DataMeltjWork.ORG
|
Simcenter ComposeSiemens
|
|||||
Related Products
|
||||||
About
DataMelt (or "DMelt") is an environment for numeric computation, data analysis, data mining, computational statistics, and data visualization. DataMelt can be used to plot functions and data in 2D and 3D, perform statistical tests, data mining, numeric computations, function minimization, linear algebra, solving systems of linear and differential equations. Linear, non-linear and symbolic regression are also available. Neural networks and various data-manipulation methods are integrated using Java API. Elements of symbolic computations using Octave/Matlab scripting are supported.
DataMelt is a computational environment for Java platform. It can be used with different programming languages on different operating systems. Unlike other statistical programs, it is not limited to a single programming language. This software combines the world's most-popular enterprise language, Java, with the most popular scripting language used in data science, such as Jython (Python), Groovy, JRuby.
|
About
Simcenter Compose is a numerical computing environment from Siemens designed for custom mathematical data operations and CAE pre- and post-processing work. It allows engineers to perform a wide range of math operations, including linear algebra, matrix manipulation, statistics, differential equations, signal processing, control systems, polynomial fitting, and optimization. The software includes native CAE and test result readers that help users better understand systems and support model-based development. Simcenter Compose provides a user-friendly integrated development environment with all capabilities available in one multi-functional tool and no additional toolboxes required. Users can develop reusable scripts, automate repeated calculations, visualize results with 2D and 3D plots, and connect with OML, Octave, and Python environments. It can be used as a standalone tool or alongside other Simcenter products such as Simcenter Embed and Simcenter Twin Activate.
|
|||||
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
|||||
Audience
scientists, students
|
Audience
Simcenter Compose is best suited for engineers, simulation specialists, CAE analysts, product development teams, and technical organizations that need numerical computing, scripting, data visualization, and model-based development support
|
|||||
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
|||||
API
Offers API
|
API
Offers API
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
$0
Free Version
Free Trial
|
Pricing
No information available.
Free Version
Free Trial
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
|||||
Company InformationjWork.ORG
Founded: 2005
United States
datamelt.org
|
Company InformationSiemens
Founded: 1847
Germany
www.siemens.com/en-us/products/simcenter/systems-simulation/compose/
|
|||||
Alternatives |
Alternatives |
|||||
|
|
|
|||||
|
|
|
|||||
|
|
|
|||||
|
|
|
|||||
Categories |
Categories |
|||||
Data Visualization Features
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery
Statistical Analysis Features
Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Survival Analysis
Time Series
Visualization
Artificial Intelligence Features
Chatbot
For eCommerce
For Healthcare
For Sales
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
Data Analysis Features
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Data Mining Features
Data Extraction
Data Visualization
Fraud Detection
Linked Data Management
Machine Learning
Predictive Modeling
Semantic Search
Statistical Analysis
Text Mining
Deep Learning Features
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
|
||||||
Integrations
Apache NetBeans
Check Point IPS
Check Point Infinity
Eclipse BIRT
Oracle Big Data Discovery
|
Integrations
Apache NetBeans
Check Point IPS
Check Point Infinity
Eclipse BIRT
Oracle Big Data Discovery
|
|||||
|
|
|