231 results about "Correlation index" patented technology

Upon selecting the stock portfolio, a plurality of corporate valuation index related data containing an intellectual asset related index is acquired (steps S1 to S6), analysis is performed with the acquired corporate valuation index related data and a company ranking corresponding to at least one prescribed index is created (steps S7 to S13 and S19), a prescribed number of companies is selected from the created company ranking (step S14), an investment ratio is selected in relation to each of the selected companies (step S15), and, based on the obtained distribution result of the investment ratio, a stock portfolio corresponding to the selected company is created and output (steps S16, S17). Therefore, a device for automatically selecting a more preferable stock portfolio based on the results upon performing a comprehensive valuation of companies using a corporate valuation index containing an intellectual asset related index is provided.

The embodiment of the invention discloses a commodity searching method and a device adopting the same. The method comprises the following steps: commodity key words input by a user are received and used for searching the relevant commodities; recorded information corresponding to the commodity key words is inquired in the recorded information according to the commodity key words, and the recorded information comprises the commodity key words, categories and correlation indexes; the categories are sequenced according to the level of the correlation indexes, and the sequence result of the commodities corresponding to the categories is acquired; and the sequence result is sent to the terminal of the user. By adopting the embodiment of the invention, the user can quickly obtain the wanted commodities, the result accuracy in searching commodities in the network is improved, and better experience is brought for the user to search commodities in the network.

A method for commissioning sensors includes determining correlation data between the sensors and a plurality of actuators. The correlation data is based upon conditions detected by the sensors at a plurality of actuator settings. Correlation indexes are calculated from the correlation data, where a correlation index for a sensor is a function of the plurality of actuator settings and a particular actuator. In addition, each of the sensors is assigned to at least one of a plurality of actuator families based upon the calculated correlation indexes of the sensors to thereby commission the sensors.

A process is provided that is directed to a steam pyrolysis zone integrated with a hydrotreating zone and a solvent deasphalting zone to permit direct processing of crude oil feedstocks to produce petrochemicals including olefins and aromatics. The integrated hydrotreating, solvent deasphalting and steam pyrolysis process comprises charging the crude oil to a hydroprocessing zone operating under conditions effective to produce a hydroprocessed effluent reduced having a reduced content of contaminants, an increased paraffinicity, reduced Bureau of Mines Correlation Index, and an increased American Petroleum Institute gravity; charging the hydroprocessed effluent to a solvent deasphalting zone with an effective amount of solvent to produce a deasphalted and demetalized oil stream and a bottom asphalt phase; thermally cracking the deasphalted and demetalized oil stream in the presence of steam to produce a mixed product stream; separating the mixed product stream; purifying hydrogen recovered from the mixed product stream and recycling it to the hydroprocessing zone; recovering olefins and aromatics from the separated mixed product stream; and recovering pyrolysis fuel oil from the separated mixed product stream.

An integrated hydrotreating and steam pyrolysis process for the direct processing of a crude oil is provided to produce olefinic and aromatic petrochemicals. Crude oil and hydrogen are charged to a hydroprocessing zone operating under conditions effective to produce a hydroprocessed effluent reduced having a reduced content of contaminants, an increased paraffinicity, reduced Bureau of Mines Correlation Index, and an increased American Petroleum Institute gravity. Hydroprocessed effluent is thermally cracked in the presence of steam to produce a mixed product stream, which is separated. Hydrogen from the mixed product stream is purified and recycled to the hydroprocessing zone, and olefins and aromatics are recovered from the separated mixed product stream.

A storage device may include a nonvolatile storage and a storage controller. The nonvolatile storage may include a map table which stores information including a logical address, a physical address corresponding to the logical address and a correlation index designating the physical address. The storage controller is configured to transmit the information to an external host device, and to access the nonvolatile storage based on a request and the correlation index, each of the request and the correlation index transmitted from the host device.

A method for correlating information across distinct domains without requiring feature co-occurrence. The disparate information collections are broken down into features, and a correlation index with correlation score is created. To determine the correlation between distinct domains, an information artifact collection is reduced to a representational set of features, these features are replaced with correlated features using the correlation index, and the new set of features is matched against the second information artifact collection using an appropriate comparison technique. The correlation method allows a single input artifact to be matched against an existing collection, resulting in a set of correlated artifacts from the disparate collection, each ranked by correlation score.

The invention discloses an automatic parking locus optimization method based on a full-simultaneous dynamic optimization framework, and brings forward a vehicle-environment integrated modeling dynamic optimization framework based on full-simultaneous solution strategy, for the purposes of solving the problem of safe parking at a narrow parking space within shortest time due to fast rhythm of cities, effectively eliminating influences exerted by different parking space shapes on locus planning strategies and optimizing a safe bump-free locus which has nonholonomic constraints and satisfies low-speed parking of vehicles within the shortest time. The method provided by the invention is crucially characterized in that vehicle-parking space obstacle avoidance integrated modeling is realized by use of an MPCC mathematic optimization technology, and at the same time, can optimize correlation indexes of vehicle kinetics and dynamics. According to the method, control information such as the speed, the front-wheel corner, the accelerated speed, the front-wheel angular velocity and the like of a vehicle tracking optimization locus can be directly obtained, and actual parking assistance is facilitated.

