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44 results about "Global local" patented technology
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Segmentation of objects by minimizing global-local variational energy
InactiveUS20070122039A1Robust accurate estimationImage enhancementImage analysisImage segmentationBackground distribution
Owner:MICROSOFT TECH LICENSING LLC
Image enhancement based on multiple frames and motion estimation
ActiveUS20090231449A1Television system detailsColor television detailsMultiple frameMotion estimation
A system and method for capturing images is provided. In the system and method, preview images are acquired and global local and local motion are estimated based on at least a portion of the preview images. If the local motion is less than or equal to the global motion, a final image is captured based at least on an exposure time based on the global motion. If the local motion is greater than the global motion, a first image is captured based on at least a first exposure time and at least a second image is captured based on at least one second exposure time less than the first exposure time. After capturing the first and second images, global motion regions are separated from local motion regions in the first and second images, and the final image is reconstructed at least based on the local motion regions.
Owner:QUALCOMM INC
Global-local optimization model based on multistage convolution neural network and significant detection algorithm
The invention provides a significant detection algorithm based on a multistage convolution neural network. The algorithm comprises the following steps of using a global estimation model of a large receptive field to carry out global significance estimation; during a global estimation model training process, using a full connection layer as an output layer to train and initialize parts of convolution layer parameters; using a plurality of alternative convolution layers and liter sampling layers to replace the full connection layer and training and acquiring an optimal global significance estimation graph; using a local convolution neural network with a small receptive field and a large output picture size to fuse global and local information to acquire a high quality significance graph. Through processing of the local convolution neural network, an original image is served as input of the model. A final output result possesses a same size with an original input image and is clear. By using the significant detection algorithm based on the multistage convolution neural network, compared to a traditional method, high accuracy is possessed; a significant object can be accurately found and simultaneously a contour is clear.
Owner:XI AN JIAOTONG UNIV
Method and device for constructing legal text syntax tree based on deep neural network
ActiveCN106202010ASolve the problem of semantic deviationText processingBiological neural network modelsLanguage understandingAlgorithm
The invention provides a method and device for constructing a legal text syntax tree based on a deep neutral network. The method comprises the following steps: acquiring a training text of the legal service; performing word vector sparse representation on the training text; performing semantic annotation on the training text through the DNN according to the word vector sparse representation; performing dependency description on the training text according to the semantic annotation to construct the legal text syntax tree. The invention provides a systematic method to construct the syntax tree about technical language understanding in the legal service field, and the global-local training is used for solving the semantic bias problem in the legal language understanding.
Owner:CHONGQING MEGALIGHT TECH CO LTD
Segmentation of objects by minimizing global-local variational energy
InactiveUS7706610B2Robust accurate estimationImage enhancementImage analysisImage segmentationBackground distribution
An “Image Segmenter” provides a variational energy formulation for segmentation of natural objects from images. In general, the Image Segmenter operates by adopting Gaussian mixture models (GMM) to capture the appearance variation of objects in one or more images. A global image data likelihood potential is then computed and combined with local region potentials to obtain a robust and accurate estimation of pixel foreground and background distributions. Iterative minimization of a “global-local energy function” is then accomplished by evolution of a foreground / background boundary curve by level set, and estimation of a foreground / background model by fixed-point iteration, termed “quasi-semi-supervised EM.” In various embodiments, this process is further improved by providing general object shape information for use in rectifying objects segmented from the image.
