a preset numerical simulation strategy and a preset plateau environment simulation strategy, and performing parameter optimization of the dynamic stress ratio similar model to design a target scale model. According to the scheme provided by the invention, experimental simulation of the bridge deck in the plateau environment can be efficiently and accurately carried out, and the experimental simulation cost is reduced.

The invention discloses a long flexible blade reduced scale model design method suitable for a large fan wind tunnel experiment. The method comprises the following steps: selecting a reasonable similarity criterion, selecting a section airfoil of a model blade, optimizing the distribution of chord length and torsion angle in the length direction of the blade, and optimizing a model rotor variable pitch control strategy; the design objectives that the thrust coefficient of the reduced-scale model rotor in the experimental wind speed range is equal to that of the original-size fan rotor in the corresponding original-size wind speed range, and the first-order inherent frequency in the flapping and shimmy directions of the blades of the reduced-scale model is equal to that of the original-size blades are achieved, and the long flexible blade reduced-scale model is provided for a large-scale fan wind tunnel experiment. According to the method, the first-order inherent frequency of the flapping and shimmy directions of the model blade and the blade of the original size is equal, the thrust coefficients are equal under multiple working conditions, the wind tunnel experiment similarity criterion is met, different airfoil choices are appointed for different design control sections, and the method has high optimization solution efficiency.

The present invention proposes a method for preparing jointed rock samples based on three-dimensional scanning and 3D printing. The present invention uses a handheld three-dimensional scanner to perform multi-section scanning on the jointed rock sampled on site, obtains the spatial relative position of the cross-section joint fissures, reconstructs and partitions the three-dimensional model, and simulates and produces jointed rock samples based on the partitioning situation and the gaps between printed materials of different particle sizes based on the similarity ratio criterion to characterize the joint fissure situation, and then simulates the weakening effect of the filling in the joint fissures on the jointed rock under different confining pressure conditions through a weak filling migration simulation device. Through this method, samples of jointed rock containing fillings under different confining pressure conditions are simulated and produced, which provides a new idea for the study of the mechanical properties of rocks and a new method for artificially restoring the internal structure of jointed rock masses.

The invention discloses an image recognition system for marking the appearance of a mobile phone. The system obtains an area of ​​interest marked on the appearance of a mobile phone by a user, wherein the area of ​​interest is a subset of an image to be detected, and is a partial area extracted from the image, and the partial area is composed of a plurality of irregular shapes. The image to be detected is segmented into two or more non-overlapping areas according to a similarity criterion of preset grayscale, color, texture and shape features. The areas segmented from the image are used as target objects for subsequent feature extraction according to connected components, and the two-way components are pixels connected together according to preset rules in a binary image. The mapping relationship of data from input to output is obtained, and the best mapping function for reflecting the target task is found through training. High-dimensional abstract features are used to represent low-dimensional target features. A network training module includes a convolution layer and a pooling layer. Different data amplifications are used to increase the data volume, so that data samples are richer and the precision and accuracy of defective part extraction are improved.

There is provided a technique of computerized substituting an odor item of interest in a formula of a smell. The method comprises: generating for a given inventory of odor items a dataset informative, at least, of similarity of the pairs of odor items of interest with other odor in the inventory; processing data in the generated dataset to reveal one or more odor items meeting one or more similarity criteria, thereby generating one or more candidate odor items; and applying to the one or more generated candidate odor items an optimization algorithm to find, among them, a candidate odor item with the best fit to the formula of the smell. The resulting odor item is usable for substituting the odor item of interest in the formula of the smell. Similarity labels in the dataset can be provided with the help of a plurality of labeling functions applied to the pairs of odor items.

The invention relates to the technical field of dam foundation treatment, and discloses a low-liquid-limit clay dam foundation soil body excavation tedding thickness calculation method, which comprises the following steps: firstly, collecting an undisturbed soil sample and a disturbed soil sample, and obtaining physical and mechanical parameters through an indoor test; performing a light compaction test by using the disturbed soil sample, and calculating a first soil layer compaction coefficient according to the height change before and after compaction; an indoor dynamic compaction physical model meeting the similarity criterion is constructed based on the white Jinhan Pi theorem, the conversion relation between model compaction energy and on-site compaction energy is deduced through a geometric similarity coefficient, a time similarity coefficient and a quality similarity coefficient, and a second soil layer compaction coefficient is measured; and the maximum value of the two compaction coefficients is taken as a final calculation parameter, and the excavation tedding thickness is calculated in combination with the design thickness of the dam foundation bearing stratum. According to the method, the indoor test is used for replacing field trial compaction, so that the test cost is reduced, two measurement schemes of a compression modulus method and an accumulated compaction settlement method are provided, and the calculation result is more in line with engineering practice.

