84 results about "Correlation theory" patented technology

The invention belongs to the field of language processing, in particular to a cross-language text similarity evaluation technology based on bilingual word embedding. The technical route and workflow of cross-language text similarity evaluation technology based on bilingual word embedding can be divided into three stages: the construction of bilingual word embedding model, the construction of textsimilarity calculation framework based on multi-neural network, and the cross-language similarity calculation. Through this model, a bilingual shared word embedding representation can be generated, which is based on the word vector correlation theory and Skip-Gram model is used to train word vectors on artificially constructed pseudo-bilingual corpus. Secondly, in order to make the generated wordembedding space as complete as possible, monolingual corpus is used as a supplement to learn additional word embedding knowledge. The similarity score of sentences is obtained by combining several neural network structures to learn the semantic representation of sentences. By dividing short text into paragraphs and treating paragraphs as long sentences as sequence input, the similarity iteration on a larger scale can be realized.

The invention relates to a joint estimation method of a state of charge (SOC) and a state of health (SOH) of a power battery system based on an electrochemical model. The method comprises the steps of establishing a pseudo two-dimensional electrochemical model correlation mathematical equation based on an electrochemical correlation theory, performing dimensionality reduction processing and calculation solution on a complicated partial differential equation by a finite analysis method and a numerical calculation method, allowing an open circuit potential of an electrode to be equivalent to open circuit voltage of a battery, establishing a capacity-surface SOC-EOCV three-dimensional response surface, extracting and establishing a degradation path graph of a battery performance degradation characteristic parameter by an intelligent optimization algorithm based on battery ageing test data, and finally realizing estimation of the SOH of the power battery based on the degradation path graph and realizing estimation of the SOC of the power battery based on concentration distribution and change rules of lithium ions in the battery.

The invention discloses a sharing spectrum access-based carrier and power combined allocation method. By the method, the problem of spectrum allocation in cognitive radio is solved by combining a game correlation theory, a duality principle, a subgradient method and the like; when an overlay spectrum accesses, an iterative algorithm for power allocation is provided, the convergence and the availability of the iterative algorithm are verified, and the problem of carrier and power allocation is solved when an underlay spectrum accesses; and when the underlay spectrum accesses, due to the constraint of the interference tolerance, strategy spaces among users are mutually coupled, and a coupling strategy game is decomposed into an independent strategy non-cooperative game and an optimization problem by introducing the duality principle and the subgradient method, so that the problem of carrier and power allocation is solved when the underlay spectrum accesses.

The invention discloses a method for quantitatively analyzing core slice visualized displacement. The method includes the following steps: firstly, the core slice is saturated with to-be-displaced medium; a displacing liquid tank is filled with displacing liquid; a valve is opened, and the flow is adjusted, wherein the micro flow in the system is read by a micro photoelectric meter; the focal length and aperture of a micro lens are adjusted, and the laser spot of a dual-pulse laser is adjusted to ensure that a clear image of the pore in the core slice is formed in a computer; when the gas-liquid two-phase interface or the liquid-liquid two-phase interface appears at the pore throat of the core slice, a synchronizer controls the dual-pulse laser and a CCD camera to work simultaneously, and a computer program determines and reads the displacements of two consecutive gas-liquid two-phase interfaces or liquid-liquid two-phase interfaces on the basis of correlation theories; within the given time interval, the speed and direction of the two-phase interface at the pore throat are calculated. The method provided by the invention can accurately measure the speed and direction of the gas-liquid or liquid-liquid displacement two-phase interface at the pore throat in a real core, and can provide preferable technical parameters for the research on improving the recovery ratio of oil fields.

The invention belongs to the technical field of wireless communication, and particularly relates to a method for reducing antenna training overhead of iterative beam forming by utilizing inter-channel sparsity in a wireless multiple input multiple output (MIMO) communication system. The invention provides an iterative beam forming method of a millimeter wave precoding system, and is used for overcoming the defect of high antenna training overhead of a power iteration method of a large-scale MIMO system. According to the method, the spatial sparsity of a millimeter wave channel is utilized, and the estimation problem of receiving vectors of millimeter wave MIMO antenna training is converted into a sparse reconstruction problem so that the loss is reduced by utilizing the correlation theory of compression perception.