The invention discloses an aero-engine service life prediction method based on label-free, unbalanced and initial value uncertain data, which comprises the following steps of firstly, carrying out feature screening on an engine training data set by utilizing a correlation index and a trend index; then, obtaining a health state label through quantum fuzzy clustering, training a multivariable deep forest classifier, and obtaining an aero-engine health assessment model; meanwhile, training a long-short cycle memory neural network (LSTM) time sequence prediction model by utilizing the engine training data set; and finally, obtaining the maintenance time and the final residual service life (RUL) of the engine at different health stages by using the engine test data set according to the trainedhealth assessment model and the time sequence prediction model. According to the method, the defects of no label, imbalance and initial value uncertainty of observation data are overcome, and a technical reference is provided for maintenance decisions of the aero-engine in different subsequent health stages.

The invention discloses a fault prediction method and device for industrial equipment based on an LSTM circulating neural network, wherein the method comprises the following steps of: acquiring a state monitoring data set of a plurality of sensors at the periphery of target equipment, wherein the state monitoring data set comprises monitoring data from 0 moment to a current moment; selecting a prediction characteristics containing preset fault information from the state monitoring data set by utilizing a characteristic selection standard, wherein the characteristic selection standard comprisesa correlation index and a monotonicity index; performing characteristic conversion on the prediction characteristics to obtain a prediction characteristic vector; and performing single-step fault prediction, long-term fault prediction and residual life prediction on the target equipment according to the prediction characteristic vector and a fault prediction network model. The method can effectively avoid insufficient prediction precision caused by unreasonable preset fault threshold, can give a confidence interval under the occasion of single-step performance prediction, and can achieve long-term prediction of performance and residual service life of the equipment.

The invention discloses a variable frequency scroll compressor fault diagnosis method based on improved VMD and SVM, and the method carries out the processing and analysis of a vibration signal of a variable frequency scroll compressor from three aspects: signal processing, feature extraction and classification recognition, and comprises the steps: firstly carrying out the vibration test of the variable frequency scroll compressor; acquiring vibration acceleration signals under different states of normality, scroll plate faults, bearing faults and crankshaft faults of the variable-frequency scroll compressor, and obtaining data samples of different fault types; taking the envelope entropy-correlation index as a fitness function, adopting a sparrow search algorithm (SSA) to optimize a variational mode decomposition (VMD) algorithm to process the vibration signal of the variable frequency scroll compressor, and obtaining intrinsic mode functions of different scales; and calculating multi-scale permutation entropies of different intrinsic mode functions to form a feature vector, inputting the feature vector into a classifier established based on a support vector machine (SVM) for training and predictive classification, and judging the fault type of the variable-frequency scroll compressor.

The invention relates to an assisting image matching method by means of airborne lidar point cloud data. The assisting image matching method by means of the airborne lidar point cloud data includes the steps of obtaining a reference image, searching image and the cut out airborne lidar point cloud data, abstracting a feature point from the reference image as a point to be matched, generating regularized digital surface model (DSM) information corresponding to an image overlapped region by means of the lidar point cloud data, converting point of sale (POS) data into elements of exterior orientation of the reference image, working out object space coordinates of corresponding ground points of the feature point to be matched by means of the DMS information and the elements of exterior orientation of the reference image, reversely calculating object space coordinates of the corresponding ground points to the searching image, obtaining the initial position of a corresponding matching point of the searching image, and matching by means of the correlation index to obtain a final matching result. The assisting image matching method provides good object space restraint for image matching by means of the lidar point cloud data, can effectively avoid complicated search strategies, achieves the purpose of the image matching and is high in matching success rate, short in consumed time and effective.

An integrated hydrotreating and steam pyrolysis process for the direct processing of a crude oil is provided to produce olefinic and aromatic petrochemicals. Crude oil and hydrogen are charged to a hydroprocessing zone operating under conditions effective to produce a hydroprocessed effluent reduced having a reduced content of contaminants, an increased paraffinicity, reduced Bureau of Mines Correlation Index, and an increased American Petroleum Institute gravity. Hydroprocessed effluent is thermally cracked in the presence of steam to produce a mixed product stream, which is separated. Hydrogen from the mixed product stream is purified and recycled to the hydroprocessing zone, and olefins and aromatics are recovered from the separated mixed product stream.