Owner:MICROSOFT TECH LICENSING LLC
Weighted convolutional autoencoder-long short-term memory network-based crowd anomaly detection method
ActiveCN108805015ASuppress interferenceIncrease reconstruction errorCharacter and pattern recognitionNeural architecturesShort-term memoryOriginal data
The invention discloses a method for performing anomaly detection by a weighted convolutional autoencoder-long short-term memory network (WCAE-LSTM network). The method is devoted to perform anomaly detection and positioning by learning a generation model of a mobile pedestrian, thereby guaranteeing the public safety. The invention provides a novel double-channel framework, which learns generationmodes of an original data channel and a corresponding optical flow channel and reconstructs data by utilizing the WCAE-LSTM network, and performs the anomaly detection on the basis of a reconstruction error. In addition, for the problem of complex background, it is proposed that a sparse foreground and a low-rank background are separated by adopting modular robust principal component analysis decomposition; and a weighted Euclidean loss function is designed according to obtained background information, so that background noises are inhibited. The designed WCAE-LSTM network can not only perform the anomaly detection globally but also roughly locate an abnormal region locally; and through the joint consideration of global-local anomaly analysis and optical flow anomaly analysis results, finally robust and accurate detection of abnormal events is realized.
Owner:CHANGZHOU UNIV
Semiconductor memory device
InactiveUS20090251948A1Improve operating profitStabilizing sense amplification.Digital storageBit lineAudio power amplifier
In a semiconductor memory device, a memory cell is connected with a local sense amplifier and a global sense amplifier via a local bit line and a global bit line. The local sense amplifier is a single-ended sense amplifier including a single MOS transistor, which detects a potential of the local bit line which varies when reading and writing data with the memory cell. The threshold voltage of the MOS transistor is monitored so as to produce a high-level write voltage and a low-level write voltage, which are corrected and shifted based on the monitoring result so as to properly perform a reload operation on the memory cell by the global local sense amplifier. Thus, it is possible to cancel out temperature-dependent variations of the threshold voltage and shifting of the threshold voltage due to dispersions of manufacturing processes.
Owner:LONGITUDE LICENSING LTD
Pedestrian re-identification method and device based on global features and coarse granularity local features
InactiveCN107766791AExact matchThe recognition effect is accurateCharacter and pattern recognitionSpecial data processing applicationsComputation complexityImaging processing
Owner:PEKING UNIV
Global-local RGB-D multimode-based gesture recognition method
ActiveCN108388882AGesture recognition performance improvementWide application backgroundCharacter and pattern recognitionRgb imageUser input
The invention discloses a global-local RGB-D multimode-based gesture recognition method. An inputted gesture video is expressed mainly through data modes comprising a bone position, an RGB image, a depth image and an optical flow image; after the multimode gesture data expression is obtained, a method of a convolution neural network and a recurrent neural network is used to carrying out feature expression on gesture data in different modes, and the features obtained in different modes are used for gesture classification; and finally, different classes of gesture scores obtained in different modes are fused to obtain a multimode-based gesture classification result finally. The method can be applied to a client or a cloud for recognizing a gesture video inputted by the user, and through gesture input, a computer or mobile phone software or hardware makes a corresponding response.
Owner:SUN YAT SEN UNIV
Global-local-low-rank-based image salient target detection method
The invention discloses a global-local-low-rank-based image salient target detection method. The method comprises the followings steps: step (1), obtaining an initial salient image; step (2), carrying out global and local low-rank processing; and step (3), carrying out global and local salient image combination; to be specific, combining a global salient image and a local salient image, providing different weights based on contributions of the two images and carrying out fusion to obtain a final result. According to the invention, an image initial salient image is obtained by combining a CIE Lab color space contrast feature; and non-salient information of the initial salient image is inhibited in the global and local ways. Because the obtained salient image contains less background non-salient information, the processing result can be applied to more tasks like computer vision and image processing. The less background non-salient information the salient target image contains, the clearer and more reliable the obtained salient target becomes.