The invention discloses a DDoS attack detection based on hidden Markov and Q-learning cooperation. The method comprises the following steps: by combining related theory of the hidden Markov model, proposing a DDoS attack detection based on hidden Markov model and TCP connection state combination on the basis of the existing detection method; firstly capturing different historic data from a networkdata stream, wherein the historic data comprises normal data traffic and the data traffic suffering from the DDoS attack; respectively acquiring TCP connection states of a network transmission unit,an attacker and a target host, and learning model parameters, thereby enabling the Hidden Markov model to accurately describe a state sequence of the network data stream dynamic TCP connection; on thebasis of a single-point detection model, proposing a detection method based on distributed cooperation Q learning for the problem in the distributed detection by combining the related theory of the Qlearning in the reinforcement learning. Through the experiment contrast analysis, the communication quantity among various detection points in the system is reduced, and running efficiency of the system is improved.

The invention discloses a novel pulse taking system based on remote medical treatment and discloses a remote pulse taking instrument which comprises a collecting system, a computer unit, a pulse wave simulation system, a calibration device and a simulation hand. A radial artery pulse signal and a human body temperature signal of a patient are detected, and therefore a network technology is adopted to promote butt joint of family information and hospital information. A modern electronic technology and haemodynamics correlation theories are used for finishing analog simulation of far-end pulse-taking signals, and remote comprehensive reproduction of pulse-taking comprehensive information is achieved. The system can be applied to traditional Chinese medicine remote medical treatment, and doctors of the traditional Chinese medicine can clearly feel the physiological status of the patient, and convenience is brought to doctor seeking of the patient. If the novel pulse taking system is matched with visual software in application, remote information integration of four traditional Chinese medicine diagnostic methods is completely achieved. In addition, the remote pulse taking instrument can also be applied to teaching practice of traditional Chinese medicine.

The invention brings forward a rolling bearing fault diagnosis method based on improved fractal box dimensions and a self adaption gray correlation theory. Fault characteristics (including useful and easy-to-differentiate information capable of reflecting different working states of a bearing) are extracted from bearing vibration signals via the improved fractal box dimensions, and fault types and different orders of severity of bearings can be automatically identified via self adaption gray correlation algorithms. The rolling bearing fault diagnosis method is used for solving a problem that work and health states of rolling bearings cannot be easily assessed via traditional time domain and frequency domain methods; via the rolling bearing fault diagnosis method, fault types and different orders of severity of different bearings can be accurately and effectively identified.

The invention provides a remote sensing character optimization algorithm for improving an mRMR (min-redundancy max-relevance) algorithm. In an object-oriented high-resolution remote sensing ground surface classifying process, a certain algorithm needs to be used for dividing a high-resolution remote sensing image so as to obtain a series of primitive objects, various features of the primitive objects are calculated, properties of the primitive objects are determined according to the features of the different primitive objects, and a ground block object classifying process is finished. Because ground block features are numerous, the feature which is the most effective on determination of ground blocks needs to be selected from the various features, and the process is a feature optimization process. On the basis of a correlation theory of mutual information in an information theory, three methods comprising binary discretization, histograms and F statistics are used for implementing a calculation process of the mRMR algorithm, and the feature optimization process is implemented by the mRMR algorithm. The feature optimization process can be implemented efficiently. Moreover, the remote sensing character optimization algorithm can be widely used for applications such as similar feature optimization and feature validity check and evaluation of certain ground object types.

The invention provides a video sequence loss frame prediction recovery method based on a deep neural network. The deep learning correlation theory is used, a deep convolution network is used for automatically extracting image features and the learning ability of a LSTM long-term memory network on a time sequence, a fixed number of video frame image data are used as training samples to train the network, and loss frame prediction recovery in the video sequence is performed, the intrinsic features of the video frame images and the similarity and coherence of the images between the frames are fully used to improve the prediction accuracy and efficiency, meanwhile, the video sequence loss frame prediction recovery method is high in generalization ability and has a certain social value and practical significance.

