# Karel Marik, Revnice CZ

## Karel Marik, Revnice CZ

Patent application number | Description | Published |
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20080217005 | AUTOMATED OIL WELL TEST CLASSIFICATION - The subject mater herein relates to oil well testing and, more particularly, automated oil well test classification. Various embodiments described herein provide systems, methods, and software for statistical analysis and classification of oil well tests. Some embodiments include receiving a first set of oil well test results from one or more measurement devices of a well test separator, storing the first set of oil well test results in a database, and annotating one or more tests of the first set oil well test results. The annotated test results are then used to build one or more classification models to enable automated oil well test classification as new oil well tests are performed. | 09-11-2008 |

20080255760 | Forecasting system - A process includes providing a plurality of forecasts from a plurality of forecasting models. The plurality of forecasts each includes a mean and a variance. A model weight is calculated for each forecasting model. The model weight is proportional to the ability of that model to successfully forecast a queried situation. The plurality of forecasts are combined using an aggregate mean and an aggregate variance of the plurality of forecasts. | 10-16-2008 |

20090125825 | APPARATUS AND METHOD FOR DISPLAYING ENERGY-RELATED INFORMATION - A method includes receiving energy-related information associated with multiple elements in a hierarchically-arranged domain. The method also includes determining a value of an energy-related metric for each of the elements using the energy-related information. The method further includes generating a graphical user interface using the metric values and presenting the graphical user interface to a user. The graphical user interface includes a treemap having multiple sections, each associated with one of the elements. The graphical user interface also includes a graph displaying energy-related information associated with a selected element. A size of each section in the treemap could be based on a size, importance, energy usage, and/or carbon emission of the associated element. A color and a color intensity of each section in the treemap could be based on the metric value of the associated element and/or a comparison of the absolute energy usage to a baseline. | 05-14-2009 |

20090216469 | SYSTEM FOR MULTIDIMENSIONAL DATA-DRIVEN UTILITY BASELINING - A system for utility base lining records historic values of utility loads for regions within a facility. The system also records historic values of independent variables such as outside temperature, time, date, workday versus non-workday, and occupancy. A similar data selector seeks out similar times in the past and submits the data from those times to a base line estimator which produces a baseline estimate. Differences between the current load and the estimated load can trigger alarms or investigations to determine why the utility load has changed. False alarms can occur when the utility load drifts over time. Detecting drift can help reduce false alarms or help in the investigation of alarms. A graphical user interface (GUI) can present an easily understood representation of the regions, load estimation errors, alarms, and detected drift. | 08-27-2009 |

20140027103 | OPERATION OF A THERMAL COMFORT SYSTEM - Systems, methods, and devices for operation of a thermal comfort system are described herein. For example, one or more embodiments include receiving data, including a target temperature for a zone, an actual temperature of the zone, and an ambient temperature of air being supplied to a thermal comfort system, and determining, through a regression model, from the received data, a calculated time when the zone will reach the target temperature upon operation of the thermal comfort system. | 01-30-2014 |

20140067088 | TUNING MODEL STRUCTURES OF DYNAMIC SYSTEMS - Tuning model structures of dynamic systems are described herein. One method for tuning model structures of a dynamic system includes predicting a variable for each of a number of models associated with a number of model structures of a dynamic system, calculating a rate of error of the predicted variable for each of the number of models compared to an observed variable, determining a best model structure among the number of model structures based on the calculated rate of error, and creating a revised model structure using the best model structure to tune the number of model structures of the dynamic system. | 03-06-2014 |

20140067132 | HVAC CONTROLLER WITH REGRESSION MODEL TO HELP REDUCE ENERGY CONSUMPTION - A thermal control system for a building is disclosed, which includes a regression model: Given a forecast temperature outside the building, the regression model predicts how much an HVAC system will cost to run during a day, for a given set of time-varying target temperatures for all the thermostats in the thermal control system. The thermal control system may also include an optimizer, which invokes multiple applications of the regression model. Given a forecast temperature outside the building, the optimizer predicts an optimal set of time-varying target temperatures for all the thermostats in the thermal control system. Running the HVAC system with the optimal set of time-varying target temperatures should have a reduced or a minimized cost, or a reduced or minimized total energy usage. The optimizer works by running the regression model repeatedly, while adjusting the time-varying target temperature for each thermostat between runs of the model. | 03-06-2014 |

20140128997 | IDENTIFYING MODELS OF DYNAMIC SYSTEMS - Identifying models of dynamic systems is described herein. One method for identifying a model of a dynamic system includes estimating a number of parameters for each of a number of models of the dynamic system, predicting an output using the estimated number of parameters for each of the number of models, calculating a rate of error of the predicted output for each of the number of models compared to an observed output, and identifying a best model among the number of models of the dynamic system based on the calculated rate of errors. | 05-08-2014 |

20140277760 | SUPERVISORY CONTROLLER FOR HVAC SYSTEMS - A supervisory controller for heating, ventilation, and air conditioning (HVAC) systems is described herein. One device includes a data management module configured to receive a zone demand signal from a local controller of a zone of an HVAC system and receive a number of additional signals from a number of sensors, and a parameter identification module configured to determine, based on the zone demand signal, whether the zone is in a comfort state by loading a best model structure from a number of models and identifying parameters of the best model structure based on data received from the data management module. | 09-18-2014 |

20140336787 | INDEX GENERATION AND EMBEDDED FUSION FOR CONTROLLER PERFORMANCE MONITORING - A system calculates a first ratio of a prediction error variance of a model of a controller error, and the lesser of a variance of a prediction error of a naïve predictor model and a variance of a controller error. The system rates a process controller as a function of the first ratio. The system also calculates a second ratio of a variance of the controller error and a variance of the prediction error of the naïve predictor model. The system rates the process controller a function of the second ratio. The system uses the first ratio, second ratio, other ratios, and discrete indicators in determining an embedded fusion for loop performance monitoring in the process controller and for displaying a value as a measure of the loop performance. | 11-13-2014 |