Owner:LANZHOU UNIVERSITY OF TECHNOLOGY
A data dimension reduction method based on a tensor global-local preserving projection
ActiveCN103605985AGood dimensionality reduction effectCharacter and pattern recognitionHat matrixDimensionality reduction
A data dimension reduction method based on a tensor global-local preserving projection comprises the following steps: (1) data samples are selected to form a sample set which is to be subjected to dimension reduction; (2) distances between sample pairs are calculated; (3) neighborhoods of sample points are divided to obtain close neighbor points and non-close-neighbor points; (4) neighboring right matrixes and non-neighboring right matrixes are established according to close neighbor relations and not-close-neighbor relations among the samples; (5) An object function corresponding to data global and local structure preserving is established, and an optimization problem is constructed; (6) the optimization problem is converted to a generalized eigenvalue problem, and a projection matrix is obtained through solving the problem; and (7) projection is carried out on the sample set to obtain dimension reduction data. Targeting at a dimension reduction problem of second order tensor data, the invention provides the data dimension reduction method which can simultaneously carry out excavation on the global and local structures of the data, which is good in dimension reduction effects and which are based on the tensor global-local preserving projection.
Owner:ZHEJIANG UNIV OF TECH
Method for analyzing residual compression strength of composite materials after impact damage
ActiveCN106202598AEfficiently predict residual strengthSpecial data processing applicationsUltrasound attenuationResidual strength
The invention belongs to the field of structural damage tolerance design of composite materials, and specifically relates to a method for analyzing residual compression strength of composite materials after impact damage; and the method is used for determining the residual compression strength of composite materials after impact damage. The method comprises three steps of 1, selecting a Hanshin failure criterion as a damage failure criterion for low-speed impact of a laminated plate according to failure characteristics of a composite material; 2, importing the Hanshin failure criterion by adopting a large-scale dynamic finite element program DYTRAN, so as to calculate a damage area under the low-speed impact of the laminated plate; and 3, carrying out rigidity attenuation on a damage area after the low-speed impact according to the damage area determined in the second step, and calculating the residual compression strength of the laminated plate after the low-speed impact by adopting a global-local model analysis method. The invention discloses a brand new analysis method, so that the residual strength of typical components of composite materials after impact damage can be effectively predicted, and basis is provided for the structural design, analysis and verification of the composite materials of airplanes.
Owner:HARBIN
Pedestrian image feature classification method and system
InactiveCN106709478ASatisfy the strict conditions required by the input sampleGuaranteed robustnessCharacter and pattern recognitionData expansionClassification methods
The invention provides a pedestrian image feature classification method and system, and the method comprises the steps: carrying out the data expansion of a pedestrian image sample in a sample dataset; carrying out the grouping of the pedestrian image sample in the sample dataset after expansion, and obtaining a plurality of pedestrian sample groups; selecting samples, building a multi-channel convolution neural network, and extracting the global and local features of the sample data through the multi-channel convolution neural network; setting a loss function, calculating a loss value of the multi-channel convolution neural network, and optimizing the multi-channel convolution neural network; carrying out the feature classification of each global-local feature through the optimized multi-channel convolution neural network, and obtaining the feature class of each pedestrian sample group. The method enables the sample data to be expanded, meets the condition that triple loss exerts strict requirements for an input sample, can guarantee the robustness through employing multi-loss to optimize the multi-channel convolution neural network, and is suitable for the processing of pedestrian image features of a plurality of scenes.
Owner:GUILIN UNIV OF ELECTRONIC TECH
Image description method
InactiveCN110390363AReduce the impactImprove performanceCharacter and pattern recognitionNatural language data processingFault toleranceImage description
The invention discloses an image description method, and the method comprises the steps: extracting global image features in a picture through a VGG convolution neural network, and extracting local image features in picture by using Faster R-CNN network, fusing global image features and local image features through a global-local feature fusion algorithm to acquire the image fusion features; processing image fusion features through a bidirectional long-short-term memory network with an attention mechanism; and generating a preliminary image description statement, performing WordNet word vectorsimilarity calculation based on the image target information obtained during local image feature extraction and nouns in the preliminary image description statement, correcting the image descriptionstatement, and generating a final image description statement. According to the method, the influence of useless information is reduced, the expression of key information is enhanced, the fault tolerance and generalization ability of the model are enhanced, and the accuracy of statement description is improved.
