A system and method for determining an optimal solution to an optimization problem in a swarm of candidate solutions is provided. The invention comprises generating a population of random particles, where each particle is representative of a candidate solution. Further, a best particle is identified from the generated population of particles. The best particle is representative of an optimal solution. The population of particles is categorised into similar and non-similar particle groups by applying one or more multivariate measurement techniques, and similarity between the particles of the non-similar particle group with best particle is updated by applying an imitation technique. The generated population is updated with updated particles and a new best particle is evaluated from said population. Furthermore, final best particle is determined by further updating the population of particles until one or more target conditions are achieved.

Multi-dimensional aggregation using user interface workflow composition is described. A determination is made whether aggregation is complete for each level of a multi-dimension aggregation. Data is retrieved for a level of aggregation in response to a determination that aggregation is not complete for each level of the multi-dimension aggregation. The data is aggregating based on the level of aggregation. The aggregated data is stored for a next level of aggregation. The data for a final level of aggregation is output to a user interface in response to a determination that aggregation is complete for each level of the multi-dimension aggregation.

Multi-dimensional aggregation using user interface workflow composition is described. A determination is made whether aggregation is complete for each level of a multi-dimension aggregation. Data is retrieved for a level of aggregation in response to a determination that aggregation is not complete for each level of the multi-dimension aggregation. The data is aggregating based on the level of aggregation. The aggregated data is stored for a next level of aggregation. The data for a final level of aggregation is output to a user interface in response to a determination that aggregation is complete for each level of the multi-dimension aggregation.

A system and method to augment model-to-model coupling include obtaining an output signal fs from an upstream model. The method also includes obtaining an observation signal g.sub.ob from a region of interest, extracting a high-frequency signal g from the observation signal g.sub.ob using a linear operator, and providing to a downstream model the high-frequency signal g in addition to information based on the output signal fs from the upstream model. The downstream model is implemented to obtain a prediction or estimation of one or more parameters of interest or drive a mechanical process.

A methodology for discontinuous smooth interpolation in order to generate a curve of a discontinuous volume due to one or more faults in a subsurface is disclosed. Faults in a subsurface result in discontinuities in the subsurface. Hydrocarbon management may seek to determine various surfaces in the subsurface, including across the faults in the subsurface. To generate the various surfaces, a continuous formulation of the interpolation method is followed in which discontinuous smooth interpolation is viewed as a variational optimization problem (such as an energy optimization problem) for the surface curvature function. In this way, the methodology does not require that the input data be located at grid points and discretized with a structured regular grid. Rather, because a continuous function is used, an unstructured grid may also be used to discretize the resulting equation.

A spurious outlier detection-system is provided. The system includes a memory having computer-readable instructions stored therein and a processor configured to execute the computer-readable instructions to receive time-series data from one or more sensors and/or applications, process the time-series data to detect one or more change points based on a pre-defined cost function. The processor is configured to identify data chunks between the change points using pre-determined window sizes and to estimate smooth reconstructed values (SRVs) for each of the change point data chunks between two consecutive change points to identify one or more global outliers from the SRVs. The processor is configured to determine distribution of the global outliers using kernel density for each change point data chunk and identify one or more true outliers from the distribution of the global outliers based upon a skewness of the distribution.

A digital medium environment is described to dynamically modify or extend an existing path in a user interface. An un-parameterized input is received that is originated by user interaction with a user interface to specify a path to be drawn. A parameterized path is fit as a mathematical ordering representation of the path to be drawn as specified by the un-parametrized input. A determination is made as to whether the parameterized path is to extend or modify the existing path in the user interface. The existing path is modified or extended in the user interface using the parameterized path in response to the determining that the parameterized path is to modify or extend the existing path.

Disclosed is a method for generating an utterance of a chatbot based on a semantic graph database and executed by a computer, includes generating the semantic graph database by using a past utterance of a user, and generating the utterance of the chatbot for responding to a new utterance of the user, by using the semantic graph database.

A document data processing apparatus includes a memory and a processor. The memory stores a distributed-representation set including multiple distributed representations corresponding to multiple pieces of data. The processor is configured to modify the distributed-representation set on the basis of multiple data pairs and multiple scores corresponding to the data pairs. The data pairs are subjected to learning. The processor is configured to modify the distributed-representation set in such a manner that, for each of the data pairs, a value indicating a relationship in a modified distributed-representation pair corresponding to the data pair comes close to a score corresponding to the data pair.

To improve efficiency for solving a system of equations, art equation solver uses variable reduction techniques to reduce a number of variables to be solved. The equation solver identifies derived variables and eliminates them from the system of equations. The equation solver considers the remaining variables to be primitive variables. The primitive variables may be rewritten into a representation of the system of equations or into a set of equations that may be used to solve for values of the primitive variables. The equation solver solves for values of the primitive variables. Prior to solving or during solving iterations, the equation solver may apply storage policies to further reduce the number of variables to be solved. The storage policies indicate parameters and techniques for eliminating primitive variables to be solved, such as primitive variables that are insignificant (i.e., have little effect on a solution for the system of equations).