The Predictive Ecosystem Analyzer (PEcAn) is an integrated ecological bioinformatics toolbox.
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Updated
May 27, 2024 - R
The Predictive Ecosystem Analyzer (PEcAn) is an integrated ecological bioinformatics toolbox.
Multi-species size-based ecological modelling in R
Food Wastage Management: Providing a simpler means of collecting the leftover food from restaurants and distributing the same to those in need
RBBGCMuso is a software package that supports the application of the Biome-BGCMuSo biogeochemical model.
ForestESS simulates plant demographic processes (e.g., growth, reproduction, and mortality), competition for light and soil resources, and soil biogeochemical processes. The codes are from the version of LM3-PPA used to simulate the forest successional dynamics in the paper of Weng, E., Farrior, CE, Dybzinski, R, and Pacala, SW, et al. 2016 Glob…
Package to help the in calibration of Atlantis
A predator-prey simulation programmed with the p5.js library.
🧫 A complex cellular automaton which simulates an entire ecosystem : universe, flora and fauna.
Source data and code supporting model-based analysis of emergent properties (ECA) of soil enzyme-driven organic matter decomposition
An ecosystem and evolution simulation in HTML5 and JS.
Projects developed in AED
Extendable, dynamic, process-based herbivore simulator that can be integrated into a dynamic vegetation model. Written as a C++ library.
This is a simulator of plants and herbivores and carnivores.
See the live simulation at : https://hemant27031999.github.io/Prey_Predator_Genetic_Algorithm/
A scalable multi-user desktop application to ensure feedback based qualitative enhancements of drugs.
Response time reduction system for patients with heart disease.
A population dynamic simulation of an island's ecosystem. The island consists of both herbivores and carnivores living in different landscape types. The goal is to investigate whether both species can survive in the long term. Exam project in INF200 (course code) at NMBU.
An Ecosystem simulation I build for my A-Level Computer Science NEA - GRADE: 99%
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