The invention discloses an extracting method of optical spectrum vector cross-correlation features in hyper-spectral image classification. The method comprises the steps that pretreatment, normalization, denoising, dimensionality reduction and the like of hyper-spectral image data are included; boostrap sampling and weighted average are performed so as to obtain a reference sample set; spectral signal random process theoretical assumption includes first assumption and second assumption, wherein in the first assumption, spectral signals are random experiments of a stable random process at a certain time, and in the second assumption, the probabilities of all random experiment values are the equal, the spectral signals are abstracted according to the cross-correlation theory of the random process, a cross-correlation coefficient calculation formula is obtained, and finally cross-correlation feature vectors are formed by combination; sparse decomposition is carried out on the cross-correlation feature vectors through the MOD. The extracting method for features in the hyper-spectral classification is provided from the aspect of the cross-correlation of the random process, good noise immunity and high stability are achieved, and hyper-spectral classification precision is improved.

The invention belongs to the technical field of wireless communication, and especially relates to a method which reduces the antenna training cost of iteration wave beam shaping by utilizing the channel space sparseness in a wireless MIMO communication system. The rapid iteration wave beam shaping method based on channel space sparseness comprises the steps of initialization, LANCZOS iteration, cycled iteration control and the like. In the time division duplex MIMO system, Uplink and downlink channels can be interchanged, iterated antenna training is carried out by introducing the LANCZOS algorithm, the channel space sparseness is utilized, problems in estimating reception vectors in the iteration process is modeled into a sparse reconstruction problem, theory related to compressed sensing further reduce cost of iteration training, and antenna training is completed at an extremely high speed.

The invention discloses a rail transit key node and a key road section identification method. The method includes: based on a complex network theory and a PageRank algorithm, calculating a topologicalindex value of the rail network as a node importance evaluation system value; carrying out evaluation value calculation on a node importance evaluation matrix by adopting three evaluation methods ofa grey correlation analysis method, a TOPSIS method and a principal component analysis method, determining weights of evaluation results by utilizing an entropy weight method, and finally obtaining importance values of the nodes and the road sections so as to identify the key nodes and the key road sections. According to the invention, identification of the key nodes of the rail transit network isobjectively and comprehensively considered; the key node importance degree calculation method is designed by using relevant theories such as a complex network and comprehensive evaluation, stations needing important maintenance in rail transit operation can be judged, the importance degrees of all the stations are ranked, and a choice is further provided for robustness analysis of the key nodes of the rail transit network.

The invention belongs to the technical field of wireless communications, particularly relates to a method for reducing iterative beam forming antenna training expenses through a channel space sparse characteristic in a wireless multiple input multiple output (MIMO) communication system, and provides an iterative beam forming method based on the channel space sparse characteristic. The method comprises the steps that sparse modeling is carried out through a geometric model of a sparse multipath channel; initialization is carried out; beam forming vector quantity training is received; the beam forming vector quantity training is sent. The space sparse characteristic of the millimeter wave channel is utilized, the estimating problem of vector quantity receiving in millimeter wave MIMO antenna training is converted into a sparse rebuilding problem, and therefore correlation theories of compressed sensing are utilized, and the expense of a power iteration method is further lowered by 50-60 percent with quite low performance losses.

The invention relates to a scattering generalization imaging method and experiment method based on physical driving, and belongs to the technical field of imaging analysis, and the method comprises the steps: building a physical / data model, and employing a speckle pattern collected by a camera for imaging the speckle pattern; and taking the speckle correlation theory as a universal physical principle to constrain and guide the neural network to carry out generalized imaging in different scattering scenes. The experimental method comprises theoretical analysis and a system experiment, and the method is systematically discussed by establishing a specific system experiment. And the generalization ability and the generalization quality are improved, and more complex targets are generalized. Aphysical model based on speckle correlation and a data model based on deep learning are organically combined, so that the scattering generalization imaging effect and the imaging range of the neural network model are greatly improved.