Owner:SHANGHAI MARITIME UNIVERSITY
High-speed train real-time monitoring oriented mass data management method
ActiveCN105243140APositive application valueImplement performance storageRelational databasesSpecial data processing applicationsRelational databaseGlobal local
The present invention provides a high-speed train real-time monitoring oriented mass data management method. According to the method, a two-layer storage architecture is formed by a distributed file system and a relational database, and a mileage triggered oriented window data management mechanism is established on an upper layer based on the relational database to realize the organization of monitored data; and by utilizing the distributed file system at a lower layer, balanced storage management of mass data is implemented. Ordered organization of the data can be realized in combination with a storage model of object dynamic coupling on the basis; and meanwhile, by using a way of global-local property delivery management and establishing mileage accumulated triggering for trains, demands of train monitoring and analyzing are met. Aiming at high-speed train real-time monitoring, the high-speed train real-time monitoring oriented mass data management method provides core technologies of massive and cross-discipline data management under the large data background and has active application value in the fields of transportation, logistics, smart city and the like.
Owner:INST OF SOFTWARE - CHINESE ACAD OF SCI
A method for controlling alignment of pre-fabricated segmental beams based on a short-line matching method
ActiveCN109543216AImprove calculation accuracyImprove analysis accuracyGeometric CADDesign optimisation/simulationBridge engineeringSoftware engineering
The invention relates to the technical field of alignment control of pre-assembled segmental beams in bridge engineering, in particular to a method for controlling alignment of pre-fabricated segmental beams based on a short-line matching method. The method comprises the following steps: S1, performing on-site data measurement; S2, establishing a local global coordinate conversion system; S3, n-1# block 6 control point measured local coordinates are converted into measured global coordinates data; S4, deviation analysis is performed on the -1 # block; S5, determining the coupling angle of n-1 #two end axis and performing decoupling; S6, calculating the correction coordinates of the I end of the n # block; S7, judging whether the adjustment is made to the n + 1 # block; S8, judging whether there is deviation in the construction of the n # block, and if so, adjusting the positioning point of the I end section of the n + 1 # block; S9, obtaining the local coordinate data of the six control points when the n # block is used as the matching block to prefabricate the n + 1 # block through the global-local coordinate conversion, which has the beneficial effect that the real beam block axis deviation angle can be obtained, and the calculation accuracy of the corrected coordinate of the prefabricated beam block is improved.
Owner:SOUTH CHINA UNIV OF TECH
Semiconductor memory device
InactiveUS7933141B2Improve operating profitStabilizing sense amplification.Digital storageBit lineAudio power amplifier
In a semiconductor memory device, a memory cell is connected with a local sense amplifier and a global sense amplifier via a local bit line and a global bit line. The local sense amplifier is a single-ended sense amplifier including a single MOS transistor, which detects a potential of the local bit line which varies when reading and writing data with the memory cell. The threshold voltage of the MOS transistor is monitored so as to produce a high-level write voltage and a low-level write voltage, which are corrected and shifted based on the monitoring result so as to properly perform a reload operation on the memory cell by the global local sense amplifier. Thus, it is possible to cancel out temperature-dependent variations of the threshold voltage and shifting of the threshold voltage due to dispersions of manufacturing processes.
Owner:LONGITUDE LICENSING LTD
A mesh surface curve design method based on distance constraint
ActiveCN109360272AImprove efficiencyImprove robustness3D modellingDistance constraintsCutting-plane method
The invention discloses a mesh surface curve design method based on distance constraint. The designed curve passes through a given interpolation point and is smooth (in the sense of discreteness) andstrictly located on the mesh surface. The method transforms the complex manifold constraints into distance constraints and describes them as optimization problems together with smooth constraints andinterpolation constraints. The local surface is approximated by the tangent plane, and the distance constraint is relaxed to the distance from the point to the tangent plane. Because the points on thecurve used to calculate the distance are interdependent with their corresponding tangent points, a global-local iterative strategy is adopted and Gauss- Newton idea method is used to control its convergence behavior: in the whole stage, it is relaxed into a convex optimization problem by distance approximation to solve the iterative step size; In the local phase, a robust and efficient projectionmethod is used to map the optimized curves to the surface to update the tangent points. Finally, all the relaxed polygons are mapped to the mesh surface by using the cutting plane method. Compared with the existing methods, this method has many advantages in efficiency, robustness and application range.
