Recognition and prediction of elderly thermal sensation based on outdoor facial skin temperature

Skills of Statistical Learning Algorithms in Thermal Stress Assessment Compared with the Expert Judgement Inherent to the Universal Thermal Climate Index (UTCI)

“…Our approach was to apply selected SL algorithms deeming representative for recent applications [5][6][7][8][9][10][11][35][36][37][38][39][40][41] to the data simulated by the UTCI-Fiala model [27] at stage 2 of the UTCI development (Figure 1).…”

“…Statistical or machine learning (SL) is central to artificial intelligence (AI) applications [1][2][3] with potential relevance to environmental risk assessment, especially in settings with high dimensional input as for thermal stress indices [4]. There, they may assist or even attempt replacing the biometeorological expert judgement, as indicated by the increasing number of recent application studies in this field [5][6][7][8][9][10][11].…”

Application of Statistical Learning Algorithms in Thermal Stress Assessment in Comparison with the Expert Judgment Inherent to the Universal Thermal Climate Index (UTCI)

“…Our approach was to apply selected SL algorithms deemed representative for recent applications [5][6][7][8][9][10][11][35][36][37][38][39][40][41] to the multi-dimensional data simulated over a comprehensive grid of relevant climatic conditions by the UTCI-Fiala model [27] at stage 2 of the UTCI development process (Figure 1).…”

“…Statistical or machine learning (SL) is central to artificial intelligence (AI) applications [1][2][3] with potential relevance to environmental risk assessment, especially in settings with high-dimensional input such as thermal stress indices [4]. There, they may assist or even attempt to replace the bio-meteorological expert judgment, as indicated by the increasing number of recent applications in diverse fields of biometeorology concerning, e.g., indoor and outdoor thermal comfort, the impact assessment of climate change-related heat stress, urban planning, the adaptation of buildings and human behavior to changing climatic conditions, or establishing a link between human physiology and thermal sensation [5][6][7][8][9][10][11]. The rising number of SL applications triggers a demand for quantitatively assessing the skills of statistical learning in comparison to results involving expert judgment.…”