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features
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Description

Measurements are always subject to deviations from their true values, a phenomenon known as measurement uncertainty, especially when assessing or calibrating measurement tools or methodologies. To ensure quality control, it is essential to accurately quantify this uncertainty. GUMsim®, which adheres to the latest Guide to the Expression of Uncertainty in Measurement (GUM) and its supplement 1, utilizes sophisticated computational algorithms that facilitate a more effective determination of measurement uncertainty in line with ISO/IEC 17025 standards. The process of determining measurement uncertainty involves a mathematical relationship and statistical analysis of all variables influencing the measurement outcomes. To streamline this process, GUMsim provides a user-friendly input environment designed for various measurement models. Additionally, it offers a range of pre-defined application models that function as templates tailored to assist you in conducting specific evaluations, making it easier to embark on your measurement uncertainty assessments. This feature not only enhances the user experience but also encourages consistency in measurement practices across different applications.

Description

STOCHOS is an advanced probabilistic AI solution designed specifically for engineering and research and development applications. It harnesses existing simulation, testing, and measurement data to swiftly predict new variants while providing uncertainty assessments for each prediction, allowing engineers to discern when to trust the results or opt for traditional solvers. Utilizing the DIM-GP framework, STOCHOS is effective even with limited datasets, ranging from just a few dozen to a few hundred samples, and can handle various data types such as scalars, signals, 2D and 3D fields, meshes, geometries, and images. Its capabilities include surrogate modeling, uncertainty quantification, Bayesian and multi-objective optimization, as well as multi-fidelity modeling and sensitivity analysis, along with generative geometry techniques. STOCHOS Flow, a user-friendly visual workbench, enables the creation of workflows without the need for coding, allowing teams to deploy them as web applications. The software operates on local hardware and can be installed offline, ensuring accessibility and privacy. Founded in 2018 in Grafing bei München, PI Probaligence is part of the CADFEM Group and has established itself as a technology partner with Ansys, promoting innovative solutions in engineering. Furthermore, its ability to integrate seamlessly into existing processes enhances productivity and drives efficiency in engineering teams.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

No images available

Integrations

No details available.

Integrations

No details available.

Pricing Details

€870 one-time payment
Free Trial No 
Free Version No 

Pricing Details

Quote on request
Free Trial No 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based No 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac No 
Linux Yes 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

QuoData

Country

Germany

Website

www.quodata.de/gumsim

Vendor Details

Company Name

PI Probaligence GmbH

Founded

2018

Country

Germany

Website

probaligence.com

Product Features

Statistical Analysis

Analytics No 
Association Discovery No 
Compliance Tracking No 
File Management No 
File Storage No 
Forecasting No 
Multivariate Analysis No 
Regression Analysis No 
Statistical Process Control No 
Statistical Simulation Yes 
Survival Analysis No 
Time Series No 
Visualization No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

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