To provide a system and method for implementing multi-sourced machine learning (ML) model-based AI character training.SOLUTION: A method includes: receiving interaction data; identifying an action, as well as personality profiles corresponding respectively to multiple participant cohorts; generating an interaction graph with respect to the behavior of the multiple participant cohorts in the action; simulating, using a behavior model, participation of each of the participant cohorts in the action to provide a predicted interaction graph; comparing the predicted and generated interaction graphs to identify a similarity score for the predicted interaction graph relative to the generated interaction graph; when the similarity score satisfies a similarity criterion, training, using the behavior model, an artificial intelligence character for interactions; and when the similarity score fails to satisfy the similarity criterion, modifying the behavior model based on one or more differences between the predicted and generated interaction graphs.SELECTED DRAWING: Figure 3A

A set Kalman filtering turbulence model assimilation method based on full field similarity criterion is disclosed, which comprises the following steps: sensitivity analysis is performed on the coefficients of the candidate turbulence model to obtain sensitive coefficients and their sampling range for Latin hypercube sampling, i.e., sampling interval; model constant sample combinations are extracted from the sampling interval by using a directional Latin hypercube sampling method, and target flow field results are calculated; a data assimilation algorithm based on the set Kalman filtering algorithm is used for the target flow field results and the model constant sample combinations, and after obtaining the optimized model constant combination, the model constant combination is updated and verified in cycles to obtain the optimal model parameter combination; finally, the improved turbulence model is used to simulate the internal flow field of the fuel assembly in the core of the pressurized water reactor with high similarity. The present application can provide an objective evaluation standard for the full physical field similarity of the data assimilation method, significantly improve the convergence speed of the algorithm, strengthen the robustness of the algorithm, and reduce the calculation cost of the algorithm.

A system and method for protecting ranging by feedback of at least one channel metric. The method can include receiving, by a first modem, a first training signal from a second modem, generating, by the first modem, a first estimate of a channel metric based on the first training signal, receiving, by the first modem, a second estimate of the channel metric from the second modem, determining, by the first modem, that the first estimate of the channel metric and the second estimate of the channel metric do not meet a similarity criterion, and denying, by the first modem, access to a resource.

The invention provides a method for constructing a bearing test distortion model of an ice-resistant structure under the action of a dynamic ice load, and belongs to the field of test similar reduced scale model design under an ice breaking load of the ice-resistant structure. The problem that in the prior art, the strain rate of a fully-similar model is dissimilar due to the scale effect is solved; a traditional distortion model design method has the problem of dissimilar energy distribution. The method comprises the following steps: establishing a fully similar model from an ice-resistant structure prototype to a geometric and plate thickness equal ratio reduced scale; establishing a plate thickness distortion reduced scale model by using the same material on the basis of the geometric similar reduced scale model; preliminarily determining a collision contact position of the thickness distortion reduced scale model; a dynamic ice load similarity criterion is applied, correction factors are deduced through dimensional analysis, and ice body parameters and collision speed of a distortion model system are adjusted, so that the ice breaking capacity and dynamic structure response are similar to those of a prototype system. The device is mainly used in the field of polar region icebreaking.

The invention discloses a seaplane wave sliding load spectrum compilation method. The method comprises the steps of determining gravity center acceleration data of pool test data of each task section according to overall and structural parameters of a seaplane; comparing a gravity center acceleration time history curve representing the gravity center acceleration data with an airframe trim angle time history curve, and intercepting stable section data of each task section; performing power spectrum density analysis on acceleration overload / overload increment in the stable section data to obtain an acceleration characteristic frequency band; determining a cut-off frequency according to the acceleration characteristic frequency band, and filtering the stable section data; carrying out accumulated transcendental statistics on the filtered stable section data to obtain an accumulated transcendental curve of each task section; according to the time proportion of each task segment and the similarity criterion, obtaining an accumulative surpassing curve of each task segment of the real machine water surface operation; and forming a body wave sliding equivalent spectrum according to a damage equivalence criterion. The technical problem of compiling and verifying the water skiing fatigue load spectrum of the seaplane is solved.

The application discloses a kind of wave energy device whole process model test similarity criterion coordination method, specifically relates to wave energy generation and electrochemical energy storage field, specific steps are as follows: identifying multistage energy conversion process;Determine the dominant similarity criterion of each stage energy conversion process;Similarity criterion coordination;Introduce correction coefficient;Data acquisition and correction coefficient calculation;Back calculation prototype performance.The application is through the virtual and real complementation mode of numerical simulation and physical model test, in whole process test, all physical phenomena are considered and tested simultaneously, the behavior and performance of complete system under actual conditions can be directly observed, the problem of uncoordinated similarity criterion encountered in the whole process model test is solved, the accuracy of back calculation prototype performance of physical model test is improved, the characteristics of prototype device can be evaluated using limited test, the efficiency of model test is improved, and the development cost of device is reduced.