Owner:ZHEJIANG SCI-TECH UNIV
Data dimension reduction method based on data global-local structure preserving projections
InactiveCN103605889AGood dimensionality reduction effectSpecial data processing applicationsHat matrixHigh dimensional
A data dimension reduction method based on data global-local structure preserving projections includes the following steps: 1), creating a sample set and calculating Euclidean distances among sample pairs; 2), diving territory of each sample point to acquire neighboring points and non-neighboring points; 3), creating a neighboring-right matrix and a non-neighboring-right matrix of the sample set; 4), creating target functions corresponding to data global structure preservation and data local structure preservation, and constructing optimization problems; 5), transforming the optimization problems into generalized eigenvalue problems, and creating a projection matrix according to feature vectors acquired by solution; 6), projecting the sample set to obtain dimension reduced data. According to the method, global and local structures of high-dimensional data are maintained during dimension reduction, the dimension reduced data can describe basic features of original high-dimensional data completely and accurately, and accordingly, data dimension reduction effect is improved.
Owner:ZHEJIANG UNIV OF TECH
Sparse multi-view-angle three-dimensional reconstruction method for indoor scene
ActiveCN110288712AEasy to implementAchieve satisfactionImage enhancementImage analysisReconstruction methodComputer graphics
The invention belongs to the field of computer vision and computer graphics, and aims to ensure the universality of the application of the technology and generate a relatively accurate three-dimensional model. The technical scheme adopted by the invention is as follows: the sparse multi-view three-dimensional reconstruction method for the indoor scene comprises the following steps of: obtaining depth information and semantic information based on a deep learning method, and then realizing model fusion of each sparse view angle by using a global-local registration method, wherein the global-local registration method specifically comprises the steps of filtering and smoothing the depth map by using a method of establishing a patch by using a single view angle, converting the depth map under each view angle into point cloud and carrying out fusion. The method is mainly applied to image processing occasions.
Owner:TIANJIN UNIV
Freehand interactive three-dimensional model retrieval method based on high-level semantic property comprehension
ActiveCN108170823AEffectively respond to complex changesImprove retrieval efficiencyCharacter and pattern recognitionSpecial data processing applicationsSemantic propertyData-driven
The invention provides a freehand interactive three-dimensional model retrieval method based on high-level semantic property comprehension. According to the method, first, a data driving mode is utilized to extract global-local semantic properties of freehand sketches under different styles and categories, and a semantic property space of the freehand sketches is defined; second, on the basis of the defined semantic property space, automatic annotation of semantic properties is performed on a three-dimensional model in a database according to content characteristics corresponding to the three-dimensional model; and last, the semantic properties of the freehand sketches and the semantic properties of the three-dimensional model in the database are mapped to the same measurement space by means of constructing a semantic property tree for comparison, and if the similarity between the semantic properties of the freehand sketches and the semantic properties of the three-dimensional model reaches a set similarity, information of the three-dimensional model is fed back, and retrieval is completed. Through the method, deviation brought by an existing freehand interactive three-dimensionalmodel retrieval algorithm through which a three-dimensional model cannot be compared with freehand sketches unless the three-dimensional model is projected into a two-dimensional view is avoided.
