Investigation of temperature extremes is very important as one of the most important climate parameters in different parts. If exposed to enough heat, humans will suffer from extreme heat. Maximum temperature and heat can adversely affect many living organisms. The effects of extreme heat on people with chronic lung disease, including asthma and emphysema, are greater; even for people with healthy lungs, outdoor activities are not recommended during high ozone levels. The purpose of this study is to monitor and analyze the effects of atmospheric temperature extreme and extreme heat on human health in Central Iran. Therefore, the minimum and maximum data of 15 synoptic stations in the study area for the period (1988–2018) using hybrid artificial neural network (HANN) and adaptive neuro-fuzzy inference system (ANFIS) models were used. Finally, multi-criteria decision-making (MCDM) models TOSIS and SAW were used to prioritize the areas exposed to rising temperature. The results showed that according to ANFIS modelling for predicting extreme temperatures, the lowest mean training error and the mean error of validation for the minimum temperature were equal to 0.10 for the Yazd Station and 1.66% for the Damghan station. The lowest mean training error and the mean error of validation for the maximum extreme temperature obtained 0.016 for the Garmsar station and 9.39% for the Shahroud station. The maximum extreme temperature of two stations of Garmsar and Bafgh (1 and 0.9689, respectively) was more exposed to extreme temperatures based on the TOPSIS model. Garmsar and Salafchegan Stations (1 and 0.9873, respectively) were more exposed to extreme temperatures based on the SAW model. Climate change is fundamentally changing the Earth’s climate system in a way that directly and indirectly endangers human physical and mental health. Severe increase in temperature is directly associated with death from cardiovascular and respiratory diseases, especially in the elderly. Also in the study area, the house is a place for peace and comfort for every human being. Climatic and weather conditions have a direct impact on creating a sense of comfort in any architectural space. Proper heating and air conditioning in the interior of the building is another case of architecture that will not be easy because this architectural issue is related to the comfort or non-comfort of man, and the concepts of heat or cold are mostly due to the natural feeling of man and his physiological conditions. The rising trend of thermal stresses in the studied stations increases the need to pay attention to the issue of thermal stresses and the spread of diseases (heat attack, syncope, and muscle cramps) in terms of crisis planning and management.

中文翻译：

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西南亚伊朗中部大气温度和极端高温环境对人类健康影响的监测与分析

作为不同地区最重要的气候参数之一，极端温度的调查非常重要。如果暴露在足够的热量下，人类将遭受极端高温。最高温度和热量会对许多生物体产生不利影响。极端高温对哮喘和肺气肿等慢性肺病患者的影响更大；即使对于肺部健康的人，也不建议在高臭氧水平期间进行户外活动。本研究的目的是监测和分析伊朗中部大气温度极端和极端高温对人类健康的影响。因此，使用混合人工神经网络（HANN）和自适应神经模糊推理系统（ANFIS）模型的研究区15个天气站在1988-2018年期间的最小和最大数据。最后，多标准决策 (MCDM) 模型 TOSIS 和 SAW 用于优先考虑暴露于温度升高的区域。结果表明，根据预测极端温度的ANFIS模型，亚兹德站的最低平均训练误差和最低温度验证的平均误差分别为0.10和1.66%。Garmsar 站的最低平均训练误差和最大极端温度验证的平均误差为 0.016，Shahroud 站为 9.39%。根据 TOPSIS 模型，Garmsar 和 Bafgh 两个站的最高极端温度（分别为 1 和 0.9689）更易暴露于极端温度。根据 SAW 模型，Garmsar 和 Salafchegan 站（分别为 1 和 0.9873）更容易暴露在极端温度下。气候变化正在以一种直接或间接危害人类身心健康的方式从根本上改变地球的气候系统。温度的严重升高与心血管和呼吸系统疾病的死亡直接相关，尤其是老年人。同样在学习区，房子是每个人和平与舒适的地方。气候和天气条件对在任何建筑空间中营造舒适感都有直接影响。建筑物内部适当的暖气和空调是另一种不容易的建筑案例，因为这个建筑问题与人的舒适或不舒适有关，而冷热的概念大多是由于自然人的感觉和他的生理状况。