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In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the 'outcome variable') and one or more independent variables (often called 'predictors', 'covariates', or 'features'). The most common form of regression analysis is linear regression, in which a researcher finds the line (or a more complex linear function) that most closely fits the data according to a specific mathematical criterion. For example, the method of ordinary least squares computes the unique line (or hyperplane) that minimizes the sum of squared distances between the true data and that line (or hyperplane). For specific mathematical reasons (see linear regression), this allows the researcher to estimate the conditional expectation (or population average value) of the dependent variable when the independent variables take on a given set of values. Less common forms of regression use slightly different procedures to estimate alternative location parameters (e.g., quantile regression or Necessary Condition Analysis) or estimate the conditional expectation across a broader collection of non-linear models (e.g., nonparametric regression).

InactiveUS7062510B1Less chargeHigh priceMarketingSpecial data processing applicationsRegression analysisHabit

Computer network method and apparatus provides targeting of appropriate audience based on psychographic or behavioral profiles of end users. The psychographic profile is formed by recording computer activity and viewing habits of the end user. Content of categories of interest and display format in each category are revealed by the psychographic profile, based on user viewing of agate information. Using the profile (with or without additional user demographics), advertisements are displayed to appropriately selected users. Based on regression analysis of recorded responses of a first set of users viewing the advertisements, the target user profile is refined. Viewing by and regression analysis of recorded responses of subsequent sets of users continually auto-targets and customizes ads for the optimal end user audience.

Owner:PRIME RES ALLIANCE E LLC

ActiveUS6869404B2Simplified and minimized in sizeElectrocardiographyAuscultation instrumentsRegression analysisT wave

A minimally invasive, implantable heart sound and ECG monitor and associated method for deriving blood pressure from heart sound data. The device is equipped with an acoustical sensor for detecting first and second heart sounds which are sampled and stored during sensing windows following R-wave and T-wave detections, respectively. ECG and heart sound data are stored in a continuous, looping memory, and segments of data are stored in long-term memory upon an automatic or manual data storage triggering event. Estimated blood pressure is calculated based on custom spectral analysis and processing of the first and second heart sounds. A calibration method includes measuring a patient's blood pressure using a standard clinical method and performing regression analysis on multiple spectral variables to identify a set of best fit weighted equations for predicting blood pressure. Concurrent ECG and estimated blood pressure may be displayed for review by a physician.

Owner:MEDTRONIC INC

InactiveUS20050119534A1Minimizes adverse reactionMaximize therapeutic responseDrug and medicationsSurgeryMedical recordCost effectiveness

Nonlinear generalized dynamic regression analysis system and method of the present invention preferably uses all available data at all time points and their measured time relationship to each other to predict responses of a single output variable or multiple output variables simultaneously. The present invention, in one aspect, is a system and method for predicting whether an intervention administered to a patient changes the physiological, pharmacological, pathophysiological, or pathopsychological state of the patient with respect to a specific medical condition. The present invention uses the theory of martingales to derive the probabilistic properties for statistical evaluations. The approach uniquely models information in the following domains: (1) analysis of clinical trials and medical records including efficacy, safety, and diagnostic patterns in humans and animals, (2) analysis and prediction of medical treatment cost-effectiveness, (3) the analysis of financial data, (4) the prediction of protein structure, (5) analysis of time dependent physiological, psychological, and pharmacological data, and any other field where ensembles of sampled stochastic processes or their generalizations are accessible. A quantitative medical condition evaluation or medical score provides a statistical determination of the existence or onset of a medical condition.

Owner:PFIZER PROD INC +1

InactiveUS20080013940A1Amount of timeMinimally deteriorating category classification performanceImage analysisProcessed material treatmentRegression analysisClassification methods

A photo category classification method including dividing a region of a photo based on content of the photo and extracting a visual feature from the segmented region of the photo, modeling at least one local semantic concept included in the photo according to the extracted visual feature, acquiring a posterior probability value from confidence values acquired from the modeling of the at least one local semantic concept by normalization using regression analysis, modeling a global semantic concept included in the photo by using the posterior probability value of the at least one local semantic concept; and removing classification noise from a confidence value acquired from the modeling the global semantic concept.

