55results about How to "Fully analyzed" patented technology

The invention belongs to the technical field of underwater acoustic signal processing, and particularly relates to an underwater acoustic signal target classification and recognition method based on deep learning. The method comprises the following steps: (1) carrying out feature extraction on an original underwater acoustic signal through a Gammatone filtering cepstrum coefficient (GFCC) algorithm; (2) extracting instantaneous energy and instantaneous frequency by utilizing an improved empirical mode decomposition (MEMD) algorithm, fusing the instantaneous energy and the instantaneous frequency with characteristic values extracted by a GFCC algorithm, and constructing a characteristic matrix; (3) establishing a Gaussian mixture model GMM, and keeping the individual characteristics of theunderwater acoustic signal target; And (4) finishing underwater target classification and recognition by using a deep neural network (DNN). According to the underwater acoustic signal target classification and recognition method, the problems that a traditional underwater acoustic signal target classification and recognition method is single in feature extraction and poor in noise resistance can be solved, the underwater acoustic signal target classification and recognition accuracy can be effectively improved, and certain adaptability is still achieved under the conditions of weak target acoustic signals, long distance and the like.

The invention discloses an extra-high voltage transmission line loss prediction method based on a quantum ant colony optimization RBF network, and belongs to the technical field of combination of an electric power system and deep learning. The method comprises the following steps: (1) preprocessing data; (2),establishing a characteristic index system; 3, determining a neural network structure; (4)optimizing connection parameters of a network output layer by a quantum ant colony algorithm; (5) training the neural network by using an alternate optimization mode; (6) predicting the extra-high voltage line loss value, and analyzing the prediction model. According to the invention, by use of a neural network calculation mode, various nonlinear relationships are easy to fit, calculation detailsdo not need to be manually controlled when the relationship between input parameters and line loss is found, and use is simple; the RBF neural network is used for guaranteeing that the training speedis high, the local approximation characteristic is achieved, and the calculation process is simple; the quantum ant colony algorithm is introduced into the optimization process of the neural network,and the problem that the optimization of the neural network is easy to fall into the local optimal solution is improved.

The invention provides a PDS three-dimensional model analysis and reconstruction method. The method involves a model analysis module and a model reconstruction module. The model analysis module comprises a DGN file element acquisition module (S11), an information extraction module (S12) and an information writing module (S13). The model reconstruction module comprises an assembly file creation module (S21), an information analysis module (S22) and a model reconstruction module (S23). According to the PDS three-dimensional model analysis and reconstruction method provided by the invention, geometric information and attribute information of a DGN three-dimensional model can be analyzed and the DGN three-dimensional model is reconstructed into an accurate model in other format, so that a user can perform accurate virtual simulation verification and display on a PDS model by using virtual reality software.

The invention discloses a SDN-based Internet of Things data forwarding system, and belongs to the control application field of the SDN network traffic. The system comprises an Internet of Things equipment layer, an OpenFlow switch layer, a SDN control layer, a REST API abstract layer, an Internet of Things client layer. After the Internet of Things data is collected, the system firstly classifies the data in the Internet of Things, and then performs secondary processing on pointedly according to the classification result, the data after the secondary processing is sent to a priority controller to judge the priority, and the data is forwarded according to the network environment. The SDN is combined with the forwarding of the Internet of Things data, the data forwarding is pointedly performed according to the features of the Internet of Things data while processing large-scale Internet of Things data; the utilization efficiency of the network is improved, the robustness of the network is guaranteed, and the system has actual application value.

The invention discloses an interface unit for a fully homomorphic encryption chip. The interface unit comprises an encryption interface, a decryption interface and a cipher text operation interface. The encryption interface is used for encrypting data of a data owner to generate cipher texts and transmitting the cipher texts to a data processor. The cipher text operation interface is used for receiving the cipher texts from the data processor to operate the cipher texts and transmitting the operated cipher texts to the data owner. The decryption interface is used for receiving the operated cipher texts from the data owner, decrypting the cipher texts to generate plain texts, and transmitting the plain texts to the data owner. The encryption interface comprises a first integer sub-interface and a first real sub-interface, wherein the first integer sub-interface is used for encrypting plain text integers and plain text unsigned integers, and the first real sub-interface is used for encrypting plain text real numbers, plain text floating numbers, plain text double-precision floating numbers and plain text format real numbers. The interface unit for the fully homomorphic encryption chip can complete arithmetic operation, relation comparison operation and logical operation under encryption and can guarantee information safety.

