Search Results for "time series forecasting java"
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Showing 25 open source projects for "time series forecasting java"
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PyTorch Forecasting
Time series forecasting with PyTorch
PyTorch Forecasting aims to ease state-of-the-art time series forecasting with neural networks for both real-world cases and research alike. The goal is to provide a high-level API with maximum flexibility for professionals and reasonable defaults for beginners. A time series dataset class that abstracts handling variable transformations, missing values, randomized subsampling, multiple history lengths, etc. -
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forecast
Forecasting Functions for Time Series and Linear Models
The forecast package is a comprehensive R package for time series analysis and forecasting. It provides functions for building, assessing, and using univariate forecasting models (e.g. ARIMA, exponential smoothing, etc.), tools for automatic model selection, diagnostics, plotting, forecasting future values, etc. It's widely used in statistics, economics, business forecasting, environmental science, etc. -
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Kronos
A Foundation Model for the Language of Financial Markets
...This allows Kronos to perform a variety of quantitative tasks such as forecasting, pattern recognition, and anomaly detection within financial datasets. It is optimized for the noisy and complex nature of market data, distinguishing it from general-purpose time-series models. The project includes multiple pre-trained model sizes and tools for fine-tuning, making it adaptable to different computational constraints and use cases. -
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Prophet
Tool for producing high quality forecasts for time series data
Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. -
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NeuralProphet
A simple forecasting package
NeuralProphet bridges the gap between traditional time-series models and deep learning methods. It's based on PyTorch and can be installed using pip. A Neural Network based Time-Series model, inspired by Facebook Prophet and AR-Net, built on PyTorch. You can find the datasets used in the tutorials, including data preprocessing examples, in our neuralprophet-data repository. The documentation page may not we entirely up to date. Docstrings should be reliable, please refer to those when in... -
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A tool to support individuals and teams using high-maturity, metrics-intensive project management methodologies [such as PSP(SM) and TSP(SM)]. Supports personal and team earned value tracking and forecasting; simplifies metrics collection and analysis.
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Deep learning time series forecasting
Deep learning PyTorch library for time series forecasting
Example image Flow Forecast (FF) is an open-source deep learning for time series forecasting framework. It provides all the latest state-of-the-art models (transformers, attention models, GRUs) and cutting-edge concepts with easy-to-understand interpretability metrics, cloud provider integration, and model serving capabilities. Flow Forecast was the first time series framework to feature support for transformer-based models and remains the only true end-to-end deep learning for time series forecasting framework. ... -
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Padasip
Python Adaptive Signal Processing
Padasip (Python Adaptive Signal Processing) is a Python library tailored for adaptive filtering and online learning applications, particularly in signal processing and time series forecasting. It includes a variety of adaptive filter algorithms such as LMS, RLS, and their variants, offering real-time adaptation to changing environments. The library is lightweight, well-documented, and ideal for research, prototyping, or teaching purposes. Padasip supports both supervised and unsupervised filtering modes and is built to be modular and extensible, making it easy to integrate into larger machine learning pipelines or control systems. -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. ... -
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ksqlDB
The database purpose-built for stream processing applications
Build applications that respond immediately to events. Craft materialized views over streams. Receive real-time push updates, or pull current state on demand. Seamlessly leverage your existing Apache Kafka® infrastructure to deploy stream-processing workloads and bring powerful new capabilities to your applications. Use a familiar, lightweight syntax to pack a powerful punch. Capture, process, and serve queries using only SQL. No other languages or services are required. ksqlDB enables you... -
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Fixer
A foreign exchange rates and currency conversion API
...One of its key strengths is its simplicity, as it uses straightforward RESTful endpoints and JSON responses that can be easily integrated into web or mobile applications. Fixer also supports time-series and fluctuation data, enabling more advanced financial analysis and forecasting use cases. While a free tier is available with some limitations, more advanced features such as higher request limits and additional base currencies are offered through paid plans. -
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CrNiCKL
CrNiCKL (chronicle) is a Java database for time series
CrNiCKL (pronounced "chronicle") is a data manager written in Java handling large sets of heterogeneous time series. A simple schema system allows to confiture value types and time domains. CrNiCKL runs on top of SQL or NoSQL databases. Drivers for JDBC and MongoDB are available. -
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SmartRoot
Semi-automated root image analysis software
SmartRoot is a semi-automated image analysis software which streamlines the quantification of root growth and architecture for complex root systems. The software combines a vectorial representation of root objects with a powerful tracing algorithm which accommodates to a wide range of image source and quality. The software supports a sampling-based analysis of root system images, in which detailed information is collected on a limited number of roots selected by the user according to... -
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LDT
Automatic Time Series Analysis with Stationary VAR Models
LDT is designed for automatic time-series analysis. Current version focuses on stationary vector autoregressive models (VAR) and the related analyses such as forecasting and Granger causality. See the following paper for an application: See http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2818213 -
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Personal Financier
Personal budgeting software with projections based on past trends.
