Search Results for "model-builder"

Grafana OSS is the leading open-source platform for visualization and observability. It enables teams to query, visualize, alert on, and explore telemetry data from multiple sources in a single interface. With support for 100+ data source plugins—including Prometheus, Loki, Elasticsearch, InfluxDB, SQL/NoSQL databases, and OpenTelemetry—Grafana helps teams correlate metrics, logs, and traces across applications and infrastructure. Users can build interactive dashboards with rich...

***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** ***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** ***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** Within the SIROCCO suite of numerical tools, the purpose of SDAP is to provide a flexible platform to carry out multivariate assimilation of geophysical data in a numerical model. The program is multi-grid (finite differences or finite elements), multi-algebra (plug-in analysis kernels), multi-model (simple standardized interface). The program supports reduced-order data assimilation methods, as well as Ensemble assimilation approaches such as the Ensemble Kalman Filter. Recent additions include extensions towards simultaneous assimilation and downscaling (AMICO project), and a toolbox for ensemble assessment (SCRUM project).

Autoplot is an interactive browser for data on the web. Give Autoplot a URL or local file name and it creates a sensible plot of the data. Autoplot allows you to interactively browse data stored in ascii, .cdf, netcdf, and many other formats. Autoplot's source has been moved to GitHub. Thanks to SourceForge for many years of hosting!

This project describes a model of how the semantic human memory represents the information relevant to the objects of the world in text format. It provides a system and a GUI application capable of extracting and managing concepts and relations from English texts. https://aseryla2.sourceforge.io/

Pretty Damn Quick (PDQ) analytically solves queueing network models of computer and manufacturing systems, data networks, etc., written in conventional programming languages. Generic or customized reports of predicted performance measures are output.

Malware Analysis Network in Taiwan <Man in Taiwan, MiT> Welcome to contact us (TonTon@TWMAN.ORG) if you are interested in collaborating with us. This project is open source and distributed under the GNU General Public License version 3. Please feel free to add to or modify this source and propose changes or new converters. Developer & Copyrighted by : TonTon Hsien-De Huang Prompter: Jazz Yao-Tsung Wang, Figaro Chen-Ho Yang | Logo Desinger:Temaki Guo Community on...

The CAPS Scenario Builder will allow government officials, conservation groups and others to submit "scenarios" for proposed changes to land cover and infrastructure so that these changes can be assessed for their impact on ecological integrity.

This project examines techniques to model three-dimensional rigid body motion using the geometric algebra of Dual Quaternions and how such models compare to more traditional models when used in underconstrained filtering applications.

The Model Interaction Environment for Neuroscience provides tools for development, searching, editing, execution, and visualization of biophysical models, abstract mathematical models, and experimental protocols used in neuroscience research.

KML is a knowledge base with support of logical modeling. Advanced model is used to represent knowledge as a set of statements similar to natural language sentences. This project hosts a set of model storage library and server (vrb-ols) and clients.

This is a implementation of the 'enhanced Topic-based Vector Space Model' (eTVSM) using the python language. A Java-Version and maybe other java-code contributions are planned.

RISO: distributed, heterogeneous Bayesian belief networks. Belief network: a probability model defined on an acyclic directed graph; distributed: nodes can be on different hosts; and heterogeneous: allowing different types of conditional distributions.

Development codes for hierarchical stochastic block models

...It provides algorithms for unsupervised and supervised learning, which may be done with continuous or discrete labels. Post analysis, the toolkit further automates building the visual representations for the trained model.