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Average Ratings 0 Ratings

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ease
features
design
support

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Description

MPCPy is a Python library designed to support the testing and execution of occupant-integrated model predictive control (MPC) within building systems. This tool emphasizes the application of data-driven, simplified physical or statistical models to forecast building performance and enhance control strategies. It comprises four primary modules that provide object classes for data importation, interaction with real or simulated systems, data-driven model estimation and validation, and optimization of control inputs. Although MPCPy serves as a platform for integration, it depends on various free, open-source third-party software for model execution, simulation, parameter estimation techniques, and optimization solvers. This encompasses Python libraries for scripting and data manipulation, along with more specialized software solutions tailored for distinct tasks. Notably, the modeling and optimization tasks related to physical systems are currently grounded in the specifications of the Modelica language, which enhances the flexibility and capability of the package. In essence, MPCPy enables users to leverage advanced modeling techniques through a versatile and collaborative environment.

Description

Enhance artificial intelligence by utilizing a diverse array of models. AI models serve as innovative building blocks, and Sieve provides the simplest means to leverage these components for audio analysis, video generation, and various other applications at scale. With just a few lines of code, you can access cutting-edge models and a selection of ready-to-use applications tailored for numerous scenarios. You can seamlessly import your preferred models similar to Python packages while visualizing outcomes through automatically generated interfaces designed for your entire team. Deploying custom code is a breeze, as you can define your computational environment in code and execute it with a single command. Experience rapid, scalable infrastructure without the typical complexities, as Sieve is engineered to automatically adapt to increased traffic without any additional setup required. Wrap models using a straightforward Python decorator for instant deployment, and benefit from a comprehensive observability stack that grants you complete insight into the inner workings of your applications. You only pay for what you consume, down to the second, allowing you to maintain full control over your expenditures. Moreover, Sieve's user-friendly approach ensures that even those new to AI can navigate and utilize its features effectively.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Python
Docker
Ubuntu

Integrations

Python
Docker
Ubuntu

Pricing Details

Free
Free Trial
Free Version

Pricing Details

$20 per month
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

MPCPy

Country

United States

Website

github.com/lbl-srg/MPCPy

Vendor Details

Company Name

Sieve

Website

www.sievedata.com

Product Features

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