Multi-objective Evolutionary Algorithm Supported Construction of Architectural Window Design Model Based on Visual Comfort - A Case Study of Office Buildings in Cold Regions

[1] Fu, X., & Sun, J. (2017). A new learning based dynamic multi-objective optimization evolutionary algorithm. In 2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings.Search in Google Scholar

[2] Celadyn, M. (2020). Integrative Design Classes for Environmental Sustainability of Interior Architectural Design. Sustainability, 12.Search in Google Scholar

[3] Bakar, A. M. R., Abbas, et al. (2017). Solution for Multi-Objective Optimization Master Production Scheduling Problems Based on Swarm Intelligence Algorithms. Journal of Computational and Theoretical Nanoscience.Search in Google Scholar

[4] Xie, Q., Wang, et al. (2017). Multi-objective evolutionary algorithm based on decision space partition and its application in hybrid power system optimization. Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies, 46(4), 827-844.Search in Google Scholar

[5] Wonoto, N. (2017). Integrating Parametric Structural Analysis and Optimization in the Architectural Schematic Design Phase [Doctoral dissertation, Clemson University].Search in Google Scholar

[6] George, A., Poguluri, S. K., Kim, J., & Cho, I. H. (2022). Design optimization of a multi-layer porous wave absorber using an artificial neural network model. Ocean Engineering.Search in Google Scholar

[7] Sarah, N., Christina, B., & Daryl, M. (2018). ‘Essentially it’s just a lot of bedrooms’: architectural design, prescribed personalization and the construction of care homes for later life. Sociology of Health & Illness.Search in Google Scholar

[8] Liang, H., & Huang, J. (2021). Research on the Architectural Design Positioning of University Halls. 005(006):P.25-32.Search in Google Scholar

[9] Zhang, J., Yao, Y., Sun, W., et al. (2022). Application of the Non-dominated Sorting Genetic Algorithm II in Multi-objective Optimization of Orally Disintegrating Tablet Formulation. AAPS PharmSciTech, 23(6), 1-7.Search in Google Scholar

[10] Park, W. Y., Tangpong, C., Ro, Y. K., et al. (2022). The design sourcing choice and technological performance in the upscale and downscale markets of an architectural innovation. Journal of Operations Management.Search in Google Scholar

[11] Fu, L., Huang, Z., Kilbinger, M., et al. (2010). The Application of the Multi-Dimensional Clustering Algorithm in the Field of Abell 383. In Galaxy Evolution: Infrared to Millimeter Wavelength Perspective.Search in Google Scholar

[12] Kong, S., Yeap, et al. (2018). Constructing a Mixed Methods Research Design: Exploration of an Architectural Intervention. Journal of Mixed Methods Research.Search in Google Scholar

[13] Luo, F. E., Peng, J. H., & Jian-Qiang, H. U. (2009). Application of data mining in the field of agriculture. Agriculture Network Information.Search in Google Scholar

[14] Feng, Y., Feng, L., Kwong, S., et al. (2022). A Multivariation Multifactorial Evolutionary Algorithm for Large-Scale Multiobjective Optimization. IEEE Transactions on Evolutionary Computation: A Publication of the IEEE Neural Networks Council, 26(2), 26.Search in Google Scholar

[15] Whitcomb, J. (2005). Achieve the watercolor look using Photoshop. Creative Designer, 2005(5), 2.Search in Google Scholar

[16] Guo, Y., Liu, Z., Tan, J., et al. (2022). LPFS: Learnable Polarizing Feature Selection for Click-Through Rate Prediction.Search in Google Scholar

[17] Liu, H., Pan, J., & Marxism, S. O. (2018). A Dilemma of Green Development in Northwest China and Its Countermeasures. Shanghai Environmental Sciences.Search in Google Scholar

[18] Yue, C., Dang, Y., Gu, S., et al. (2022). Optimization of undifferenced and uncombined PPP stochastic model based on covariance component estimation. GPS Solutions, 26(4).Search in Google Scholar

[19] Anandhi, J. S., & Joseyphus, R. J. (2022). Subsurface thermal sensitivity evaluation of magnetic nanoparticles for theranostics using infrared thermography.Search in Google Scholar

[20] Jwo, D. J., & Hsieh, M. H. (2021). GPS Vector Tracking Loop with Fault Detection and Exclusion.Search in Google Scholar

[21] Erdal, Y., Aye, E. E. E., & Dilek, N. M. (2022). Evaluation of Citrus reticulata essential oil: Chemical composition and antibacterial effectiveness incorporated gelatin on E. coli and S. aureus. International Journal of Environmental Health Research.Search in Google Scholar

[22] Bouquot, T. (2022). Architects Embrace a New Paradigm About Metal Building Design. Metal Architecture.Search in Google Scholar

[23] Alsaadani, S., & Souza, C. (2019). Teaching BPS to architects: A closer look at the building performance simulation ‘consumer’ and ‘performer’ training paradigms. IOP Conference Series: Earth and Environmental Science, 397(1), 012004 (10pp).Search in Google Scholar

[24] Jun, L. U., Zheng, G. S., Jin-Feng, M. A., et al. (2014). Optimization design and analysis of the SCARA robot. Journal of Shaanxi University of Science & Technology (Natural Science Edition).Search in Google Scholar

[25] Eriksson, A. B. (2016). Residential usability and social sustainability, Towards a paradigm shift within housing design?Search in Google Scholar

[26] Qing, M. A. (2016). Multi-objective Evolutionary Algorithm Based Weight Vectors Generation Method of MOEA/D. Computer Science.Search in Google Scholar

[27] Claps, R. J. (2010). Time-resolved spectroscopy system and methods for multiple-species analysis in fluorescence and cavity-ringdown applications.Search in Google Scholar

[28] Wu, G., & Zhao, G. (2022). Parameter influence law analysis and optimal design of a dual mass flywheel. 2(2):13.Search in Google Scholar

[29] Wang, W., Li, K., Jalil, H., et al. (Neural Computing and Applications, 1-19). An improved estimation of distribution algorithm for multi-objective optimization problems with mixed-variable.Search in Google Scholar

[30] Zhu, D., Hu, F., & Peng, X. (2018). Expansion Design of Interferometric Aperture Synthesis Arrays Based on Multi-Objective Optimization. IEEE Access.Search in Google Scholar

[31] Pan, J. S., Liu, N., & Chu, S. C. (2022). A competitive mechanism based multi-objective differential evolution algorithm and its application in feature selection. Knowledge-Based Systems, 245, 108582.Search in Google Scholar