The invention provides a method for building a physical environment evaluation system of traditional residential buildings and relates to the technical field of building physical environment evaluation. The method is particularly characterized in that a traditional residential building physical environment evaluation system is taken as a research object, the definition of the traditional residential buildings, the research range of the building physical environment and the basic conception of the evaluation system are researched through related theories, and the core problems, namely evaluation indicators and weight coefficients, in building the evaluation system are determined, and solving ideas of index screening and quantization and a determining weight method are explored; then building physical environment evaluation indexes are summarized and concluded to form a traditional residential building physical environment evaluation index set; based on related standards or norms of physical environment evaluation, by referring to parametric study or measured data of the traditional residential building physical environment, evaluation criteria for index evaluation is formed; and the weight coefficients of all the indexes are calculated on the basis of AHP-process expert questionnaire, together with the evaluation norms, the traditional residential building physical environment evaluation system is formed, and grading of evaluation results and use of priority improvement items are explored.

The invention discloses a self calibration method for an image measuring instrument. According to the method, on the basis of the correlation theory of mathematic images, two adjacent images of a tested workpiece before or after the translation in a two-dimensional plane are used as objects, the pixel displacement value is calculated, then, the reading value of a grating ruler during the image collection is combined, the practical physical size displacement value is obtained, finally, the scale factor of the image measuring instrument is obtained according to the ratio of the pixel displacement value to the practical physical size displacement value, and the self calibration of the image measuring instrument is realized. The self calibration method does not need a special-customized high-precision calibration plate and has the advantages of simple and convenient operation and high efficiency, the image measuring instrument can be fast calibrated in any time, and in addition, the cost is saved.

The invention relates to a turbot fin cell line forming method. It includes the following steps: using pectoral fin and pelvic fin tissue as raw material; shearing the fin tissue adopting trypsin, hyaluronidase, II type collagenase multiple step digestion process to gain free fin cell and loosen tissue block; and culturing in L-15 culture solution containing 20% fetal calf serum, carboxymethyl chitin, N- acetyl glucose hydrochloride, glucosamine hydrochloride, human epidermic cell growth factor, human alkali fibroblast growth factor, and tooth bothid gill cell culture solution; adopting trypsin digestion process to do sub-culturing. The technology is scientific. The formed sub-culturing cell reaches the 62th generations. The formed turbot fin cell is not transfected by any virus or oncogene, and can hopefully be directly applied to correlation theory study and viral vaccine development.

The invention belongs to the technical field of wireless communication, especially relates to a method for performing carrier wave synchronization and simultaneously compensating and inhibiting phase noise by use of cross correlation of a Golay sequence in a millimeter wave wireless communication system, and brings forward a data auxiliary carrier wave synchronization and phase noise compensation method. According to the invention, by use of good correlation and matching gain of a pseudo sequence, the problem of influences exerted by carrier wave frequency deviations and phase noise on a signal error rate is converted into a problem of correcting data phase deviations, such that by use of a correlation theory based on data auxiliary carrier wave synchronization and phase noise compensation inhibition, through correcting the carrier wave deviations and the phase deviations caused by the phase noise, the error rate of data is reduced to the order of magnitude of 10 <-6> to 10<-7>.

In combination with a graph structure correlation theory, a two-layer road network logic structure is constructed. The road network logic structure comprises a road network topology layer and an intranet correlation layer, wherein the road network topology layer is composed of road segments and intersections, and the road segments are divided into straight ways and bends. A cardinal spline curve with five datum points is adopted to perform base modeling on the bends, and a data structure is created on the basis of generality of the road segments to describe basic attributes of the road segments; last, a road network editing tool is realized on the basis of a road network construction model, wherein the tool provides a visual interaction interface, and therefore a user can edit a road network in a simulated region just through simple operation such as dragging and rotating.