A method is implemented for automatically labelling images at a computer system having one or more processors and memory. The computer system obtains a first image including an object, e.g., from a camera disposed at a physical environment. A reference model is applied to process the first image and generate a reference label, e.g., identifying the object in the first image. An image generative model is applied to generate a reference image based on the reference label. In accordance with a determination that the first image and the reference image satisfy a similarity criterion, the computer system labels the first image with the reference label. The first image that is labelled with the reference label is added to a corpus of training data to be used to generate a target model for autonomously monitoring the physical environment.

The invention discloses a method and system for processing ground surface settlement monitoring data, and relates to the technical field of tunnel monitoring data processing, and the method comprises the steps: collecting the ground surface settlement monitoring data of each measuring point, and carrying out the outlier recognition and processing; extracting a feature image of the monitoring data of each measuring point by adopting a Mel-frequency cepstrum coefficient feature extraction method, and converting the ground surface settlement monitoring data into an MFCC feature map; the MFCC feature map is input into a pre-trained MFCC-Transform model for data classification, and measuring point data affected by tunnel excavation construction are reserved; an improved ELM time sequence prediction algorithm is adopted to fill data missing values; and decomposing the monitoring data into a plurality of intrinsic mode functions (IMF) by adopting a VMD time sequence decomposition algorithm, and selecting the IMF with the highest similarity as the monitoring data after noise reduction in combination with a similarity criterion. According to the invention, the full-automatic processing of the ground surface settlement monitoring data is realized, and the reliability of data processing is ensured while the data processing speed is improved.

The application provides a low-rank parameter update denoising method and system for continuous learning, comprising: for any pre-training model, obtaining original update parameters by training on a current task using low-rank self-adaption; obtaining left singular vectors of the update parameters as candidate subspace basis vectors by singular value decomposition; defining a subspace similarity scoring function based on Grassmann manifold to calculate the alignment degree of the update subspace and the pre-training model base subspace; automatically screening and retaining key components according to the highest similarity criterion, eliminating noise interference components, and reconstructing the denoised update parameters; and updating the model in an incremental or staged manner using the denoised update parameters. The application effectively balances the plasticity and memory of old knowledge of the model on a new task by removing noise components in the low-rank self-adaptive training update, and significantly alleviates the catastrophic forgetting problem in continuous learning.

The invention relates to the technical field of physical similar simulation, and particularly provides a physical simulation method for a lunar lava tube structure forming process, which comprises the following steps of: mixing a thermoplastic material and a condensation additive to prepare a simulation melt meeting a basalt lava rheology and thermodynamics similarity criterion; the low gravity effect, the high vacuum environment and the radiation cooling condition in the lunar environment are reproduced through an inclined flow channel and a thermal vacuum cavity, and the injection rate, the flow channel inclination angle and the target environment temperature of the simulated melt are determined by accurately matching dimensionless parameters such as the Peclet number, the dimension temperature and the Rayleigh number; under the condition, controlled flow and surface solidification crusting of the melt are simulated, and finally a cavity structure model is formed, so that physical research on the lunar lava tube structure forming process is realized. According to the method, the lava flow dynamic crusting and cavity forming process in the extreme lunar environment can be accurately reproduced, and a quantitative experimental data basis is provided for formation mechanism research and engineering application of the lunar lava tube.

This invention relates to the field of physical similarity simulation technology, specifically providing a physical simulation method for the formation process of lunar lava tube structures. The method involves preparing a simulated melt that meets the rheological and thermodynamic similarity criteria of basaltic lava by mixing thermoplastic materials with condensation additives. The low-gravity effect, high-vacuum environment, and radiative cooling conditions under lunar conditions are reproduced using inclined flow channels and thermal vacuum cavities. By precisely matching dimensionless parameters such as Peckley number, dimensional temperature, and Rayleigh number, the injection rate, flow channel inclination angle, and target ambient temperature of the simulated melt are determined. Under these conditions, controlled melt flow and surface solidification crust formation are simulated, ultimately forming a cavity structure model. This allows for the physical study of the formation process of lunar lava tube structures. This invention can accurately reproduce the dynamic crust formation and cavity formation process of lava flow under extreme lunar conditions, providing a quantitative experimental data basis for the study of the formation mechanism of lunar lava tubes and their engineering applications.