相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Machine learning-based seismic response and performance assessment of reinforced concrete buildings
F. Kazemi et al.
ARCHIVES OF CIVIL AND MECHANICAL ENGINEERING (2023)
Predictive Model of Clothing Insulation in Naturally Ventilated Educational Buildings
Maria L. de la Hoz-torres et al.
BUILDINGS (2023)
Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
Faramarz Bagherzadeh et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2023)
A systematic review of personal thermal comfort models
Larissa Arakawa Martins et al.
BUILDING AND ENVIRONMENT (2022)
Application of machine learning in thermal comfort studies: A review of methods, performance and challenges
Zahra Qavidel Fard et al.
ENERGY AND BUILDINGS (2022)
Variables That Affect Thermal Comfort and Its Measuring Instruments: A Systematic Review
Tamara Mamani et al.
SUSTAINABILITY (2022)
Comparison of models for predicting winter individual thermal comfort based on machine learning algorithms
Bin Yang et al.
BUILDING AND ENVIRONMENT (2022)
Using machine learning algorithms to multidimensional analysis of subjective thermal comfort in a library
Ge Song et al.
BUILDING AND ENVIRONMENT (2022)
Investigating the performance of machine learning models combined with different feature selection methods to estimate the energy consumption of buildings
Xue Liu et al.
ENERGY AND BUILDINGS (2022)
Measuring the right factors: A review of variables and models for thermal comfort and indoor air quality
Nan Ma et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2021)
A Random Forest Classification Algorithm Based Personal Thermal Sensation Model for Personalized Conditioning System in Office Buildings
Qing Yun Li et al.
COMPUTER JOURNAL (2021)
Regression forecasting of 'neutral' adaptive thermal comfort: A field study investigation in the south-eastern Mediterranean climate of Cyprus
B. Ozarisoy et al.
BUILDING AND ENVIRONMENT (2021)
Study on an adaptive thermal comfort model with K-nearest-neighbors (KNN) algorithm
Lei Xiong et al.
BUILDING AND ENVIRONMENT (2021)
Smart monitoring technologies for personal thermal comfort: A review
Ana Culic et al.
JOURNAL OF CLEANER PRODUCTION (2021)
Practical issues in implementing machine-learning models for building energy efficiency: Moving beyond obstacles
Zeyu Wang et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2021)
Nudging the adaptive thermal comfort model
Thomas Parkinson et al.
ENERGY AND BUILDINGS (2020)
Data-driven thermal comfort model via support vector machine algorithms: Insights from ASHRAE RP-884 database
Xiang Zhou et al.
ENERGY AND BUILDINGS (2020)
Comparing machine learning algorithms in predicting thermal sensation using ASHRAE Comfort Database II
Maohui Luo et al.
ENERGY AND BUILDINGS (2020)
Review on occupant-centric thermal comfort sensing, predicting, and controlling
Jiaqing Xie et al.
ENERGY AND BUILDINGS (2020)
Thermal comfort modeling when personalized comfort systems are in use: Comparison of sensing and learning methods
Ashrant Aryal et al.
BUILDING AND ENVIRONMENT (2020)
On hyperparameter optimization of machine learning algorithms: Theory and practice
Li Yang et al.
NEUROCOMPUTING (2020)
Data-driven simulation of a thermal comfort-based temperature set-point control with ASHRAE RP884
Siliang Lu et al.
BUILDING AND ENVIRONMENT (2019)
Thermal Comfort-Based Personalized Models with Non-Intrusive Sensing Technique in Office Buildings
Siliang Lu et al.
APPLIED SCIENCES-BASEL (2019)
Tuning machine learning models for prediction of building energy loads
Saleh Seyedzadeh et al.
SUSTAINABLE CITIES AND SOCIETY (2019)
Personal thermal comfort models with wearable sensors
Shichao Liu et al.
BUILDING AND ENVIRONMENT (2019)
Machine learning method for real-time non-invasive prediction of individual thermal preference in transient conditions
Andrei Claudiu Cosma et al.
BUILDING AND ENVIRONMENT (2019)
Random forest based thermal comfort prediction from gender-specific physiological parameters using wearable sensing technology
Tanaya Chaudhuri et al.
ENERGY AND BUILDINGS (2018)
Present and future Koppen-Geiger climate classification maps at 1-km resolution
Hylke E. Beck et al.
SCIENTIFIC DATA (2018)
Challenging the assumptions for thermal sensation scales
Marcel Schweiker et al.
BUILDING RESEARCH AND INFORMATION (2017)
Modeling of Gender Differences in Thermoregulation
Anthony E. Iyoho et al.
MILITARY MEDICINE (2017)
Field study on adaptive thermal comfort in mixed mode office buildings in southwestern area of Spain
Elena Barbadilla-Martin et al.
BUILDING AND ENVIRONMENT (2017)
Modelling personal thermal sensations using C-Support Vector Classification (C-SVC) algorithm
Lai Jiang et al.
BUILDING AND ENVIRONMENT (2016)
Support vector machines in engineering: an overview
S. Salcedo-Sanz et al.
WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY (2014)
Decision trees: a recent overview
S. B. Kotsiantis
ARTIFICIAL INTELLIGENCE REVIEW (2013)
Updating the adaptive relation between climate and comfort indoors; new insights and an extended database
M. A. Humphreys et al.
BUILDING AND ENVIRONMENT (2013)
Derivation of the adaptive equations for thermal comfort in free-running buildings in European standard EN15251
Fergus Nicol et al.
BUILDING AND ENVIRONMENT (2010)
World map of the Koppen-Geiger climate classification updated
Markus Kottek et al.
METEOROLOGISCHE ZEITSCHRIFT (2006)
Exploring conditions for the optimality of Naive bayes
H Zhang
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE (2005)
Adaptive thermal comfort and sustainable thermal standards for buildings
JF Nicol et al.
ENERGY AND BUILDINGS (2002)