Owner:JIANGXI NORMAL UNIV
Video description method based on cyclic convolution decoding of a complementary attention mechanism
InactiveCN109919114ASolve the problem that it is easy to ignore the details of the videoImprove long-distance dependenceCharacter and pattern recognitionData setComputer vision
The invention discloses a video description method based on complementary attention mechanism cyclic convolution decoding. The video description method is used for generating short and accurate description for a given video clip. The method specifically comprises the following steps: obtaining a video data set for training a video description generation model, and defining an algorithm target; modeling a global time sequence feature and a local semantic feature in the video data set; establishing a complementary attention mechanism on a circular convolutional decoder based on global-local features; using the model to generate a description of an input video. The method is suitable for video description generation of a real video scene, and has a good effect and robustness for various complex conditions.
Owner:ZHEJIANG UNIV
Aggregation node location method based on improved discrete difference algorithm
ActiveCN105959912AImprove reliabilityImprove service qualityNetwork topologiesLocation information based serviceLocal optimumDifferential algorithm
The present invention provides an aggregation node location method based on an improved discrete difference algorithm. The influence of the isomerism of nodes and the reliability of the routing path in real engineering on aggregation node location is fully considered, an adaptive zoom factor is introduced into the improved discrete difference algorithm to allow the algorithm to maintain high global search capability at the initial stage and maintain high global local search capability at the later period; an adaptive variation mechanism is introduced, an appropriate variation strategy is selected according the trend of the population evolution in the evolution process to maintain the diversity of the population and avoid falling into the local optimum so as to improve the global optimization capability of the discrete difference algorithm, rapidly converging the algorithm and solve the technical problems of the precocity convergence and falling into the local minimum of the original difference algorithm at the discrete variable optimization, and therefore the optimized aggregation node location disposition is obtained, the data communication reliability is enhanced, and the network service quality is improved.
Owner:CHONGQING TECH & BUSINESS UNIV
Image enhancement based on multiple frames and motion estimation
A system and method for capturing images is provided. In the system and method, preview images are acquired and global local and local motion are estimated based on at least a portion of the preview images. If the local motion is less than or equal to the global motion, a final image is captured based at least on an exposure time based on the global motion. If the local motion is greater than the global motion, a first image is captured based on at least a first exposure time and at least a second image is captured based on at least one second exposure time less than the first exposure time. After capturing the first and second images, global motion regions are separated from local motion regions in the first and second images, and the final image is reconstructed at least based on the local motion regions.
Owner:QUALCOMM INC
Method for extracting complete periodic waveform
InactiveCN108647661AAvoid interferenceEasy accessCharacter and pattern recognitionComputer scienceSignal processing
The invention provides a method for extracting a complete periodic waveform, belonging to the signal processing field. The invention adopts the technology of combining global local extremum, successfully overcomes the interference of waveform glitch, intercepts the complete periodic waveform from the starting position of the rising edge, and facilitates the acquisition of the periodic signal waveform in scientific research.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA
Heterogeneous network recommendation algorithm based on deep neural network
ActiveCN111832724AReduce distractionsNeural architecturesPhysical realisationPathPingRecommendation model
The invention discloses a heterogeneous network recommendation algorithm based on a deep neural network. The heterogeneous network recommendation algorithm comprises the following steps: S1, representing vectors of global local information of users and articles; S2, automatically selecting meta-path types by utilizing a bolt genetic algorithm; S3, obtaining meta-path instances under the optimal Xmeta-path types; S4, obtaining an interaction vector based on the meta-path; S5, fusing global local information of the user and the article; S6, enhancing the vector representation of the user and the object by using a collaborative attention mechanism; S7, obtaining scores of the user and the article pair; S8, building loss function optimization parameters; and S9, repeating the steps 1-8, and when lu, i stably tends to a very small threshold epsilon (epsilon) 0), stopping training to obtain a heterogeneous network recommendation model based on the deep neural network. According to the invention, valuable meta-path types are automatically obtained by utilizing a genetic algorithm, so that the interference of human factors is reduced; and global and local information in the heterogeneousnetwork are mined through the node domain and the network structure information.
