Mirror of GLPK versions and changes made by me and by others elsewhere
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Updated
May 16, 2025 - C
Mirror of GLPK versions and changes made by me and by others elsewhere
To make An Library collection of An Algorithm., by Calculating it's mathematical modelling and applying Pseudocode while i also mentioned references, and this all program's i publish is my original work as i taken references not code
Graphical user interface for Theta applications.
Sets and Fields Scientific Data Model and Scalable I/O Library
2D Poisson Equation Solver. Discretized using the Finite Difference Method & Solved by Parallelising the Jacobi Iterative Method via the OpenMP API.
This project is level_1 end semester exam course in Industrial mathematics which is about Mathematical Models in the Interaction Between the Immune System and Cancer.
C implementation of Newton's method for solving system of equations
Parallel-fibre to Purkinje cell plasticity simulator. Multiple optimisation functions incorporated to fit model to experimental data.
This repo is a solution (algorithm) to a number of engineering application problems
A backup of Hoste & Thistlethwaite's knot software, as indexed on the Knot Atlas
a program from 42 Amman Core Curriculum designed to graphically render fractals using mathematics !
Generic library for making predictions using Simca-QP. Use this library to write standalone and client/server applications for SIMCA-QP.
Finance algorithms and models for price evolution and dynamic hedging
LibSBMLSim mathematical simulation program via BioSimulators-compliant command-line interface and Docker container
The chemgps-sqp2 package contains a daemon, client and standalone program for making predictions using Umetrics Simca-QP. The programs is based on the libchemgps library.
🖥️ FdF - 42 Project FdF is a wireframe 3D renderer written in C using MiniLibX, featuring parametric line rendering ,and isometric projection, and events management. 🚀
A mesmerizing ASCII art animation of a rotating donut rendered in your terminal, written in C.
A simple linear regression that models the relationship between inputs and output using weights and a bias. It computes the prediction with the weighted sum formula: output=∑i=1n(wi×xi)+b output=i=1∑n(wi×xi)+b
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