Personal Financier is a tool to track expenses by category and then project the impact to the overall budget. Underspending in a given month increases the budget available to use in future months, and overspending reduces it. In this way, the budget adjusts over time to reflect actual spending. The easiest way to try it out is to use the demo account (password demo) that gets automatically setup on install. Enjoy! (See Wiki for more detailed information) -
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JFreeChart is a free (LGPL) chart library for the Java(tm) platform. It supports bar charts, pie charts, line charts, time series charts, scatter plots, histograms, simple Gantt charts, Pareto charts, bubble plots, dials, thermometers and more. *** JFreeChart has moved to GitHub: https://github.com/jfree/jfreechart ***
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GWT Highcharts is a freely available open source library that provides an elegant and feature complete approach for including Highcharts and Highstock visualizations within a GWT application using pure Java code. Note: the source code for this project is now being maintained on GitHub here: https://github.com/squinn/gwt-highcharts
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QuantComponents
Free Java components for Quantitative Finance and Algorithmic Trading
An open-source framework for financial time-series analysis and algorithmic trading, based on Java and OSGi, with an Eclipse front-end. * Highly modular: usable as plain java API, OSGi components, or integrated into Eclipse * Standalone or client-server architecture, depending on performance and reliability needs * Integrated with Interactive Brokers through IB Java API * Generic broker API, it can easily be extended to work with other brokers * It works with historical and/or realtime market data * Backtesting facility * Extensible SWT charting library -
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ToolTimeS40
ToolTimeS40 is a S40 Series Mobile Phone midlet
ToolTimeS40 is a S40 Series Mobile Phone midlet for Timemanagment tasks on a click. It supports 6 Live counter "Jobtime,Drive,Work,Pause,Work,Drive" and offers posibilities to save additional information as well. You will never loose a second. -
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ChronoDB
ChronoDB is a data manager for generic time series.
The project has been renamed CrNiCKL (chronicle) and moved to http://crnickl.sourceforge.net. ChronoDB is a data manager written in Java. It supports time series of any type. With its simple and powerful schema subsystem it takes charge of very large heterogeneous data sets. The software consist of an API and a generic implementation layer running on top of an SQL or a NoSQL system. Applications can mix objects from multiple ChronoDB databases. -
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OpenForecast is a package of general purpose, forecasting models written in Java that can be applied to any data series. No knowledge of forecasting is required. Using this package, the most appropriate algorithm for your data will be selected.
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OpenQuant is an open source backtesting and quantitative / technical analysis platform for time series financial data. It offers a simple tradesystem development framework using open financial data from Yahoo.
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Regatta is a planning system for school personnel on a set of small tasks. It provides a better employment and mobility of teachers over the many activity programs. It supports budgets (time/money) of activity programs and forecasting of personnel needs
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JTSA is an educational time series analysis tool for simple calculations and forecasts using the additional or multiplicative seasonal decomposition method.
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