80results about How to "Good calculation efficiency" patented technology

The invention discloses a collision relieving method and device between vehicles in a hybrid vehicle queue. The collision relieving method between the vehicles in the hybrid vehicle queue includes the following steps that firstly, vehicle condition information of the network-connection vehicles and vehicle condition information of the non-network-connection vehicles in front of and behind the network-connection vehicles are acquired; secondly, the head vehicle and the rear vehicles in the hybrid vehicle queue are sequentially judged, if the corresponding network-connection vehicle is the head vehicle or the rear vehicles, the third step is executed, and if the corresponding network-connection vehicle is neither the head vehicle nor the rear vehicles, the first step is executed again, wherein the head vehicle is the network-connection vehicle with the braking working condition exceeding a set threshold value, and the rear vehicles are vehicles meeting the queue collision relieving requirement behind the head vehicle; thirdly, the vehicle condition information of the network-connection vehicles is received; fourthly, the expected acceleration of each network-connection vehicle in the rear vehicles is planned; fifthly, each network-connection vehicle in the rear vehicles travels according to the planned expected acceleration, and the each network-connection vehicle in the rear vehicles travels according to a vehicle following mode; and sixthly, whether each of the rear vehicles is parked or not is judged, if certain rear vehicles are parked, control is stopped, and if no rear vehicles are parked, the third step is executed again. By the adoption of the method and device, the braking space between the vehicles in the hybrid vehicle queue can be used for control.

The invention discloses a view-independent human action identification method based on template matching, which can identify a plurality of pre-defined typical actions in a video. When constructing a template, a motion history image under a plurality of projection viewpoints are calculated for each sample action and polar coordinate characteristics are extracted, the polar coordinate characteristics are mapped to a low-dimensional sub-space by adopting a manifold learning method, and super balls are constituted for the sample actions in the sub-space on the basis of the low-dimensional coordinate of the multi-viewpoint polar coordinate characteristics. An action template is composed of a plurality of super balls with known ball centers and radiuses. When an unidentified action is given, the motion history image and the corresponding polar coordinate characteristics of the action are firstly calculated, then the polar coordinate characteristics are projected into the template action sub-space to obtain the low-dimensional coordinate, the distances from the coordinate to all the ball surfaces of the super balls are calculated, and the nearest super ball is selected as the identification result. The technology provided by the invention realizes the view-independent action identification and has higher application value in the video monitoring field.

The invention discloses a multi-focusing image fusion method utilizing core Fisher classification and redundant wavelet transformation. The method comprises the following steps: firstly, carrying out image block segmentation on source images and calculating definition characteristics of each image block; secondly, taking part of areas of the source images as a training sample and obtaining various parameters of a core Fisher classifier after training; thirdly, utilizing the known core Fisher classifier to obtain preliminary fusion images; and finally, utilizing redundant wavelet transformation and space correlation coefficients to carry out fusion processing on the image blocks positioned at the junction of the clear and fuzzy areas of the source images to obtain final fusion images. The invention has better image fusion performance, does not have obvious blocking artifacts and artifacts in fusion results, obtains better compromise between the effective enhancement of the image fusion quality and the reduction of the calculation quantity and can be used in the subsequent image processing and display. When wavelet decomposition layers with less number are adopted, the invention is more suitable for an occasion with higher real-time requirement.

The invention discloses a radiation shield calculation method based on coupling of a Monte Carlo method and a characteristic line method. Through the coupling of the Monte Carlo method and the characteristic method, the Monte Carlo method is adopted at a radiation source area complex in geometry for simulation and the non-uniform amendatory characteristic line method is adopted in a shield layer area simple in geometry for simulation to obtain distribution result of radiating particle flux in the shield layer, wherein the Monte Carlo method has the advantages of being capable of accurately simulating the transporting process of particles in multi-dimensional complex geometry, and the characteristic line method has the advantages of being small in limit to calculation models, fast in calculation speed, free of ray effect, and capable of obtaining high-accuracy calculation results. Compared with a traditional shielding calculation method, the radiation shield calculation method based on the coupling of the Monte Carlo method and the characteristic line method are capable of penetrating a shield area deeply to obtain better geometry adaptability, higher calculation efficiency and more accurate calculation accuracy.