The invention discloses a logical reasoning mechanism being suitable for a legal expert system, effectively overcomes the malady that the current legal expert system is based on regulation, and solves the problems that the majority of legal expert systems can not apply judging knowledge for reasoning, only provides simple explanation through regulation feedback, the problems that uncertainty how to stimulate the intuition, experience and reasoning result and other problems are expressed dissatisfactorily. The reasoning mechanism introduces a correlation theory and a method of fuzzy reasoning, abandons simple positive and negative two-value features of traditional logic, regards the logical world into gray level with continuous changes, allows a proposition to be this or that, and exists partial positive and partial negative. The invention provides a more natural and more reasonable operation environment, can describe target system behavior adopting a fuzzy logic technology, imitates people to judge and control behavior technology by cognition and experience, can transform some natural languages into algorithms of computer operation to achieve the purpose of using a simple program to process complex systems which can not be processed or is difficult to be processed by traditional control method. The fuzzy logic correlation theory and method are applied in the legal expert system, can well overcome the shortcomings of knowledge expression, reasoning mechanism and knowledge acquisition and the like of the traditional method in the legal expert system, are more convenient to express numerous uncompleted and inaccurate knowledge and relationship in legal fields, more appropriately describe uncertainty in legal reasoning, makes up for defects of traditional reasoning method, and are suitable for large-scale popularization.

A GNSS terminal can provide information including a user position, speed and corresponding variance estimated value only at present, an interval of a true position value and a corresponding probability can be reckoned according to probability theory related theories, and in piratical application, the reliability of the variance estimated value cannot be ensured, and the risk that the true value isnot within the reckoning interval cannot be pre-estimated. Thus, a satellite-based and ground-based integrated enhanced system scheme and a matched realization strategy of a terminal are provided, position information, a protection interval and corresponding risk can be provided for the user, and a user can make a decision. In addition, the range of the protection interval is intrinsically associated with the risk level, so that different ranges of protection intervals and risks thereof are provided, and the user can make a balance between the precision and risk.

The invention is aimed at providing a diagnosis method of self-adapting performance of pneumatic components of a hybrid gas turbine based on the combination of the gray correlation theory and a thermodynamic model. The method comprises following steps: utilizing component pseudo relative parameters to set up a component-level thermodynamic model of the gas turbine, utilizing pseudo relative parameters to define a gas compressor and healthy indicators of turbine gas circuits, setting healthy indicators of gas circuits of all components of the thermodynamic model to simulate single components and measurement parameters of gas circuits in the case of performance degradation of multiple components, recognizing a performance degradation mode with the gray correlation theory in order to separate parts of actual performance degradation such that subsets of healthy indictors of actual gas circuits to be diagnosed are determined. The diagnosis method of self-adapting performance of pneumatic components of the hybrid gas turbine based on the combination of the gray correlation theory and the thermodynamic model has following beneficial effects: the method is capable of easily and conveniently setting healthy indicators of all components in gas circuits used for gas circuit diagnoses, reflecting changes of healthy indictors of gas circuits induced by performance degradation of components more accurately and avoiding the blurring effect of diagnosis results caused by measurement noises and a large number of parts.

The invention is concerned with a kind of dispensation of invigorating the spleen and tonifying the kidney preparation and its preparation method. It relates to raw milkvetch root, raw red sage root, Rhizoma Dioscoreae, raw bighead atractylodes rhizome, broomrape, roud cardamon seed, raw rhubarb, raw liquorice, and so on. Dry, grind, soak, boil out, boil out again, mix about materials to get the said preparation. It bases on traditional Chinese medicine theory and the correlation theory of five parenchymatous viscera. This dispensation is fit for chronic kidney disease without anaphylactic response and side effect. It can release many clinical symptoms, such as spontaneous perspiratio and fatigue, short of breath and want of speech, yellowish complexion and emaciation, inappetence and abdominal distension, improve the kidney function and nutriture to prolong survival time of sufferers. It has low cost and easy preparation technology.

The invention relates to a multi-type power supply capacity long-term planning method considering offshore wind power access. A modeling method of offshore wind farm output is proposed based on the correlation theory. The problem of offshore wind power absorption is introduced into the power planning level. Considering the peaking capacity constraints of multi-type power supplies and the system reliability constraints based on stochastic production simulation, the capacity optimization model of multi-type power supplies is established with the construction and operation economy as the goal, and the particle swarm optimization algorithm is used to solve the problem. The method is simple and practical and has high operability and solves the problem that the traditional planning method only pays attention to economic indicators and does not consider enough the peak shaving capability and reliability of the system. The method can solve the problem of peak shaving difficulties faced by windpower absorption and has great significance to ensure wind power absorption and safe and stable operation of the power grid and provides a feasible scheme for long-term power supply planning in coastal and offshore provinces rich in wind power resources.