Owner:NORTHWESTERN POLYTECHNICAL UNIV
Global-local adaptive optimization panoramic light field splicing method
PendingCN112465704AReasonable effectImprove accuracyGeometric image transformationDetails involving image mosaicingPattern recognitionComputer graphics (images)
The invention discloses a panoramic light field splicing method based on global local adaptive optimization. The panoramic light field splicing method comprises the following steps: inputting a plurality of light fields to be spliced; extracting, matching and screening feature points of the to-be-spliced light fields to calculate a global homography transformation matrix of all the to-be-spliced light fields; respectively carrying out 4D meshing on the plurality of to-be-spliced light fields, evaluating the global registration precision of each grid according to the global homography transformation matrix, calculating a local homography transformation matrix of the grid of which the global registration precision is lower than a preset threshold, and evaluating the local registration precision of the corresponding grid according to the local homography transformation matrix; and comparing the global registration precision with the local registration precision, taking the homography transformation matrix with the highest precision for each grid, and fusing the light fields to obtain a splicing result. According to the invention, the overall and detail splicing results of the light field are most accurate, so that an accurate multi-light-field panoramic splicing method is realized.
Owner:SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
Global local time representation method for video-based pedestrian re-identification
ActiveCN111563404AReduce occlusionReduce noiseCharacter and pattern recognitionNeural architecturesData setAlgorithm
The invention provides a global local time representation method for video-based pedestrian re-identification. A network provided by the invention is composed of a DTP convolution model and a TSA model. The DTP is composed of time convolution expanded in parallel and used for simulating short-term time clues between adjacent frames. The TSA captures global time cues using relationships between non-contiguous frames. Experimental results on five reference data sets show that the proposed GLTR method is superior to the most advanced method at present.
Owner:PEKING UNIV
Global and local batch process fault detection method based on dynamic orthogonality
ActiveCN109085816AEliminate Dynamic Timing DependenciesEliminate dynamicsElectric testing/monitoringTime lagCharacteristic space
The invention provides a global and local batch process fault detection method based on dynamic orthogonality, which comprises the following steps of: (1) collecting each key variable data when a batch process is normally operated, and forming a training sample X which is an element of a set of RI*J*K in a normal operation state; (2) firstly expanding the training sample X into two-dimensional data X which is an element of a set of RI*KJ along a batch direction, then carrying out standardization on the expanded two-dimensional data, and rearranging the standardizated two-dimensional data intoX which is an element of a set of RKI*J; (3) on the basis of the two-dimensional data X which is the element of the set of RKI*J, establishing a time lag matrix XD to eliminate timing autocorrelationof a process variable; (4) constructing a dynamic orthogonal global local model for the established time lag matrix XD; (5) respectively establishing T2 and SPE statistical models in a characteristicspace and a residual space, and gaining a control limit; (6) collecting online process data and carrying out standardization processing; and (7) carrying out projection on the online data by utilizingthe established dynamic orthogonal global local model, and by the T2 and SPE statistical models, judging occurrence of a fault.
Owner:LANZHOU UNIVERSITY OF TECHNOLOGY
Method and system for acquiring global rainfall information at different places by utilizing rainfall data set
The invention discloses a method and system for acquiring global rainfall information at different places by using a rainfall data set, and the method comprises the steps: collecting and summarizing the global rainfall data set, and obtaining global rainfall data taking the world time as a reference; converting the global rainfall data taking the world time as the benchmark into global rainfall data taking the designated local time as the benchmark; taking the global rainfall data taking the world time as the benchmark of any three adjacent days as an original data set, and obtaining global rainfall data of one hour interval of the next day by adopting adjacent point interpolation, so as to obtain gridding global rainfall data of one hour interval taking the designated local time as the benchmark; and calculating annual average hourly rainfall of the local time according to the global rainfall data of all days of the local time. According to the method, the nearest neighbor interpolation method is adopted, the method is simple and convenient, the operation speed is high, and the global local rainfall result can be obtained in a short time.
Owner:NAT SPACE SCI CENT CAS
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