Numericals

Numerical Methods Solver - Flutter App

This Flutter app is a comprehensive numerical toolbox implementing various algorithms and methods described in Numerical Analysis by Richard L. Burden and J. Douglas Faires. It aims to provide a versatile solution for solving equations and performing complex computations commonly encountered in mathematical and scientific fields.

Overview

The app covers a wide spectrum of numerical algorithms categorized into different modules, each catering to specific mathematical problems. Users can access these modules through a user-friendly interface, enabling them to input equations or data sets and apply the desired method to obtain accurate solutions.

Get this app

• Download the app from here

Mockups

Implemented Algorithms

Nonlinear Systems

• Bisection Method
• Fixed Point Method
• Newton Method
• Modified Newton Method
• Secant Method
• Regula Falsi Method (Method of False Position)

Features

• User-friendly Interface: Intuitive interface allowing users to input equations, select algorithms, and view detailed step-by-step solutions or concise results.
• Educational Tool: Ideal for students, academics, and professionals for understanding and applying numerical methods.
• Accuracy and Efficiency: Algorithms are optimized for accuracy and efficiency to handle a wide range of mathematical problems.
• Customizable Outputs: Provides options for viewing results in detailed or summary formats based on user preferences.
• Platform Compatibility: Compatible with various devices running Flutter, ensuring accessibility across different platforms.

Installation and Usage

1. Clone the Repository: git clone https://github.com/yourusername/numerical-methods-app.git
2. Open in Flutter: Open the project in Flutter/Dart-supported IDE (e.g., Android Studio, VSCode).
3. Run the App: Launch the app on an emulator or physical device using flutter run.

How to Use

1. Launch the app and navigate to the desired numerical method category.
2. Input the required parameters, equations, or data sets.
3. Select the specific algorithm or method you want to apply.
4. Obtain solutions or results with detailed step-wise explanations or concise output, depending on the selected method.

Contributions and Support

• Contributions: Contributions, bug reports, or suggestions for enhancements are highly appreciated. Submit pull requests or open issues to contribute.
• Feedback: Feel free to provide feedback or feature requests through GitHub issues or contact the development team directly.

License

This project is licensed under the MIT License - you’re free to modify, distribute, and use the code for personal or commercial projects.