The invention discloses an atmospheric phase screen extraction method based on ground-based SAR (synthetic aperture radar) interference. Atmospheric phase is extracted according to a ground-based radar differential interferometric phase model on basis of a least squares fitting linear deformation and time-space filtering method. The ground-based radar differential interferometric phase model has a full consideration of the ground-based radar imaging mechanism and the differential interference theory so as to extract an atmospheric phase screen. A PS (permanent scatterer) point selection method of three levels, amplitude dispersion index, correlation index and phase stability, is provided, the atmospheric phase screen of radar data of each scene is finally obtained by means of Kriging interpolation, and accurate extraction of the phase generated under atmospheric interference has an important role on improving radar interferometric precision. Correctness of the method is verified by measured dam data, and the method is of certain actual application value and universality.

A process is provided that is directed to a steam pyrolysis zone integrated with a hydrotreating zone and a solvent deasphalting zone to permit direct processing of crude oil feedstocks to produce petrochemicals including olefins and aromatics. The integrated hydrotreating, solvent deasphalting and steam pyrolysis process comprises charging the crude oil to a hydroprocessing zone operating under conditions effective to produce a hydroprocessed effluent reduced having a reduced content of contaminants, an increased paraffinicity, reduced Bureau of Mines Correlation Index, and an increased American Petroleum Institute gravity; charging the hydroprocessed effluent to a solvent deasphalting zone with an effective amount of solvent to produce a deasphalted and demetalized oil stream and a bottom asphalt phase; thermally cracking the deasphalted and demetalized oil stream in the presence of steam to produce a mixed product stream; separating the mixed product stream; purifying hydrogen recovered from the mixed product stream and recycling it to the hydroprocessing zone; recovering olefins and aromatics from the separated mixed product stream; and recovering pyrolysis fuel oil from the separated mixed product stream.

The invention discloses an enterprise relocation risk assessment method based on a logical regression model, which comprises the following steps of S1 collecting the information field of the enterprise relocation instance and the desensitized telecommunication data provided by an operator, and selecting relevant variables of the enterprise relocation; S2 dividing the related variables into data boxes; 3 screening out low prediction ability indexes; S4 eliminating the high correlation index; S5 constructing the enterprise emigration prediction model by logical regression; 6 testing that prediction model; S7 evaluating the risk of the enterprise relocation through the enterprise relocation prediction model outputted from the step S6. The enterprise migration prediction model based on the logical regression fills in the blank of the enterprise migration quantitative analysis model, and has strong prediction ability.

The invention relates to a method for network navy account number identification based on particle swarm optimization. The method specifically comprises the following steps that step 1, user information of beta users is collected, lambda correlation indexes are extracted from each piece of user information, and therefore beta index vectors are obtained; step 2, weight allocation is conducted on the lambda indexes according to the requirements so that weight vectors can be obtained; step 3, the beta index vectors are ranked according to the size of each index in the index vectors so that lambda sequences can be obtained; step 4, each user is selected to serve as a particle, the particle swarm optimization is applied, and the particles satisfying the requirements are stored in a navy user list; step 5, all suspicious navy users in the navy user list are selected and all neighbors satisfying the requirements are added to the navy user list. At the real-time aspect, the method for network navy account number identification based on the particle swarm optimization is more suitable.

The invention discloses a method for detecting TWA (T wave alternans) in the electrocardiogram and belongs to the technical field of medical testing. The method comprises the following steps of: eliminating data sections with excessively high noise from selected electrocardiosignals by judging in the earlier stage so as to obtain relatively stable data suitable to analyze and carrying out analysis by taking M beats as an analysis window; firstly, extracting a T wave matrix for the M beats of electrocardiosignals and then carrying out data fitting on T waves in the T wave matrix to obtain a novel T wave matrix; respectively calculating alternans correlation indexes by a correlation analysis method to obtain an ACI (Allowable Concentration Index) of the integral analysis window); then judging whether the TWA exists in the integral analysis window by the correlation analysis method; if the TWA exists in the integral analysis window, respectively carrying out least square linear fitting on sectional odd and even beats of the existing TWA and calculating an actual TWA quantity; and if the TWA does not exist in the integral analysis window, intercepting a next analysis window to carry out analysis. According to the invention, the TWA signals can be effectively detected from the time domain angle and the TWA quantity is accurately quantized.

An integrated hydroprocessing and fluid catalytic cracking process is provided for the direct processing of a crude oil to produce olefinic and aromatic petrochemicals. Crude oil and hydrogen are charged to a hydroprocessing zone operating under conditions effective to produce a hydroprocessed effluent having a reduced content of contaminants, an increased paraffinicity, reduced Bureau of Mines Correlation Index, and an increased American Petroleum Institute gravity. The hydroprocessed effluent is separated into a low boiling fraction and a high boiling fraction. The low boiling fraction is cracked in a first downflow reactor of a fluid catalytic cracking unit in the presence of a predetermined amount of catalyst to produce cracked products and spent catalyst, and the high boiling fraction is cracked in a second downflow reactor of the fluid catalytic cracking unit in the presence of a predetermined amount of catalyst to produce cracked products and spent catalyst. Spent catalyst from both the first and second downflow reactors are regenerated in a common regeneration zone, and first and second cracked product streams are recovered.