The invention provides a long-range rocket launching initial state error spreading estimation method, and relates to the long-range rocket launching initial state error spreading estimation method. The method aims at solving the problems that the calculation efficiency of burnout point position deviation, speed deviation, landing point longitudinal deviation and transverse deviation is low due to the existing launching initial state error, so that the spreading mechanism of the launching initial state error in the trajectory design process cannot be sufficiently analyzed. The goal of the method is achieved through the following technical scheme that the method comprises the following steps of: 1, building a kinetics perturbation equation; 2, solving long-range rocket thrust acceleration deviation, pneumatic acceleration deviation, normal gravitational acceleration deviation, Coriolis acceleration deviation and centrifugal acceleration deviation; and 3, obtaining similar analytical solutions of the burnout point position deviation and the speed deviation due to the long-range rocket launching initial state error and similar analytical solutions of the landing point longitudinal deviation and transverse deviation according to the first step and the second step. The method is applied to the field of long-range rocket or carrier rocket flight dynamics.

The invention provides an intelligent contract fuzzy test method and device, and a storage medium, relates to the technical field of block chains, and is used for improving the security of an intelligent contract in a block chain and avoiding unnecessary loss. AST scanning analysis is carried out on the intelligent contract to generate an intelligent contract method protocol; in combination with an intelligent contract method protocol, mutation operation is carried out on the test case sample to generate test case mutation data, and the test case mutation data comprises a method name of the tested intelligent contract and a test case mutation sample; the method also includes requesting the test case variation data to a blockchain service, and determining a tested smart contract in the blockchain service according to the method name of the tested smart contract; and executing the test case variation sample on the tested smart contract, and collecting an execution result of the tested smart contract for the test case sample so as to determine a vulnerability of the tested smart contract according to abnormal data in the execution result.

The invention discloses a multi-round dialogue method and device based on dialogue state prediction, computer equipment and a storage medium, and the method comprises the steps: obtaining the (i + 1)th round of voice inputted by a user after the i round of dialogue with the user; performing speech recognition processing on the (i + 1) th round of speech to obtain an (i + 1) th round of text; judging whether the (i + 1) th round of text triggers a dialogue state generation condition or not; if the preset dialogue state generation condition is not triggered, performing dialogue state predictionby adopting p preset dialogue state prediction tools to obtain p predicted dialogue states; if the p predicted dialogue states are the same, updating the current state of the multiple rounds of dialogues to the predicted dialogue state, and obtaining the (i + 1) th round of reply voice according to the preset corresponding relationship between the dialogue state and the reply voice; and outputting the (i + 1) th round of reply voice by adopting a preset voice output device. Therefore, the generalization ability of the multi-round dialogue scheme is improved, and the fluency is ensured.

The invention relates to an optimal driving voltage selection method taking translation interaction efficiency as an index, and belongs to the field of human-computer interaction. An electrostatic force tactile feedback device is used; translation gesture interaction efficiency experimental data under two conditions of electrostatic force tactile feedback and electrostatic force tactile feedback are obtained, and a matrix is constructed; A kernel principal component analysis method is used for calculating a kernel matrix and obtaining corresponding kernel feature spaces, quantitative evaluation of the influence of electrostatic force tactile feedback on translation interaction efficiency is achieved by calculating the distance between the two kernel feature spaces, and the method is used for selecting the optimal driving voltage of the electrostatic force feedback device with the translation interaction efficiency as an index. The influence degree of electrostatic force tactile feedback on translation interaction efficiency can be quantitatively evaluated, the data theory is fully analyzed, and the obtained conclusion is high in universality; The method can also be expanded to quantitative evaluation of the influence of different electrostatic force touch driving modes on the gesture interaction performance, and is easy to popularize and apply.

The invention provides a JSON character string processing method and device. The method comprises the steps that of conducting deserialization processing is conducted on a JSON character string to extract a bottom layer element in the JSON character string, and the bottom layer element comprisinges a bottom layer key name and a corresponding first key value; for each underlying element in the underlying elements, generating an index of the underlying element based on the underlying key name of the underlying element; and generating structured data based on the generated index of each underlying element and the corresponding first key value. By utilizing the method disclosed by the invention, the JSON character string can be stored in a structured manner, so that subsequent loading and use are facilitated.

The invention discloses a dependent component information extraction method and device and a computer readable storage medium. The dependent component information extraction method comprises the steps of obtaining a to-be-detected package manager configuration file list; for each configuration file in the configuration file list, intercepting a part of text segments related to the dependency declaration, and performing matching by using a regular expression to obtain component information of a component directly dependent on the configuration file; based on the component information of the direct dependent component, obtaining the component information of the indirect dependent component by searching a component dependent knowledge base; and displaying the component information of the direct dependent component and the component information of the indirect dependent component. By the adoption of the invention, text analysis depending on the configuration file can be achieved, dependence constraints such as a local private warehouse environment and a network environment are eliminated, constraints of analysis commands of an existing package manager are eliminated, the dependence relation of components can be completely analyzed, and the hierarchical structure of a project module can be completely analyzed.

