Multiobjective optimization of building design using TRNSYS simulations, genetic algorithm, and Artificial Neural Network

By L. Magnier, F. Haghighat. 2010

733 citations recorded by the source corpus.

Subfields: Building and Construction, Computational Theory and Mathematics, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/cabc6ec77e08b540f5fb034752446bcb6a284f99

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. Ala Al-Fuqaha
2. Wei Yang
3. Shiquan Zhou
4. Chun-qing Li
5. Peter von Buelow
6. Michela Turrin
7. Yaolin Lin
8. Rudi Stouffs

In Computational Theory and Mathematics

1. Wei Yang
2. Shiquan Zhou
3. Chun-qing Li
4. Peter von Buelow
5. Michela Turrin
6. Yaolin Lin
7. Rudi Stouffs

In Mechanical Engineering

1. Wei Yang
2. Shiquan Zhou
3. Chun-qing Li
4. Peter von Buelow
5. Michela Turrin
6. Yaolin Lin
7. Rudi Stouffs

Citations in the corpus

• Design Optimization Considering Variable Thermal Mass, Insulation, Absorptance of Solar Radiation, and Glazing Ratio Using a Prediction Model and Genetic Algorithm (2018, methodology): “However, Conraud [42] and Magnier and Haghighat [20] found 22.”
• Intelligent Building Control Systems for Thermal Comfort and Energy-Efficiency: A Systematic Review of Artificial Intelligence-Assisted Techniques (2021, background): “• ANN are usually combined with GA for optimization purpose [46,64].”
• Design explorations of performance driven geometry in architectural design using parametric modeling and genetic algorithms (2011, methodology): “For thermal comfort and energy consumption, a recent example is offered by Magnier and Haghighat [57], concerning design variables affecting passive solar behavior (such as size of the windows and thermal mass) and HVAC systems.”