The invention provides a geostress field distributed data management (DDM) retrieval method based on actual measurement results and a linear programming method. According to the geostress field DDM retrieval method based on the actual measurement results and the linear programming method, required parameter information is obtained through experiments according to an engineering site geological exploration report, a displacement discontinuous method DDM numerical model is built according to the obtained information, gravity load is exerted in the vertical direction, unit load is exerted in the horizontal x direction, unit load is exerted in the horizontal z direction, an area stress field is obtained through DDM processing, stress data processing values of ground stress actual measuring points are extracted, processing regression coefficients corresponding to each working condition is processed with the linear programming method according to the stress data processing values of each ground stress actual measuring point, combining the stress field obtained by processing each working condition according to regression coefficients, and then summation is carried out to obtain an inversion ground stress field.

The invention provides a digital signature method based on identity. The method comprises the following steps: a system parameter is generated which is used for signature and signature verification; a private key of a user is generated according to identity information of the user and the system parameter; the private key is used for signature on information; signature verification is carried on the signature on information according to the system public parameter and the identity of a signer. For some calculations of verification equation arithmetic in signature arithmetic is determined as constants by system parameter, precomputation is carried out when system parameter is generated, which greatly reduces calculation cost of verification equation; When signatures is carried out on the same user with different information, special treatment (detailed specification is in the text) is carried out to greatly lower communication cost. After such treatment, operation efficiency of the system is improved greatly on the basis of not lowering safety.

The present invention discloses a method for calculation of characteristic lines of a three-dimensional ionized field of a direct current transmission line. The method can be used for calculation of direct current three-dimensional ionized fields of line crossing and around the surface structures and insulators. The method comprises: giving an assumed distribution of a space electric field and of space charges, calculating a new space electric field distribution by employing the space charges through the Poisson equation, and painting characteristic lines; solving the charge distribution on the characteristic lines according to the new space electric field distribution through the ion current equation and the current continuity equation; and repeating the steps mentioned above until the distributions of two successive space charges is in an allowable error range, and performing calculation of combination of the electric field and the ion current density. Compared to the Deutsch hypothesis method, the method for calculation of characteristic lines of the three-dimensional ionized field of direct current transmission line considers the influence of the space charges and is more accurate in calculation result; and moreover, compared to the finite element method, the method for calculation of characteristic lines of the three-dimensional ionized field of direct current transmission line greatly increases the update efficiency of charges and is obviously better than the finite element method on the computational efficiency.

The invention discloses an EEG signal classification method based on fast multidimensional empirical mode decomposition. The method comprises: (1) collecting several groups of EEG signals and preprocessing the signals; (2) conducting the fast multidimensional empirical mode decomposition on the preprocessed signals to obtain all intrinsic mode function signals; (3) conducting spectrum analysis oneach layer of each intrinsic mode function signal and selecting a signal layer with the average power spectrum concentrated in the frequency bands of 8-12 Hz and 18-26 Hz as a new multidimensional signal; (4) making the new multidimensional signal passing through a spatial filter to extract characteristics of the EEG signals; (5) inputting the characteristics into a classifier for classification,selecting optimal parameters of a CSP according to the classification accuracy and classifying the EEG signals under different motion imaging tasks by utilizing the EEG characteristics under the optimal characteristics. The method solves the problems of pattern aliasing and low computing efficiency of a common multidimensional empirical mode decomposition algorithm, a decomposition result is moreinterpretable, and the classification accuracy of the EEG signals is improved.

The invention discloses a symmetric force finding method of a prestressed cable rod structure, and belongs to the field of the design of modern space structures. The method comprises the steps that 1, a force equilibrium matrix is set up, and symmetric subspaces corresponding to an external load vector and an internal force vector are set up respectively; 2, a first partition submatrix of the symmetric type equilibrium matrix is calculated; 3, a holohedric self-stress mode is solved; 4, whether the holohedric self-stress mode is an untrivial solution or not is judged, and if the holohedric self-stress mode is a zero solution, a geometric structure is redesigned; 5, an initial prestress combination coefficient is determined; 6, whether the set-up prestressed cable rod structure meets the stability conditions or not is judged, if the structure is stable, a symmetric force finding result is output, the symmetric force finding process is finished, and otherwise, the last step is executed again to seek an initial prestress distribution scheme again.

