15 results about "Model builder" patented technology

The present invention discloses a spatial hierarchical model. The spatial hierarchical model is constructed by receiving user input to add and name each of one or more first-level spaces in a first level of the spatial hierarchical model and select a selected one of the first-level spaces in the first level of the spatial hierarchical model of the spatial hierarchical model, and adding and naming each of one or more sub-level spaces that are spatial parts of the selected first-level space in a second level of the spatial hierarchical model. A graphical representation of one or more of the first-level spaces and one or more corresponding sub-level spaces is displayed together with a list of at least some of the plurality of building control assets. User input is received to assign a selected building control asset from the list of at least some of the plurality of building control assets to the selected sub-level space.

A system is provided.SOLUTION: This system is provided with a means for selling the own illustration on a platform by an illustration provider, a means for purchasing the sold illustration and constructing a AI model by a model constructor and a means for selling the constructed AI model on the platform.SELECTED DRAWING: Figure 1

A data processing model builder precompiles a data processing model using a dependency tree and parameters provided by a provider of a product or service. New parameters can be provided in an intuitive way, without the need to understand computer program code, and a new data processing model can be compiled quickly and efficiently. The precompiled data processing model can then be deployed to provide personalized parameters for the product or service to end users almost instantaneously on request.

The invention relates to a multi-agent system and method for Simulink modeling in the aviation field. The existing automatic modeling method for Simulink modeling in the aviation field highly depends on hard coding, converts formalized requirements into model design, and has the defects of high development cost, dependence on expert knowledge, incapability of automatic verification, no support of a third-party library and the like. According to the multi-agent system provided by the invention, a plurality of expert agents are integrated and designed and workflows are strictly arranged, so that the design, implementation and verification processes of Simulink modeling in the aviation field are fully automated. With reference to abstract drawings, the whole system comprises a model designer, a test review device, a model builder, an execution and debugger, a report compiler and an Agent RAG subsystem, and different sub-modules depend on large model capability and a context management strategy to collaboratively complete tasks in a specific process. Compared with a traditional automatic modeling technology, the system and the method have the advantage that the modeling flexibility and efficiency are greatly improved.

Apparatus and method for integrating external AI services. For example, one embodiment of a method comprises: preparing training data received from various data streams on the cloud-based application service, wherein preparing includes categorizing, filtering, and curating data from the data streams; generating source data model objects (DMOs) based on training data; providing the source DMOs to the external AI service over a secure communication channel, the external AI service to register an AI model based on the source DMOs and to generate a corresponding AI model endpoint; executing an AI model builder on the cloud-based application service, the AI model builder to generate an AI model reference configurable with connection information to communicate with the AI model endpoint, the AI model builder configurable to automatically trigger an inference when data mapped to an input of the AI model is changed in one or more of the source DMOs.

The invention provides an evaluation report generation method and system based on parameter management and model combination, and the method comprises the following steps: obtaining input data which comprises energy parameter data and model data; preset standard structure data tables are filled with the energy parameter data, a target database filled with data is obtained, and the number of the standard structure data tables is at least four; different modules in the model data are freely combined, and then energy parameters in the target database are called to obtain evaluated models of different energy combinations; and performing logic verification on the parameter dependency relationship in the evaluated model, and calculating and outputting economic evaluation results of different energy combinations after the verification succeeds. According to the invention, through database standardization design and a modularized model builder, the pain point of parameter management and combination in new energy economic evaluation is solved, innovativeness and practicability are achieved, and the evaluation efficiency and accuracy of complex energy projects are significantly improved.

A robot diagnostic system includes a first robot, a second robot configured to simulate driving of the first robot, a model builder configured to learn data on a normal driving state or an abnormal driving state of the first robot or the second robot and build a model that is configured to determine whether the first robot is abnormal, and a diagnostic device configured to receive data on the driving of the first robot and diagnose a state of the first robot through the built mode.

A data processing model builder precompiles a data processing model using a dependency tree and parameters provided by a provider of a product or service. New parameters can be provided in an intuitive way, without the need to understand computer program code, and a new data processing model can be compiled quickly and efficiently. The precompiled data processing model can then be deployed to provide personalized parameters for the product or service to end users almost instantaneously on request.