The invention belongs to the technical field of wireless communications, and particularly relates to a method for reducing antenna training overhead of iterative beam forming by using sparsity among channels in a wireless multiple input multiple output (MIMO) communication system. The invention provides an iterative beam forming method based on compressed sensing. According to the method, the estimation problem of a reception vector in millimeter-wave MIMO antenna training is transformed into a sparse reconstruction problem by using the spatial sparsity of millimeter-wave channels, so that the overhead of a power iteration method is further reduced by 50-60% with tiny performance loss using the relevant theory of compressed sensing.

The invention discloses a graph theory correlation theory-based anomaly detection method, which specifically comprises the following steps: 1, performing clustering operation on an original data set,and dividing the data set into different clusters; 2, calculating the mean value density of the original data set, and comparing the mean value density of the original data set as a threshold value with the cluster density to simplify the data set; 3, carrying out feature extraction and spatial distance calculation on the data set, and carrying out datamation operation on a result; 4, distributingall data points of the effectively detected data cluster according to the calculated weight values to construct an undirected connected graph; and 5, searching the shortest path of the correspondingcluster by adopting a Floyd algorithm. In terms of preprocessing of the data set, a method of simplifying the data set for the second time is adopted, dimension reduction operation is carried out on the data set according to different reference information, a large number of useless data sets can be effectively reduced, and time complexity and space complexity in the anomaly detection process arereduced to a great extent.

The invention discloses an internal force path geometrical morphology based low-carbon material-saving bearing structure design method. The method includes that material modulus (such as elasticity modulus) of a bearing structure serves as low-carbon material-saving oriented design variable, a numerical method is used for solving to obtain internal force path geometrical morphologies (including degree of density and curvature) so as to punish unit elasticity modulus, an optimal force transferring path of the bearing structure is obtained by means of loop iteration, and based on the optimal force transferring path, a basic bearing framework and space requirements of a structure are defined. The method applies correlation theories of an internal force path to structural topological optimized design, and provides a novel idea for low-carbon material-saving design of major equipment bearing structures.

The invention discloses an automobile powertrain system rotational inertia synthetic method. The method comprises the steps of inputting the known parameters including the mass, center of mass, inertia and eulerian angle of an engine and a gear box into an EXCEL so as to facilitate data import and correction; obtaining the coordinates of the main center of mass obtained after synthesis according to the mass and center of mass of the engine and the gearbox by means of the method for solving the center of mass in theoretical mechanics; establishing a coordinate system the orientation of which is parallel to that of a main coordinate system according to the coordinates of the main center of mass; expressing vectors with a coordinate matrix, establishing the relationship between the coordinate matrixes of the same vectors under different coordinate systems, and deducing the relationship between inertia matrixes under different coordinate systems by means of correlation theoretical methods of the linear algebra, namely establishing the relationship between rigid body rotation inertia and the product of inertia under different coordinate systems; calculating a synthesis result by means of a corresponding computer language compile program according to a deduced matrix expression. According to the method, deduction is conducted in the matrix form, briefness and visualization are achieved, the conclusion is in a quite brief form, and a solution can be obtained easily by means of the computer language.

The invention relates to a cloud inference-based car cruising speed planning method, which takes the average fuel consumption of a car per 100 kilometers as an economic evaluation index. The planning method has the flow diagram that first, a cloud model of the average fuel consumption per 100 kilometers is established based on experimental data; second, related theories of cloud transform, cloud inference and the like are used for determining a concept tree of cloud model input and outputting variables so as to generate a cloud model rule base of the average fuel consumption of a car per 100 kilometers; a mapping relationship between the input and output variables is generated based on automatic extraction procedures of the cloud inference and the rule base, the economic speed under different driving resistances is extracted based on the mapping relationship, an economic cruising speed changing track which is adapted to the change of driving resistances is planned for these economic speeds, and the car runs at the economic speed corresponding to the driving resistance all the time. Accordingly, the method can improve the fuel economy of the whole car, thereby effectively reducing the average fuel consumption of a car per 100 kilometers and better achieving the purpose of energy conservation and emission reduction.