The invention discloses a distributed coordination control method of a blast furnace system and a pressure recovery turbine (TRT) device, which comprises: establishing association models of a blast furnace system and a TRT device respectively; determining the sampling periods of the blast system and the TRT device by using a distributed coordination control process; optimizing and resolving the two models respectively; and establishing a coordination control mechanism by using a variable-window-length distributed predictive control method so as to realize the coordination control over the blast system and the TRT device. In the invention, through the data interaction by a data server, the data information of associated systems are read; optimization and resolution are performed respectively, so the coordination and optimization calculation amount are reduced greatly; by performing coordination and optimization control over the two systems globally and integrally, the influences of fluctuation in raw material component and other interferences on production operation and product quality produced by perturbation action are relieved effectively, unnecessary energy waste is reduced, the normal temperature distribution in a blast furnace is ensured, and the furnace top pressure is stable; and the TRT device can generate a maximum amount of power, and the two systems operate stably and efficiently.

The invention provides a network vulnerability identification method based on removal of a timing sequence. The method comprises the following steps of 1, pre-processing network data; 2, defining a network vulnerability measurement index; 3, identifying a network key node set; and 4, optimizing a node removal timing sequence. According to the method provided by the invention, the total quantity of network attack nodes is reduced in space, sensitivity of early network attacks is improved in time, an intentional network attack effect is optimized, and thus network attack efficiency and capacity are improved in general.

The invention relates to a training-obtaining method of an image detection learning network, an image detection device, and a medium. The training method comprises following steps: constructing a first learning network and a second learning network, wherein the parameter number of the second learning network is less than the parameter number of the first learning network; utilizing a medical imagetraining data set to train the first learning network by a processor so as to obtain a trained first learning network; based on the learning result of the first learning network, utilizing the medical image training data set to train the second learning network by the processor; and utilizing the trained second learning network to detect medical images. The obtained second learning network can take both calculation precision and calculation efficiency into account in medical image detection.

The invention relates to a decoupling control method of an airborne LiDAR attitude angle compensation device. In order to compensate effects on airborne laser radar measurement point cloud imposed byhelicopter-borne platform attitude angle change, an attitude angle compensation device is designed. The device is a tri-axle turntable, and there is control coupling, so a decoupling control method isprovided. The method comprises steps of firstly, establishing a mathematical model of an attitude angle compensation device dynamic system and proving the reversibility of the attitude angle compensation device dynamic system; then, establishing a neural network inverse system model of the attitude angle compensation device dynamic system, acquiring neural network learning data and carrying out offline training on the neural network; then, comparing output of the neural network inverse system with an expected input value, and sending the differential value into a feedforward controller to beused for correcting a control voltage signal of the attitude angle compensation device dynamic system; and finally, by combining a fuzzy-PID controller of a closed-loop feedback loop, forming a feedforward-feedback composite controller. Thus, real-time decoupling of the attitude angle compensation device dynamic system is achieved, control precision and anti-interference are improved and dynamic control performance is improved.

The invention discloses a method for implementing PML (perfectly matched layers) in DGTD (discontinuous Galerkin time domains) by the aid of hybrid triangular prism-tetrahedron grids. The method includes steps of S1, selecting computational models, selecting PML absorption layers and establishing Maxwell equations for PML zones and non-PML zones in computational domains; S2, dividing grids and guaranteeing that the grids on primary surfaces and secondary surfaces of periodic boundaries are matched with one another; S3, expanding electric field intensity vectors and magnetic field intensity vectors in the grids in different regions by the aid of different basis functions; S4, carrying out space discretization by the aid of DGTD algorithms and then carrying out time discretization to obtaintime discretization equations; S5, integrating element matrixes and acquiring solved element matrixes according to conditions; S6, carrying out time iteration to obtain electric field and magnetic field values at each moment. The method has the advantages that the grids in PML regions are divided into triangular prisms, accordingly, the computational precision can be controlled from two dimensions, and the method is excellent in adaptability to hierarchical characteristics of the PML and is good in solving precision and high in solving speed.

