Dataset and code for AI-supported many-objective optimization of U3A design in cold regions

Description

This repository contains the dataset and code supporting the article “Multi-objective optimization based on ANN and NSGA-III: integrated design of luminous environment, thermal comfort, and heating/cooling loads for U3A in cold regions”. The repository includes: (1) the 1,900-case simulation dataset, (2) definitions of the 19 design variables and 12 performance objectives, (3) scripts for training and evaluating the 12 ANN surrogate models, (4) Sobol sensitivity analysis scripts, and (5) NSGA-III optimization scripts. The files are provided to support transparency and reproducibility of the reported results.

Steps to reproduce

1. Open dataset_1900_cases.csv. 2. Refer to variable_dictionary.csv for definitions of the 19 inputs and 12 outputs. 3. Install the Python packages listed in requirements.txt. 4. Run ann_training_and_evaluation.py to reproduce ANN surrogate model training and evaluation. 5. Run sobol_sensitivity_analysis.py to reproduce the Sobol sensitivity analysis. 6. Run nsga3_optimization.py to reproduce the many-objective optimization process.

Institutions

• Tianjin University

  Tianjin, Tianjin

Categories

Licence