Methods, systems, apparatuses, devices, and computer program products are described. A data service may receive a first user input indicating a first set of entities for training an artificial intelligence (AI) model for propensity score-prediction. The data service may receive a second user input indicating a set of outcome conditions which define what a user would like to predict about a customer (e.g., propensity to purchase). The data service may generate the AI model accordingly, and based on executing the AI model, generate a set of prediction metrics (propensity scores) for a second set of entities. The data service may store an indication of the AI model for review by a user. When the user approves the AI model and publishes the AI model to the data service, the generated propensity scores may be used to generate a segment of entities of the second set of entities.

The hereby disclosed invention pertains to a method and system for creating and executing customized software-based models for simulating production processes. It involves defining simulation targets, selecting suitable equations from a digital catalog, and using a Model Builder Module to assemble these equations into a model. The digital catalog consists of equations stored in the Functional Mock-up Unit (FMU) format, which can be easily updated and reused. The method allows for rapid model creation and modification by simply adjusting a configuration file, eliminating the need for repeated qualification. This approach enhances the accuracy and efficiency of simulations, enabling real-time adjustments to production parameters based on model predictions. Additionally, the invention includes a workflow for adding new equations to the digital catalog, ensuring it remains current and comprehensive. The system supports various modeling types, including mechanistic, empirical, and machine learning models, and is compatible with GxP environments. This flexible and adaptable solution is particularly useful for optimizing bioprocesses in bioreactors, providing precise control over production conditions and outcomes.

The present invention discloses a system and method for modeling and monitoring processes in organizations using digital twins. The system has a model builder to create models, communicate with a first user device and create an integrated model of the process called digital twin definition. The digital twin includes a server component for executing the digital twin definition and the server component further communicates with multiple transaction systems and auxiliary systems. The digital twin has a client module that enables output on a second user device and deploys the digital twins to monitor the processes. The present invention discloses method for creating dynamic models and monitor said models using digital twin. The present invention also discloses a method for creating said PLAY.

System and method are disclosed for multi-phase process of automated data capture for photogrammetry and 3D model building of an unknown object (311) in an unknown environment. Planner module (152) generates a flight plan (413) for a camera drone (110) to fly autonomously on a flight path along a virtual polygon grid (302) defined above the target object (311) during a survey phase. Model builder computer (153) receives a point cloud dataset (321) captured by LiDAR sensor on camera drone (301) during survey flight and constructs low resolution 3D mesh (331) of the target object (311). Planner module (152) generates a flight path (413) for camera drone inspection phase with virtual waypoints surrounding the target object (311) at a marginal distance from the surface defined by the low resolution 3D mesh (331). Model builder (153, 163) builds a high resolution 3D model (422) of the target object (311) using photogrammetry processing of high resolution images captured by camera drone (411, 412) during inspection phase.

Method for establishing and calibrating a on-demand software-based model for simulating a production process via a software-based Model Builder Module on a computer, wherein the Model Builder Module is connected to an ontology database that contains different domains, such as a bioprocessing data domain, a numeric simulation domain, and a mathematical model domains for the Model Builder Module, comprising the following steps of Defining the goal of the software based model, including information about the process the model describes, in particular process steps, cell line, molecule produced, variables the model predicts and threshold values of required model quality indicators; Selecting experimental data required for the calibration and the validation of the model in form of a list of experiments selectable in the Model Builder Module, wherein the context of the experiment data, which is stored in the ontology database matches the defined goal of the model; Composing the software-based model using the toolset proposed by the Model Builder Module which is specific to the respective process step the model describes; Calibrating the created software-based model with provided experimental data via the Model Builder Module; and Checking the validity and quality of the software-based model by performing a quality check of the Model using different mathematical analysis.

A system and method for modeling and monitoring processes in an organization using digital twins is disclosed. The system has a model builder that creates a model, communicates with a first user device and creates an integrated model of the process called a digital twin definition. The digital twin includes a server component for executing the digital twin definition and the server component also communicates with a plurality of transaction systems and ancillary systems. The digital twin has a client module that enables output on a second user device and deploys the digital twin to monitor the process. A method for creating a dynamic model and monitoring the model using a digital twin is disclosed. A method for creating the presentation is also disclosed.

The present disclosure relates to a robot diagnostic system, including: a first robot; a second robot configured to simulate driving of the first robot; a model builder configured to learn data about a normal driving state or an abnormal driving state of the first robot or the second robot and build a model configured to determine whether the first robot is abnormal; and a diagnosis device configured to receive data about driving of the first robot and diagnose a state of the first robot through the constructed model.