The invention provides a transmission line security reliability evaluation method, which comprises the following steps: S1, acquiring the transmission line satisfies N-1, N-2 standard proportions, calculate N-1, N- Pass Rate Score = N-1, N-2 Pass rate* 100; 2, respectively calculate that proportion of the heavy-load line, the proportion of the light-load line, the maximum load rate and the load unbalance degree, and marking the rationality of the power flow distribution according to the difference between the average value of the four indexes of the heavy-load line proportion, the proportion of the light-load line, the maximum load rate and the load unbalance degree and the four indexes; 3, calculating that abundance of the short-circuit current to obtain a rationality score of the short-circuit current; S4: Scoring the variable capacitance load ratio according to the difference between the variable capacitance load ratio and the standard interval; 5, scoring that reliability of electric power use according to the load reduction probability and the expected power supply shortage quantity in a year; S6: Integrating Step S1-S3 socres. The invention realizes the comprehensive evaluation through the combination of safety reliability and electric power reliability.

The invention discloses a method for calculating energy flux density distribution of focusing light spots of a tower type solar heat absorber. A heat absorber focusing light spot energy flux density dynamic simulation model of a tower type solar heliostat field is established by utilizing a heat absorber light spot equivalent model. According to the average energy flow density in the conical surface of the projection light of the heliostat, based on coordinate rotation transformation and energy superposition, energy flow density values on grid points of the receiving surface of the heat absorber are obtained through conversion, and then energy flow density distribution of the heat absorber is obtained. By adopting the method, the energy flow density values on all grid points do not need tobe directly calculated, so that the calculation amount is effectively reduced, the calculation duration can be effectively shortened, and the calculation efficiency is improved.

The invention discloses a 3D and isogeometric mixed unit modeling method of a rifling barrel. The rifling barrel is divided into a rifling and a barrel body, an isogeometric unit is used to establish the rifling structure, a Lagrange finite element mesh of the barrel body is obtained by utilizing discrete finite elements. In the isogeometric unit of the rifling, Lagrange transformation is carried out on a connecting curved surface cooperated with the barrel body so that the rifling is effectively connected with the barrel body. The connecting curved surface is a curved surface shared by the rifling and the barrel body. Unit nodes whose coordinates are the same are removed from a model after connection, and nodes are marked again to obtain a complete isogeometric and 3D mixed unit model of the rifling barrel. According to the isogeometric and 3D mixed unit model of the rifling barrel, the accurate geometric shape of the rifling is reserved, more accurate results can be obtained by simulating calculation, and the barrel body can use a mature finite element frame to reduce the modeling time.

The invention relates to a distance distribution-based square detecting method in a digital image, which comprises the steps: acquiring an image, and inputting the acquired image into a computer; computing the gradient of each pixel point by a gaussian gradient template; computing an edge graph of the image by a Canny edge detection operator; computing a directional line of each edge point by the gradient of each edge point on the edge graph; computing the characteristic length and the characteristic energy of each pixel point in the image to obtain a characteristic length distribution map and a characteristic energy distribution map of the image; under the constraint of a threshold value, detecting a plurality of local maximum value points on the characteristic energy distribution map; confirming a plurality of edge point sets of one square by each local maximum value point and the characteristic length of each local maximum value point; checking and getting rid of the unreasonable edge point sets of the square by the direction information of the edge points; and outputting the edge point sets which form the square. The method can be used for exactly detecting the center and the edge of the square in the image. Compared with the existing method, the method is simpler and easier to realize, and higher in computation efficiency.

The invention discloses an encryption method and a decryption method based on a color image quaternion representing method. Firstly, conjugate symmetric sequency-ordered quaternion Hadamard transform (CS-SQHT) is defined firstly and the defects such as color information loss and non-considered integrality of traditional CS-SCHT (Conjugate Symmetric Sequency-Ordered Complex Hadamard Transform) in color image encryption application; next, color image double-random phase encryption and decryption methods are provided based on CS-SQHT. According to the encryption method and the decryption method based on the color image quaternion representing method, the integrity and the dependency of three channels of a color image are taken into account, and excellent anti-attack robustness is achieved; as a result, the encryption method and the decryption method based on the color image quaternion representing method are obviously superior to the traditional CS-SCHT algorithm and appreciably superior to the existing algorithms based on quaternion; the encryption method and the decryption method are simple to implement, low in time complexity, and obviously superior to the existing algorithms based on quaternion in calculation efficiency.

