Genetic algorithm-optimized artificial neural network - optimization biomass and EPS

Published: 17 March 2025| Version 1 | DOI: 10.17632/3xphsf6xgk.1
Contributor:
BISWANATH MAHANTY

Description

This module contains scripts to develop a GA-optimized ANN model from an experimental data set, and use the models for individual and multi-objective process optimization based on desirability, and Pareto font.

Files

Steps to reproduce

a0_ANN_GA_two_resp .mat is used to develop ANN model from the Box-Behnken data set, considering R2trn, R2test, R2val, and R2CV scores. a2_ANN_Single_min_max.mat is used to optimize individual responses within design space. a3_ANN_multiobj.mat computes the pareto font using multiobjective score, while a4_Desirability_multi.mat calculates desirability-based scores for optimization.

Institutions

  • Karunya University

Categories

Artificial Intelligence, Artificial Neural Network, Genetic Algorithm, Multi-Objective Optimization

Related Links

Article
https://doi.org/10.1007/s00449-025-03143-3
cites this dataset

Licence