The invention relates to a tea processing technology. The tea processing technology comprises the steps that picked fresh green tea leaves are cleaned thoroughly and then are dried at the temperature of 80-100 DEG C for 5-10 minutes; the dried tea leaves are immersed in ethanol with the mass concentration 55-65% for 5-10 seconds and then are taken out, then the tea leaves are transferred into an ultrasonic processor to undergo ultrasonic processing under the conditions of 15-60 KHZ and 80-150 w for 10-15 minutes; ultrasonically processed tea leaves are transferred into a frying pan, tea oil and salt are added, the addition amount of the tea oil is 10-20% by weight of the tea leaves, the addition amount of the salt is 5-10% by weight of the tea leaves, the tea leaves are stir-fried at the temperature of 100 DEG C for 10-20 minutes, and then the tea leaves are taken out of the pan and cooled. The tea processing technology is simple, a production cycle is short, the whole process only needs 25-45 minutes, the produced tea leaves can be rapidly brewed with warm water or cold water, can be directly eaten or eaten after being soaked and well meets the travel and outgoing demands of people.

The invention belongs to the technical field of big data, and provides a distributed database monitoring method and device based on full-link monitoring, and the method comprises the steps of responding to a transaction request, and generating a link corresponding to the transaction request; collecting information of links and operation indexes of the distributed database; generating a topological relation corresponding to the link according to the information and the operation index; and monitoring the distributed database according to the topological relation. According to the invention, from the perspective of SQL analysis, operation and maintenance personnel can be helped to find that links which consume long time can be associated when overall query of a certain SQL is slow, then drill-down analysis is carried out, a typical link is found through a plane and a line, then the line and a point are carried out, and therefore the reason of the slow SQL link is analyzed.

The invention discloses a processing technology of picked fresh tea.The processing technology comprises the following steps that 1, the picked fresh tea is spread until a moisture content of the tea is 65-75%; 2, the tea obtained in the step 1 is placed in a pesticide degradation device to degrade residual pesticides, then the tea is dried after washed, the dried tea is immersed in ethanol and ultrasonically processed for 6-8minutes; 3, the tea obtained in the step 2 is dried and the dried tea is put into a fresh bamboo tube for aerobic fermentation; 4,the tea after fermentation processing is rolled by a rolling machine; 5,the rolled tea is put into a steam-hot fixation machine to be fixed for three times; 6, after fixation is completed, the tea is transferred to a deblocking machine to be scattered, and after deblocked, the tea is put into a dryer to be dried and taken out until the moisture content of the tea is 20-30%; 7,the tea is spread and dried for moisture regaining, formation is carried out at the temperature of 80-90 DEC C, and then the tea is dried until the moisture content is equal to or less than 6%.

The invention belongs to the technical field of data analysis, and particularly relates to a user data statistics method and device, and the method comprises the steps: receiving a control instructioninput by a user, extracting keywords from the control instruction, and writing all the keywords in a preset unit time into a log file; generating a log statistical file based on the occurrence frequency of each keyword in the log file; and calculating the total occurrence frequency of each keyword based on the corresponding relationship between the keywords in the log statistical files and the occurrence frequency so as to calculate the keywords in the control instruction, thereby fully analyzing the control instruction and providing sufficient data support for the subsequent analysis of theuser behavior.

The invention relates to the technical field of satellite positioning, and discloses a method for acquiring positioning error data. The method comprises the following steps of: acquiring first positioning data of a measured positioner in a plurality of epochs, acquiring second positioning data of a standard positioner in the same epochs, and correspondingly processing a second coordinate value inresponse to an instruction of determining a positioning state to obtain a standard coordinate value; according to the first coordinate value and the standard coordinate value, performing calculation to obtain a positioning error value of the measured positioner in the plurality of epochs; and associating the positioning error value of each epoch with influence factor data, and then performing storing to obtain a positioning error data set. The invention has the technical effects that: in the acquisition method, the automation degree of data collection and processing is higher, the requirementfor the site is relatively low, meanwhile, the obtained positioning data can reflect numerical value changes of influence factors of the measured positioner in different states, and help can be provided for analyzing positioning errors more sufficiently and more dimensionally.

The embodiment of the invention belongs to the technical field of big data, and relates to a big data analysis processing system and method. The system comprises a data acquisition module, an edge computing server, an artificial intelligence processing module, a big data analysis module, and an application access module. The data acquisition module is used for acquiring video image data of each distributed acquisition point in real time, and performing balanced forwarding through a Kafka forwarding service; the edge computing server is used for pre-processing video image data and pushing the pre-processed video image data to the artificial intelligence processing module; the application access module is used for caching multiple paths of video image data and performing structured analysis processing on the video image data to obtain multi-dimensional structured image information, outputting the multi-dimensional structured image information to the big data analysis module, performing professional storage and big data analysis, and providing a quick search interface for the application access module through a distributed real-time search engine; and the application access module is used for providing an access interface for the application platform access system. The working efficiency of the big data application is improved.

