A decoupled ANN–NSGA-II framework for fast, bi-objective optimization of residential insulation: Balancing Life-Cycle Cost and Carbon Emissions

Published: 11 November 2025| Version 1 | DOI: 10.17632/ytvr9jn75g.1
Contributor:
mahdi mohammadi

Description

Three Python files for the code of three different models with extensions .py One Python file for the integration of NSGA-II with three ANN models, with the extensions .py Three models for heating, cooling, and coefficient with extensions .h5 Two files for standardizing the data used with extensions .pkl Two Excel files: one for the data used in the heating and cooling load models and the other for the coefficient model

Files

Institutions

  • Iran University of Science and Technology

Categories

Artificial Neural Network, Database

Licence