Owner:SAMSUNG ELECTRONICS CO LTD

InactiveUS20060064234A1Controlling traffic signalsAnalogue computers for vehiclesRegression analysisPrediction system

In a congestion prediction using measurement data which is acquired by an on-road sensor or a probe car, and which includes none of explicit information about bottleneck points, with respect to time-sequence data on congestion ranges accumulated in the past, data on congestion front-end positions are summarized into plural clusters by the clustering. Representative value in each cluster is assumed as position of each bottleneck. A regression analysis, in which day factors are defined as independent variables, is performed with congestion length from each bottleneck point selected as the target. Here, the day factors refer to factors such as day of the week, national holiday/etc. It then becomes possible to precisely predict a future congestion length.

Owner:HITACHI LTD

Illustrative embodiments of the present invention are directed to a method and system for disaggregating climate control energy use from non-climate control energy use for a building. The method includes receiving a series of building energy use values and corresponding outdoor temperature values for a time period. Each of the energy use values and outdoor temperature values is associated with a time interval. The method further includes determining a series of temperature difference values for the time period based on a difference in temperature between a predetermined baseline temperature and each of the outdoor temperature values. A regression analysis is used to determine a climate control coefficient and a non-climate control coefficient from the energy use values and temperature difference values. The climate control coefficient and/or the non-climate control coefficient is used to determine climate control energy use and/or non-climate control energy use for the building.

Owner:OPOWER

PendingCN110086649AImprove accuracyEliminate false alarmsData switching networksTraffic predictionTime segment

The invention discloses an abnormal flow detection method and device, computer equipment and a storage medium. The method comprises the following steps of: screening the historical flow data of the monitoring object; obtaining target traffic data, carrying out regression analysis on the target traffic data; establishing a flow prediction model, predicting the flow data of the monitored object by using the flow prediction model; obtaining a prediction result of the flow data of the monitoring object in a preset time period, carrying out statistical analysis is on a prediction result according to a preset statistical mode; obtaining a traffic alarm threshold value of the monitored object, further obtaining a real-time access log of the monitored object when the real-time traffic data of themonitored object is greater than the traffic alarm threshold value, and performing abnormal traffic alarm if the response time of the real-time access log is greater than the response time threshold value. According to the embodiment of the invention, the accuracy of the alarm threshold can be improved, judgment is carried out by combining the response time of the service, and thus the accuracy ofabnormal flow detection is improved.

Owner:ONE CONNECT SMART TECH CO LTD SHENZHEN

InactiveUS7280988B2Easy to appreciateNuclear monitoringDigital computer detailsRegression analysisMonitoring system

A monitoring system including a baseline model that automatically captures and models normal system behavior, a correlation model that employs multivariate autoregression analysis to detect abnormal system behavior, and an alarm service that weights and scores a variety of alerts to determine an alarm status and implement appropriate response actions. The baseline model decomposes the input variables into a number of components representing relatively predictable behaviors so that the erratic component e(t) may be isolated for further processing. These components include a global trend component, a cyclical component, and a seasonal component. Modeling and continually updating these components separately permits a more accurate identification of the erratic component of the input variable, which typically reflects abnormal patterns when they occur.

Owner:NETUITIVE

ActiveUS20140109123A1Analogue secracy/subscription systemsBroadcast information monitoringRegression analysisData mining

A system that incorporates teachings of the subject disclosure may include, for example, determining identified impressions that are detected from consumption data collected from a group of media processors where the identified impressions represent viewing of selected content and where the consumption data indicates channel tuning events at the group of media processors including changing of channels, applying a ridge regression analysis to the identified impressions to determine a predicted number of target impressions per advertisement slot, and generating a media plan based on a ratio of an advertisement slot cost to the predicted number of target impressions per advertisement slot. Other embodiments are disclosed.

