武汉理工大学2020数学建模校内集训/MCM Finallist Award/华中赛省二等资料
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Updated
Jun 27, 2021 - Jupyter Notebook
武汉理工大学2020数学建模校内集训/MCM Finallist Award/华中赛省二等资料
Toolkit for discovering and aggregating data for whole-cell modeling
Ontology of algorithms for analyzing biological models, their parameters, and their outputs
The Systems Biology Ontology (SBO) is a set of controlled, relational vocabularies of terms commonly used in Systems Biology, and in particular in computational modeling.
2023年美国大学生数学建模竞赛 Meritorious Winner 参赛作品
Software and Data associated with "Reducing Bias and Quantifying Uncertainty in Fluorescence Produced by PCR''
Utilities for building standardized command-line interfaces for biosimulation software packages
A GUI-tool for computing Nash flows over time with or without spillback as well as (spillback) thin flows.
3MC - African Mathematical School on Mathematical Modeling in Biology
A predictive model for postgraduate program enrollment based on historical data, student rankings, and various influencing factors.
Tutorials for BioSimulators
pyNeuroML simulation program via BioSimulators-compliant command-line interface and Docker container
This repository contains the code and data used in our research, supervised by Dr. Prabir Daripa, to model and analyze the effects of SP flooding, with a specific focus on the shear-thinning behavior of polymers.
Trigon Evo is a powerful Roblox Lua IDE and script executor that allows you to run and test Lua scripts with ease. Capable of executing 99% of scripts, Trigon Evo ensures seamless performance across Windows 8-11, with quick updates released within 1-24 hours after each Roblox update, which typically occurs every Wednesday.
"Simulations for the paper Mathematical Modeling of the Short Circuit Mode of a Voltage Transformer"
a Program for Building a Visualization Mathematical Model
This project applies the Firefly Algorithm (FA) to optimize logistics hub selection, aiming to minimize total transportation cost while meeting delivery demands.
This repository presents a project that explores the realm of Predictive Maintenance, focusing on assessing the reliability of a hybrid Markov model compared to traditional models. The objective is to gain insights into optimal strategies for industrial maintenance scheduling.
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