Wang et al., 2021 - Google Patents
Thermal performance optimization for housing unit design in a cold region of ChinaWang et al., 2021
- Document ID
- 4482985851230536377
- Author
- Wang S
- Liu N
- Zhang J
- Publication year
- Publication venue
- Journal of Building Performance Simulation
External Links
Snippet
Current housing unit design focuses on performance optimization, such as building energy use, daylighting, and occupant comfort. There is significant potential for efficient optimization in the early design stage. This paper proposed a building energy demand optimization …
- 238000005457 optimization 0 title abstract description 119
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
- G06Q10/063—Operations research or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5004—Architectural design, e.g. building design
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/20—Education
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
- G06Q50/08—Construction
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F2217/00—Indexing scheme relating to computer aided design [CAD]
- G06F2217/78—Power analysis and optimization
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce, e.g. shopping or e-commerce
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Jalali et al. | Design and optimization of form and facade of an office building using the genetic algorithm | |
| Yan et al. | Data-driven prediction and optimization of residential building performance in Singapore considering the impact of climate change | |
| Huang et al. | Optimal building envelope design based on simulated performance: History, current status and new potentials | |
| Chalal et al. | Energy planning and forecasting approaches for supporting physical improvement strategies in the building sector: A review | |
| Attia et al. | Assessing gaps and needs for integrating building performance optimization tools in net zero energy buildings design | |
| Jihad et al. | Forecasting the heating and cooling load of residential buildings by using a learning algorithm “gradient descent”, Morocco | |
| Yi | User-driven automation for optimal thermal-zone layout during space programming phases | |
| Chen et al. | Lighted-weighted model predictive control for hybrid ventilation operation based on clusters of neural network models | |
| Song et al. | Framework on low-carbon retrofit of rural residential buildings in arid areas of northwest China: A case study of Turpan residential buildings | |
| Mostafavi et al. | An interactive assessment framework for residential space layouts using pix2pix predictive model at the early-stage building design | |
| Mathur et al. | Assessing a fit-for-purpose urban building energy modelling framework with reference to Ahmedabad | |
| Fereidoni et al. | An assessment of the impact of building envelope design on the tradeoff between embodied and operating energy | |
| Khalifa et al. | Coupling TRNSYS 17 and CONTAM: simulation of a naturally ventilated double-skin façade | |
| Shakouri et al. | Developing an empirical predictive saved load-rating model for windows by using artificial neural network | |
| Abediniangerabi et al. | Estimating energy savings of ultra-high-performance fibre-reinforced concrete facade panels at the early design stage of buildings using gradient boosting machines | |
| Jayakeerti et al. | Predicting an energy use intensity and cost of residential energy-efficient buildings using various parameters: ANN analysis | |
| Wang et al. | Thermal performance optimization for housing unit design in a cold region of China | |
| Yuan et al. | Multi-atrium configuration design for energy efficiency in shopping malls: an ANN-based metamodel for sensitivity analysis and design optimization | |
| You et al. | Applying modified coot optimization algorithm with artificial neural network meta-model for building energy performance optimization: A case study | |
| Shao et al. | Multi-objective optimization design for rural houses in western zones of China | |
| Sayın et al. | A practical approach to performance-based building design in architectural project | |
| Ashraf et al. | Multiple machine learning models for predicting annual energy consumption and demand of office buildings in subtropical monsoon climate | |
| Wu et al. | Developing surrogate models for the early-stage design of residential blocks using graph neural networks | |
| Lahmar et al. | Multiobjective building design optimization using an efficient adaptive Kriging metamodel | |
| Nguyen et al. | Enhancing energy intelligence in Taiwanese office buildings: Utilizing a novel BIM-derived dataset for AI-driven energy consumption prediction |