The invention discloses an insulation paper water content evaluation method based on robust wavelength screening. The method comprises the following steps: 1, constructing an evaluation model; 2, acquiring a near infrared spectrum of the tested insulation paper; 3, substituting the obtained near infrared spectrum of the tested insulation paper into the evaluation model to obtain the water content of the tested insulation paper; according to the method, the correction model of the water content of the insulation paper is established by using the near infrared spectrum analysis technology, the water content of the insulation paper can be rapidly predicted on site, sampling is not needed, damage to insulation is avoided, and meanwhile the method has high precision, robustness and prediction capacity; according to the method, the characteristic information of the spectrum can be fully analyzed, high-quality wavelength point data can be extracted, the data dimension can be reduced, the problems of over-fitting or insufficient fitting and the like can be avoided to a certain extent, and a new technical thought is provided for the field.

A long-term evolution rapid analysis method for an inclined geosynchronous orbit comprises the following steps: firstly, deducing a primary or secondary average perturbation force function of each perturbation item, including 1:1 resonance parts of earth non-spherical perturbation field harmonic items J22, J31, J32, J33, J41, J42, J43 and J44 with harmonic items, sun-moon gravitation perturbationLegendre expansion intercepting 4-order items and solar light pressure perturbation; secondly, establishing a secondary average semi-analytical orbit recursor of the IGSO orbit through a Lagrange typeorbit perturbation equation in combination with an average perturbation force function; comparing and analyzing IGSO orbit long-term evolution conditions under consideration of different perturbationsources and orders, so that the model is simplified, and the orbit recursion efficiency is further improved; and finally, by means of efficient orbit recursion, drawing a series of dynamic grid diagrams of complete orbit elements and initial epoch moment combinations, wherein the divisible orbit elements are (e, i, [Omega], [omega]), all binary combinations of the divisible orbit elements are e-i, [omega]-[Omega];e-[omega], i-[Omega], e-[Omega], i-[omega], all binary combinations of the initial epoch moment are InitialEpoch-e, InitialEpoch-i, InitialEpoch-[Omega], and InitialEpoch-[omega], and rapid and comprehensive analysis of IGSO orbit long-term evolution is completed according to the dynamic grid chart.

The invention relates to a gear residual life prediction method based on LSTM-AON, and belongs to the field of big data and intelligent manufacturing. According to the invention, the method comprisesthe steps: designing a novel LSTM-AON neural network to predict the residual life of the gear; based on an LSTM network, improving a hidden layer of the LSTM-AON network, so the LSTM-AON network selects an interlayer position where an element with the maximum attention coefficient is located as a hierarchical position by calculating the attention coefficients of related elements and labels; guiding the division of the hierarchical structure by attention and is determined by an element most similar to the label; and embedding the tree-shaped hierarchical structure into the recurrent neural network through the attention degree of the information so as to mine the inter-layer sequence information ignored by the traditional network. Compared with a traditional LSTMs network, the LSTM-AON network adopted by the method is high in calculation speed, small in calculation amount and higher in precision.

An aspect of the invention relates to a method for automatically analysing a transaction log of a distributed computing system, comprising a plurality of lines, the method comprising the following steps:

• • For each line:
    • Cutting the line into words;
    • Constructing a comparison vector by comparing the line with the other lines of the same size as the line;
    • Constructing a pattern from the comparison vector;
  • Creating an event per pattern;

Constructing at least one prediction model by training an artificial neural network on a group of training events, the prediction model being configured to predict the next event in the transaction log;

For at least one event:

Using the prediction model to predict the event, from a group of prediction events;

Generating from the prediction model, a causal graph of the event comprising a causal relation for each event of the group of prediction events responding to a relevance condition.

The invention provides a method for detecting solid-phase reaction between inclusions and an alloy matrix in a thermal treatment process. On the one hand, the limitation that the solid-phase reaction between the inclusions and the alloy matrix can not be clearly observed due to too small size of the inclusions is broken through, on the other hand, the situation of an interface between the inclusions and the alloy matrix and the influence of the solid-phase reaction between the inclusions and the alloy matrix on components, natures and physical phases of the inclusions and the alloy matrix are disclosed. The method integrates a high-temperature confocal laser microscope pre-melting process, a quartz tube sealing process, a thermal treatment process and the like, detects the solid-phase reaction and a reaction mechanism between a Fe-Mn-Si steel matrix alloy and MnO-SiO2-FeO-MnS series inclusions in the thermal treatment process at the temperature of 1473K to verify that the technology can be used for effectively reflecting the solid-phase reaction and the reaction mechanism between the non-metallic inclusions and the steel matrix and has an important experimental and production guide effect and good application and popularization prospects.