The invention relates to a vehicle-mounted monitoring device, a monitoring system based on expression recognition, and a monitoring method. The vehicle-mounted monitoring device is good in concealment, large in monitoring visual field and good in monitoring effect. According to the monitoring system and method based on expression recognition, real-time monitoring of the mobile terminal can be achieved, monitoring data are not prone to being lost, and control operation of the monitoring device in the vehicle can be achieved through the mobile terminal. Face detection and suspicious expression recognition are based on a deep learning algorithm training expression recognition model, a potential infringement object can be automatically recognized, and the recognition accuracy is high. Comparedwith other algorithms, the Adaboost face position detection model has better calculation efficiency and is suitable for the requirement of real-time operation. Compared with the traditional CNN for classifying expressions, the LSTM network capable of ensuring the time sequence is used, the LSTM network focuses on continuous expression changes, the detection result of each frame can influence thenext frame, and a suspicious expression judgment result can be output at each moment, so the suspicious expression judgment reliability and the alarm timeliness are improved.

The invention discloses a scene reduction solving method suitable for a high-dimensional large-scale scene. The method comprises the following steps: defining a scene reduction model; initializing a typical scene set; solving a transmission matrix, and obtaining discrete probability distribution; iteratively solving the typical scene set until the Wasserstein distance change is smaller than a certain threshold value or the number of iterations reaches the set number of times; and selecting a scene closest to the typical scene from the initial scenes to reconstruct a typical scene set, and applying the typical scene set and the discrete probability distribution thereof to a stochastic optimization problem of a power system. The method has the advantages that the obtained Wasserstein distance is small, the fitting precision is high, and the calculation efficiency is excellent. For a large-scale scene, the calculation efficiency is relatively high and the fitting precision is not lost.

The invention relates to a hyperspectral remote sensing image classification method based on sparse graph regularization. The SGR method comprises the following steps: employing an effective sparse representation algorithm for a dictionary to obtain a score matrix, estimating a prediction function through optimizing a typical graph-based regularization problem, and finally, propagating labels of alarge amount of unknown data based on the score matrix and the prediction function to realize classification. Furthermore, a total variation sparse graph regularization method and a weighted joint sparse graph regularization method are introduced, total variation sparse representation classification TVSGR is expansion of the SGR in the aspect of models, spatial information modeled by using totalvariation is introduced in the sparse representation process, weighted sparse graph regularization classification WSGR is amplification of the SGR in the aspect of characteristics, and a Gaussian kernel-based adaptive weighting method is introduced into an SGR model; and the design method provided by the invention has very outstanding performance in the aspects of calculation efficiency, classification accuracy and noise robustness.

The invention relates to the technical field of computational fluid dynamics, particularly provides a method and a system for predicting flow characteristics of a marine atmospheric boundary layer based on an OpenFOAM platform, and aims to solve the problems of difficulty in predicting the flow characteristics of the marine atmospheric boundary layer and low prediction efficiency in the conventional marine measured data analysis method. In order to achieve the purpose, the method for predicting the flow characteristics of the ocean atmospheric boundary layer based on the OpenFOAM platform comprises the following steps: dividing grids for an established three-dimensional calculation drainage basin to obtain three-dimensional drainage basin grids; establishing a computational fluid mechanics model; setting boundary conditions and calculation parameters; and performing flow field numerical calculation on the three-dimensional drainage basin grid based on the established computational fluid mechanics model and the set boundary conditions and calculation parameters to obtain the marine atmospheric boundary flow characteristics.

The invention provides a digital signature method based on identity. The method comprises the following steps: a system parameter is generated which is used for signature and signature verification; aprivate key of a user is generated according to identity information of the user and the system parameter; the private key is used for signature on information; signature verification is carried on the signature on information according to the system public parameter and the identity of a signer. For some calculations of verification equation arithmetic in signature arithmetic is determined as constants by system parameter, precomputation is carried out when system parameter is generated, which greatly reduces calculation cost of verification equation; When signatures is carried out on the same user with different information, special treatment (detailed specification is in the text) is carried out to greatly lower communication cost. After such treatment, operation efficiency of the system is improved greatly on the basis of not lowering safety.

