Multi-Objective Optimization Design for Cold-Region Office Buildings Balancing Outdoor Thermal Comfort and Building Energy Consumption DOI Creative Commons
Fei Guo,

Shiyu Miao,

Sheng Xu

и другие.

Energies, Год журнала: 2024, Номер 18(1), С. 62 - 62

Опубликована: Дек. 27, 2024

Performance parameters and generative design applications have redefined the human–machine collaborative relationship, challenging traditional architectural paradigms guiding process toward a performance-based transformation. This study proposes multi-objective optimization (MOO) approach based on performance simulation, utilizing Grasshopper-EvoMass platform. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is applied to coordinate two metrics—outdoor thermal comfort building energy loads—for of design. results indicate that (1) workflow established. Compared baseline design, optimized form shows significant improvement in performance. Pareto optimal solutions, under 2022 meteorological conditions, demonstrate an annual efficiency 16.55%, outdoor neutrality ratio increases by 1.11%. These suggest effectively balances loads comfort. (2) A total 1500 solutions were generated, from which 16 selected through front method. resulting layouts provide multiple feasible configurations for early-stage phase.

Язык: Английский

A Multi-Objective Optimization of Neural Networks for Predicting the Physical Properties of Textile Polymer Composite Materials DOI Open Access
Ivan Malashin, В С Тынченко, Andrei Gantimurov

и другие.

Polymers, Год журнала: 2024, Номер 16(12), С. 1752 - 1752

Опубликована: Июнь 20, 2024

This paper explores the application of multi-objective optimization techniques, including MOPSO, NSGA II, and SPEA2, to optimize hyperparameters artificial neural networks (ANNs) support vector machines (SVMs) for predicting physical properties textile polymer composite materials (TPCMs). The process utilizes data on characteristics constituent fibers fabrics used manufacture these composites. By employing algorithms, we aim enhance predictive accuracy ANN SVM models, thereby facilitating design development high-performance effectiveness proposed approach is demonstrated through comparative analyses validation experiments, highlighting its potential optimizing complex material systems.

Язык: Английский

Процитировано

3
Multi-Objective Optimization and Sensitivity Analysis of Building Envelopes and Solar Panels Using Intelligent Algorithms DOI Creative Commons
Na Zhao, Jia Zhang,

Yewei Dong

и другие.

Buildings, Год журнала: 2024, Номер 14(10), С. 3134 - 3134

Опубликована: Окт. 1, 2024

The global drive for sustainable development and carbon neutrality has heightened the need energy-efficient buildings. Photovoltaic buildings, which aim to reduce energy consumption emissions, play a crucial role in this effort. However, potential of building envelope electricity generation is often underutilized. This study introduces an efficient hybrid method that integrates Particle Swarm Optimization (PSO), Support Vector Machine (SVM), Non-dominated Sorting Genetic Algorithm II (NSGA-II), weighted Technique Order Preference by Similarity Ideal Solution (TOPSIS) method. integrated approach was used optimize external structure photovoltaic components, leading significant reductions: overall decreased 41% (from 105 kWh/m2 63 kWh/m2), emissions 34% 13,307 tCO2eq 8817 tCO2eq), retrofit operating costs 20% CNY 13.12 million 10.53 million) over 25-year period. Sensitivity analysis further revealed window-to-wall ratio windows roles these outcomes, highlighting their enhance performance. These results confirm feasibility achieving substantial savings emission reductions through optimized design approach.

Язык: Английский

Процитировано

3
A theoretical model for evaluation of non-visual effects of lighting based on human performance: Comprehensive research ideas DOI
Xian Zhang, Lin Ma, Jing Chen

и другие.

Displays, Год журнала: 2025, Номер unknown, С. 103038 - 103038

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0
Energy impact of integrative lighting: a systematic literature review DOI Creative Commons

Mahmoud Taghizadeh,

Niko Gentile,

Pimkamol Mattsson

и другие.

Energy and Buildings, Год журнала: 2025, Номер unknown, С. 115920 - 115920

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0
Multi-objective Optimization Design of Steel Cross Section of Integrated Supports and Hangers Based on NSGA-Ⅱ and MDOS DOI

Xiongtao Fan,

Lu Yang, Xuefeng Zhao

и другие.

Journal of Building Engineering, Год журнала: 2024, Номер 98, С. 111317 - 111317

Опубликована: Ноя. 17, 2024

Язык: Английский

Процитировано

2
Sustainable illumination: experimental and simulation analysis of illumination for workers wellbeing in the workplace DOI Creative Commons
Saeed Shojaee Barjoee, S.G. Gendler

Heliyon, Год журнала: 2024, Номер 10(24), С. e40745 - e40745

Опубликована: Ноя. 30, 2024

Язык: Английский

Процитировано

2
Bio-signals based Occupant-Centric Lighting Control for Cognitive Performance, Visual Fatigue and Energy Consumption DOI
Dahyun Jung, Seunghoon Jung, Jongbaek An

и другие.

Building and Environment, Год журнала: 2024, Номер unknown, С. 112424 - 112424

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

0
Multi-Objective Optimization Design for Cold-Region Office Buildings Balancing Outdoor Thermal Comfort and Building Energy Consumption DOI Creative Commons
Fei Guo,

Shiyu Miao,

Sheng Xu

и другие.

Energies, Год журнала: 2024, Номер 18(1), С. 62 - 62

Опубликована: Дек. 27, 2024

Performance parameters and generative design applications have redefined the human–machine collaborative relationship, challenging traditional architectural paradigms guiding process toward a performance-based transformation. This study proposes multi-objective optimization (MOO) approach based on performance simulation, utilizing Grasshopper-EvoMass platform. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is applied to coordinate two metrics—outdoor thermal comfort building energy loads—for of design. results indicate that (1) workflow established. Compared baseline design, optimized form shows significant improvement in performance. Pareto optimal solutions, under 2022 meteorological conditions, demonstrate an annual efficiency 16.55%, outdoor neutrality ratio increases by 1.11%. These suggest effectively balances loads comfort. (2) A total 1500 solutions were generated, from which 16 selected through front method. resulting layouts provide multiple feasible configurations for early-stage phase.

Язык: Английский

Процитировано

0