Owner:AT&T INTPROP I L P

A method and apparatus for measuring a blood analyte concentration using an inexpensive, low precision sensor device is provided. One embodiment of the method includes obtaining energy absorption measurement data through a body part of an individual. A plurality of indicator variables are subsequently calculated from the energy absorption measurement data. An indicator variable from the plurality of indicator variables having the highest correlation to blood glucose level is determined, and a first optical term based on the indicator variable with the highest correlation to blood glucose level is allocated to form a regression analysis equation. An estimated value of the blood analyte concentration using the regression analysis equation is calculated.

Owner:FUTREX

InactiveUS20130262049A1Generation forecast in ac networkData processing applicationsRegression analysisPredictive methods

An output of a photovoltaic (PV) device is predicted by applying Fourier analysis to historical data to obtain frequencies and a mean of the frequencies in the data. Regression analysis is applied to the data to obtain a regression coefficient. Then, the prediction is a sum of the mean at the time step and a deviation from the mean at a previous time step, wherein the means are represented and approximated by selected frequencies, and the deviation for the previous time step is weighted by the regression coefficient.

Owner:MITSUBISHI ELECTRIC RES LAB INC

InactiveCN101826105AImprove scalabilityThe detection process is fastSpecial data processing applicationsPattern recognitionRegression analysis

A phishing webpage detection method based on Hungary matching algorithm is characterized by firstly extracting the text feature signatures, image feature signatures and general webpage feature signatures of the rendered webpages and more comprehensively depicting the features after access to webpages; and then computing the optimal matching of bipartite graphs by Hungary algorithm to search for the matched feature pairs among different webpage signatures and more objectively measuring the similarity among the webpages on the basis, thereby improving the phishing webpage detection efficiency. The method is also characterized by determining the inside weights of the text features, image features and global image features by utilizing the area under curve and determining the relative weightsamong the text similarity, image similarity and global image similarity during webpage similarity computation by utilizing logarithmic regression analysis. The precision and the recall rate are greatly improved in the method provided by the invention.

Owner:NANJING UNIV OF POSTS & TELECOMM

ActiveUS20060292619A1Microbiological testing/measurementAcquiring/recognising microscopic objectsGrowth phaseRegression analysis

Machine executable method of analyzing growth curve data to identify the transition from a baseline phase into a growth phase. Applications of the method include analysis of results from time-dependent monitoring of amplicon synthesis in a nucleic acid amplification reaction to quantify a starting amount of a nucleic acid template in a test sample. The method advantageously simplifies the quantitation by circumventing the need to establish thresholds used for calculating initiation of the growth phase, to calculate derivatives, or to perform linear regression analysis.

Owner:GEN PROBE INC

Methods and systems for establishing a contemporaneous Real Estate property valuations are disclosed. In accordance with one aspect of the invention, this is based upon first identifying a set of relevant value indicators, or Fields, and then producing a comprehensive Multiple Regression Analysis which statistically measures the relative value of Real Estate properties included in the Set.

Owner:CONTEMPORANEOUS PRICING TECH

ActiveCN103412526AMastering Thermoelectric PropertiesAvoid the problem of needing to increase the generation loadTotal factory controlProgramme total factory controlRegression analysisPower grid

The invention provides a scheduling method of a heat supply unit online load and a system. The scheduling method and the system are suitable for implementation of reasonable scheduling of a heat supply unit in a heating period. According to the method of the invention, based on the combination of real-time monitored data of parameters of the heat supply unit in a power grid, each heat supply index of a computer group, steam turbine variable working condition method and the actual operation status of the unit, an ordering power by heat mathematic model can be obtained, and therefore, power grid scheduling personnel can perform scheduling through adopting a minimum load mode, a load fast decreasing/increasing mode, and an energy-saving mode, and a basis can be provided for decision making in heat supply unit scheduling; according to weather forecast released by the meteorological department, and based on the combination of regression analysis results of historical data of the heat supply unit, weather, temperature and wind can be applied to heat supply quantity prediction; and according to predicted heat supply quantity, and based on the ordering power by heat mathematic model, electric power and electric quantity of a next day or a next month of the unit can be predicted.