The invention discloses a super-threshold multi-party privacy set intersection method based on oblivious pseudo-random secret sharing, which is characterized in that an oblivious programmable pseudo-random secret sharing (OPPR-SS) protocol is designed based on an OPPRF component and an SS component, and the protocol has the following structure: parameters: a sender S having a set Y: {y1,..., yn}; and the receiver R has the element x. An OPRF function and an OKVS function: Fk (.), j belongs to [1, n]; and inputting: inputting an element x by a receiver. The oblivious programmable pseudo-random secret sharing protocol is abbreviated as an OPPR-SS protocol in English. According to the method, construction can be carried out on constants only by using symmetric keys and secret sharing, and the method has better calculation efficiency under the condition that the communication round number and the communication complexity are consistent. The OPPR-SS component constructed by the invention can be used as an independent new cryptographic component, and can complete specific input with a security attribute to generate specific output with a (t, n) reconstruction attribute.

The embodiment of the invention discloses an information determination method. The method comprises the steps that historical strategies corresponding to to-be-processed information and the executionefficiency of each historical strategy are acquired; generating a first data set based on the historical strategies and the execution efficiency of each historical strategy; obtaining a first parameter corresponding to the to-be-processed information when the to-be-processed information is executed currently; and determining a target strategy for executing the to-be-processed information based onthe first data set and the first parameter. The embodiment of the invention further discloses electronic equipment and a computer storage medium.

The invention discloses a method for calculating the transportation distance of an open pit coal mine inner row. The transportation path and distance of a stripped object can be calculated according to a transportation starting point and a transportation ending point. According to the method, the inner discharging transportation process of the strip mine is simplified; the open pit coal mine end slope geometric characteristics are simplified; an end slope reference multi-segment line is used to perform the geometric mathematical representation on parameters such as slope angles, an end slope offset multi-section line at the elevation of a transportation starting point / ending point is calculated according to the input data of the transportation starting point and the transportation ending point, and a horizontal transportation path and distance and a vertical transportation climbing / downhill distance are obtained by the further calculation.

The invention discloses an air-ground collaborative edge calculation method and system. The air-ground collaborative edge calculation method specifically comprises the following steps: setting initialization information; in response to the completion of the initialization parameters, performing distribution of calculation tasks; in response to completion of allocation of the calculation task, performing allocation of communication resources; in response to completion of communication resource allocation, performing allocation of computing resources; determining the trajectory of the unmanned aerial vehicle in response to the completion of the allocation of the computing resources; in response to completion of trajectory determination of the unmanned aerial vehicle, determining a duration value; in response to the determination of the completion duration value, updating the calculation efficiency; judging whether the calculation efficiency meets preset convergence precision or not; and if yes, outputting the allocation result of the communication resources, the allocation result of the computing resources, the track of the unmanned aerial vehicle and the duration value as optimal results. According to the invention, the purposes of system resource allocation including communication resources and computing resources and combined unmanned aerial vehicle flight path design are achieved.

The present invention relates to an analytical type spatial de-aliasing method for a microphone array. The method includes the following steps that: the microphone array receives sound source signals,and the sound source signals are converted into digital sound signals; the spectra of the digital sound signals are extracted, so that the spectra of the digital sound signals of each microphone in the microphone array can be obtained; a spatial correlation matrix at each frequency point can be estimated according to the spectra of the digital sound signals of each microphone; the spatial correlation matrix at each frequency point is decomposed, so that a main feature vector can be obtained, each component of the main feature vector is corresponding to the acquired signals of one microphone;time phase difference between any two microphones is obtained according to the main feature vector at each frequency point; and a periodic number combination is obtained through an anti-aliasing formula according to the time phase difference between the microphones, and an optimal periodic value can be found out from the periodic number combination.

The present invention relates to a method of implementing the negative survey and reconstructing the positive data. The method comprises the steps of implementing the negative survey according to the form of the negative survey, at the same time, extracting a small number of samples to implement the positive survey corresponding to the title of the negative survey; gathering the data to obtain the negative selection matrixes of each option and a total sample number; carrying out the correlation analysis on the small number of samples after the positive survey and the negative survey to obtain a reconstruction matrix; according to a matrix constraint condition of the negative survey, adjusting the reconstruction matrix; applying the maximum likelihood estimation and the constraint condition of the negative survey to obtain an optimal reconstruction result. Based on the background knowledge and the event maximum likelihood estimation, the present invention provides a negative survey implementation and reconstruction method which can provide the reference for the real application mode of the negative survey, at the same time, and enables the negative data reconstruction accuracy to be improved.