Patent application number | Description | Published |
20100096474 | Gas Turbine Ejector and Method of Operation - An ejector system and method of operation for combining high and low pressure fluid flow streams is disclosed. A nozzle chamber communicates with a high pressure fluid flow stream and a suction chamber communicates with a low pressure fluid flow stream. The outlet of the nozzle chamber exit into the suction chamber and include multiple nozzles such that the high pressure flow stream exits the nozzle chamber in multiple flow streams having multiple surface areas for interlayer drag between the flows. The low pressure fluid flow stream is entrained by the high pressure fluid flow streams exiting the multiple nozzles to define an intermediate pressure flow stream. | 04-22-2010 |
20100170265 | Variable Geometry Ejector - An ejector for a turbine engine is described herein. The ejector may include a variable geometry motive nozzle and a variable geometry mixing tube positioned downstream of the variable geometry motive nozzle. | 07-08-2010 |
20140102105 | SYSTEM AND METHOD FOR HEATING COMBUSTOR FUEL - A system for heating combustor fuel includes a turbine exhaust plenum and a heat exchanger downstream from the turbine exhaust plenum. The heat exchanger has an exhaust inlet, an exhaust outlet, a fuel inlet, and a fuel outlet. An exhaust recirculation plenum has a recirculation inlet connection downstream from the exhaust outlet and a recirculation outlet connection upstream from the exhaust inlet. The system further includes structure for controlling a recirculated exhaust flow from the exhaust outlet into the exhaust recirculation plenum. | 04-17-2014 |
20140208766 | Waste Heat Recovery Fuel Gas Heater Control Method and Algorithm - A method of operating a fuel heating system is provided. The method includes performing pre-ignition diagnostic checks on a plurality of components of the fuel heating system, wherein at least one inlet damper and at least one outlet damper of an exhaust flow circuit are each in a closed position. The method also includes purging the fuel heating system of unburned hydrocarbons. The method further includes operating the fuel heating system in a normal operating condition. The method yet further includes operating the fuel heating system in a cool down condition, wherein the at least one inlet damper is in the closed position. | 07-31-2014 |
Patent application number | Description | Published |
20120084251 | PROBABILISTIC DATA MINING MODEL COMPARISON - A first data mining model and a second data mining model are compared. A first data mining model M | 04-05-2012 |
20120158624 | PREDICTIVE MODELING - A predictive analysis generates a predictive model (Padj(Y|X)) based on two separate pieces of information,
| 06-21-2012 |
20140180973 | Iterative Active Feature Extraction - Techniques for iterative feature extraction using domain knowledge are provided. In one aspect, a method for feature extraction is provided. The method includes the following steps. At least one query to predict at least one future value of a given value series based on a statistical model is received. At least two predictions of the future value are produced fulfilling at least the properties of 1) each being as probable as possible given the statistical model and 2) being mutually divert (in terms of numerical distance measure). A user is queried to select one of the predictions. The user may be queried for textual annotations for the predictions. The annotations may be used to identify additional covariates to create an extended set of covariates. The extended set of covariates may be used to improve the accuracy of the statistical model. | 06-26-2014 |
20140180992 | Iterative Active Feature Extraction - Techniques for iterative feature extraction using domain knowledge are provided. In one aspect, a method for feature extraction is provided. The method includes the following steps. At least one query to predict at least one future value of a given value series based on a statistical model is received. At least two predictions of the future value are produced fulfilling at least the properties of 1) each being as probable as possible given the statistical model and 2) being mutually divert (in terms of numerical distance measure). A user is queried to select one of the predictions. The user may be queried for textual annotations for the predictions. The annotations may be used to identify additional covariates to create an extended set of covariates. The extended set of covariates may be used to improve the accuracy of the statistical model. | 06-26-2014 |
20150134306 | CREATING UNDERSTANDABLE MODELS FOR NUMEROUS MODELING TASKS - A computer program product for creating models comprises a computer readable storage medium having stored thereon first program instructions executable by a processor to cause the processor to receive the modeling tasks each having a target variable and at least one covariate, the target variable and the at least one covariate being the same for all of the modeling tasks, a relationship between the target variable and the at least one covariate being different for all of the modeling tasks, and second program instructions executable by the processor to cause the processor to generate, for each of the modeling tasks, a model including a transfer function for approximating the relationship between the target value and the at least one covariate of the modeling task in a manner that at least two of the models share an identical transfer function and the models satisfy an accuracy condition. | 05-14-2015 |
20150134307 | CREATING UNDERSTANDABLE MODELS FOR NUMEROUS MODELING TASKS - A method for generating models for a plurality of modeling tasks is disclosed. The method comprises receiving, with a processing device, the modeling tasks each having a target variable and at least one covariate. The target variable and at least one covariate are the same for all of the modeling tasks. A relationship between the target variable and at least one covariate is different for all of the modeling tasks. For each of the modeling tasks, generating a model including a transfer function for approximating the relationship between the target value and at least one covariate of the modeling task in a manner that at least two of the models share at least one identical transfer function and the models satisfy an accuracy condition. | 05-14-2015 |
Patent application number | Description | Published |
20140132627 | Automatic Tuning of Value-Series Analysis Tasks Based on Visual Feedback - A method for selecting an analysis procedure for a value series, including displaying a value series on a computer display monitor, receiving one or more sequences of user provided annotations, where the annotations overlay at least a sub-interval of the value series on the computer display monitor, using the sequences of user provided annotations to select an optimal value series analysis method from a set of value series analysis methods, where selecting an optimal value series analysis method includes determining parameter values for the optimal value series analysis method, and presenting the selected optimal value series analysis method and parameters, and the optimal reconstruction of the annotation sequences to the user. | 05-15-2014 |
20140136563 | Accelerating Time Series Data Base Queries Using Dictionary Based Representations - A method for accelerating time series data base queries includes segmenting an original time series of signal values into non-overlapping chunks, where a time-scale for each of the chunks is much less than the time scale of the entire time series, representing time series signal values in each chunk as a weighted superposition of atoms that are members of a shape dictionary to create a compressed time series, storing the original time series and the compressed time series into a database, determining whether a query is answerable using the compressed time series or the original time series, and whether answering the query using the compressed time series is faster. If answering the query is faster using the compressed representation, the query is executed on weight coefficients of the compressed time series to produce a query result, and the query result is translated back into an uncompressed representation. | 05-15-2014 |
20140146078 | Automatic Tuning of Value-Series Analysis Tasks Based on Visual Feedback - A method for selecting an analysis procedure for a value series, including displaying a value series on a computer display monitor, receiving one or more sequences of user provided annotations, where the annotations overlay at least a sub-interval of the value series on the computer display monitor, using the sequences of user provided annotations to select an optimal value series analysis method from a set of value series analysis methods, where selecting an optimal value series analysis method includes determining parameter values for the optimal value series analysis method, and presenting the selected optimal value series analysis method and parameters, and the optimal reconstruction of the annotation sequences to the user. | 05-29-2014 |
20140149444 | Accelerating Time Series Data Base Queries Using Dictionary Based Representations - A method for accelerating time series data base queries includes segmenting an original time series of signal values into non-overlapping chunks, where a time-scale for each of the chunks is much less than the time scale of the entire time series, representing time series signal values in each chunk as a weighted superposition of atoms that are members of a shape dictionary to create a compressed time series, storing the original time series and the compressed time series into a database, determining whether a query is answerable using the compressed time series or the original time series, and whether answering the query using the compressed time series is faster. If answering the query is faster using the compressed representation, the query is executed on weight coefficients of the compressed time series to produce a query result, and the query result is translated back into an uncompressed representation. | 05-29-2014 |