Owner:STATE GRID CORP OF CHINA +2

InactiveCN101666662AMeasurement devicesComplex mathematical operationsRegression analysisBrownian excursion

The invention discloses an accelerated degradation test prediction method based on fuzzy theory, which comprises the following steps: collecting test data; performing the analysis of regression aimingat performance degradation data under each stress level; extrapolating the performance degradation rate of the product under a normal stress level; estimating a diffusion coefficient sigma in an excursion Brownian motion with drift by adopting a maximum likelihood estimation method; establishing an accelerated degradation test life and reliability predication model based on the fussy theory; andpredicting the life and the reliability of the product by adopting the fussy life and reliability prediction model. The method firstly introduces the fussy concept into an accelerated degradation testto enable the prediction result of the accelerated degradation test to be more reasonable, avoids the condition of rash routine reliability estimation result through considering the fussiness fuzziness of the performance degradation threshold, solves the problem of failed performance degradation in the engineering reality, and is suitable for the accelerated degradation tests of step stress and progressive stress and unaccelerated performance degradation prediction for the problem of the performance degradation failure.

Owner:BEIHANG UNIV

Information presented to a user via an information access system is ranked according to a prediction of the likely degree of relevance to the user's interests. A profile of interests is stored for each user having access to the system. Items of information to be presented to a user are ranked according to their likely degree of relevance to that user and displayed in order of ranking. The prediction of relevance is carried out by combining data pertaining to the content of each item of information with other data regarding correlations of interests between users. A value indicative of the content of a document can be added to another value which defines user correlation, to produce a ranking score for a document. Alternatively, multiple regression analysis or evolutionary programming can be carried out with respect to various factors pertaining to document content and user correlation, to generate a prediction of relevance. The user correlation data is obtained from feedback information provided by users when they retrieve items of information. Preferably, the user provides an indication of interest in each document which he or she retrieves from the system.

Owner:APPLE INC

A method of determining a volume of fluid associated with a fluid storage and dispensing system, the volume of fluid having a height in the system, wherein the system include measurement apparatus for measuring the height. The method includes collecting a plurality of height measurement data from the measurement apparatus in a form readable by a computer; storing the plurality of height measurement data in a compressed matrix format in a computer memory; and performing regression analysis using the compressed matrix format to calculate the volume of fluid associated with the system.

Owner:WARREN ROGERS ASSOC

ActiveUS20130098148A1Improve uniformityDifferent from numberTyresRoads maintainenceTire uniformityRegression analysis

A system and related method for improving tire uniformity includes identifying at least one candidate process effect and a corresponding process harmonic number for each process effect. A given uniformity parameter, such as radial or lateral run-out, balance, mass variation, radial lateral or tangential force variation, is measured for each tire in a test set, such that the measurements contain tire harmonics as well as a process harmonics corresponding to each candidate process effect. Rectangular coordinate coefficients are electronically constructed for each said process harmonic, after which point the rectangular coordinates corresponding to each process harmonic are solved for (e.g., by using regression-based analysis). The magnitude of each said process harmonic is estimated, and a final magnitude estimate for each process harmonic can be determined by summarizing (e.g., by taking the average or median value) the respectively estimated magnitudes for each process harmonic across all test tires.

Owner:MICHELIN & CO CIE GEN DES ESTAB MICHELIN +1

ActiveUS20160294186A1Accurately establishedFine granularityProgramme controlComputer controlBaseline dataData set

A method for dispatching buildings in a demand response program event including retrieving a plurality of baseline energy use data sets for the buildings from a baseline data stores; generating data sets for each of the buildings, each set having energy consumption values along with corresponding time and outside temperature values, where the energy consumption values within each set are shifted by one of a plurality of lag values relative to the corresponding time and outside temperature values, and where each of the plurality of lag values is different from other ones of the plurality of lag values; performing a regression analysis on each set to yield regression model parameters and a residual; determining a least valued residual from all residuals yielded, the least valued residual indicating a corresponding energy lag for the each of the buildings; and using energy lags for all of the buildings to generate a dispatch schedule for the demand response program event according to a prioritization of the energy lags.

Owner:ENEL X NORTH AMERICA INC

A system for automating certain processes of regression testing. One or more regression test cases are executed on a current build of a test application. Current application performance data are collected as a result of execution of the one or more test cases.

The current performance data are compared with baseline performance data obtained by executing the test cases on an earlier built of the test application. If it is determined that a current performance datum is worse than the corresponding baseline performance datum by exceeding a prescribed threshold, then the regression test cases are executed on the current application build under control of a profiler to collect application data for analyzing the source of the performance regression.

Owner:IBM CORP

The present invention is objective, quantitative and precise method of predicting serious complication risk degree after gastric cancer operation. The method includes the following steps: 1. screening out factors affecting the serious complication after gastric cancer operation through overall single factor analysis; 2. determining the prognostic determining factor through two-value multiple non-conditional logic regression analysis; 3. determining the optimal prediction value dividing value through the work characteristic analysis on the testee; and 4. establishing the predicting model with main risk factor as the independent variable and judging the serious complication risk degree after gastric cancer operation by means of the prediction probability. The present invention is one objective and quantitative intelligent risk evaluation system.

Owner:NANJING UNIV

Methods for predicting states of a subject are presented. For example, a method for predicting states of a subject includes obtaining training data comprising a plurality of variables, obtaining training states associated with the training data, and forming a predictive model according to the training data and the training states, the predictive model predictive of the training states. The forming of the predictive model includes extracting one or more hidden components from the training data. The extracting of the one or more hidden components includes regression analysis including determining one or more relationships between the one or more hidden components and the plurality of variables, and determining one or more relationships between the one or more hidden components and the training states. A number of the one or more hidden components is less than a number of the plurality of variables and greater than a number of the training states.

Owner:IBM CORP

InactiveUS20060085164A1Increase valueGreat forecast valueAnalogue computers for vehiclesAnalogue computers for trafficVisibilityDecision system

A system and method for making a decision of whether to carry additional fuel on an aircraft for a particular flight based on a forecast, such as for low visibility and ceiling. Preferably, observations-based probabilistic forecasts are utilized. The forecast probability of the weather at the planned aerodrome being below a prescribed minimum level is calculated using statistical regression analysis of past data. An optimal probability is estimated using cost parameters on an individual flight bases. If this forecast probability is greater than the optimal probability for a particular flight, then extra fuel is carried by that flight. This is in contrast to current practice whereby the same categorical forecast is applied to all flights. The combination of improved short-term forecasts and identification of optimal forecast probabilities minimizes the financial impact of errors and weather forecasts on airline operations thereby providing a superior financial outcome.

Owner:RGT UNIV OF OKLAHOMA THE BOARD THE

The invention discloses a network advertisement effect estimating method, which comprises the following steps of: classifying original data according to an impact factor of an advertisement effect; extracting an impact sub-factor of the advertisement effect from the impact factor of the advertisement effect, and establishing at least one estimating model by adopting regression analysis and a re-sampling algorithm (Bagging); selecting an optimal estimating model from the estimating models by a tenfold crossed validation method; and estimating the advertisement effect within a next prediction period by utilizing the optimal estimating model so as to obtain an advertisement estimated effect. By the application of an embodiment of the invention, the high-precision prediction of an advertisement delivery effect can be performed, and the estimated effect is diversified.

Owner:SHENZHEN TENCENT COMP SYST CO LTD

This invention presents an innovative framework for the application of machine learning for identification of alloys or composites with desired properties of interest. For each output property of interest, we identify the corresponding driving (input) factors. These input factors may include the material composition, heat treatment, process, microstructure, temperature, strain rate, environment or testing mode. Our framework assumes selection of optimization technique suitable for the application at hand and data available, starting with simple linear, or quadratic, regression analysis. We present a physics-based model for predicting the ultimate tensile strength, a model that accounts for physical dependencies, and factors in the underlying physics as a priori information. In case an artificial neural network is deemed suitable, we suggest employing custom kernel functions consistent with the underlying physics, for the purpose of attaining tighter coupling, better prediction, and extracting the most out of the—usually limited—input data available.

Owner:IMAGARS

ActiveUS20150235379A1Reduce error rateTelevision system detailsImage enhancementFrame basedRegression analysis

A system and method processes visual information including at least one object in motion. The visual information is processed by locating at least one spatial edge of the object, generating a plurality of spatio-temporal gradients for the at least one spatial edge over N frames, and then generating motion blur images from the spatio-temporal gradients. A regression analysis is performed on the motion blur images to determine direction of motion information of the object, and scene activity vectors are then generated for the N frames based on the direction of motion information. An event is detected in the visual information based on the scene activity vectors.

Owner:ALCATEL LUCENT SAS

The invention discloses an intelligent early-warning method for meteorological severe convection weather based on machine learning. The method comprises the steps of receiving severe convection weather early-warning basic data through a server, wherein the basic data comprise lightning positioning data, weather electric field data, automatic station meteorological essential factor real-time data, radar real-time radix data and the like, and supplying a local severe convection weather early-warning threshold for each area according to historical meteorological data based on a regression analysis method; obtaining real-time meteorological comprehensive data through big data regression analysis calculation of various meteorological essential factors, comparing the real-time meteorological comprehensive data with an early-warning threshold, and generating early-warning information. According to the intelligent early-warning method, tracing and data back-pushing are performed on meteorological historical data by means of the regression analysis method of machine learning; dynamic calculation and intelligent adjustment are performed according to a context threshold; data comparison is performed on a radar back-pushing result and automatic station meteorological essential factor real-time data; identification and early-warning are performed on the severe convection weather based on machine learning; and accurate early-warning for the severe convection weather in a preset area is realized.

Owner:GUANGDONG OKING INFORMATION IND CO LTD

A frame error concealment method is provided that includes predicting a parameter by performing a regression analysis on a group basis for a plurality of groups formed from a first plurality of bands forming an error frame and concealing an error in the error frame by using the parameter predicted on a group basis.

Owner:SAMSUNG ELECTRONICS CO LTD

InactiveUS20110191076A1Early and accurate discoveryData processing applicationsElectric testing/monitoringRegression analysisCluster group

Provided are a method which permits complete training data and data with added errors, and enables the early and accurate discovery of errors in facilities such as a plant, and a system thereof. To achieve the objectives, (1) the behavior of temporal data is observed over time, and the trace is divided into clusters; (2) the divided cluster groups are modeled in sub spaces, and the discrepancy values are calculated as errors candidates; (3) the training data are used (compare, reference, etc.) for reference to determine the state transitions caused by the changes over time, the environmental changes, the maintenance (parts replacement), and the operation states; and (4) the modeling is a sub space method such as regression analysis or projection distance method of every N data removing N data items, (N=0, 1, 2, . . . ) (for example, when N=1, one error data item is considered to have been added, this data is removed, then the modeling is performed), or a local sub space method. Linear fitting in regression analysis is equivalent to the lowest order regression analysis.

Owner:HITACHI LTD

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