| 摘要: |
| 室内环境质量（IEQ）是影响建筑
使用者舒适度与健康的关键因素，其综合评
价需要统筹热、光、声环境及空气品质等多
维指标。现有研究多采用固定权重模型，难
以反映环境因素动态变化的非线性特征。为
解决传统模型中权重静态化的问题，本研究
提出一种基于变权理论的动态权重评价方
法，旨在建立更符合实际感知的IEQ 评估体
系。通过覆盖寒冷地区多类建筑的大规模主
客观调研，构建1 468 份样本数据库；引入
变权理论构建动态权重函数，结合惩罚型变
权机制处理极端环境条件；通过50 种不同环
境条件下的实验验证模型有效性。验证表
明，这一新模型较传统常权方法更贴近实际
用户投票结果，能显著提升极端环境下的评
估精度，揭示单一环境因素权重随其舒适度
变化的非线性规律。 |
| 关键词: 室内环境质量 综合舒适度 室内
环境质量模型 变权模型 动态权重 |
| DOI：10.13791/j.cnki.hsfwest.20240522001 |
| 分类号: |
| 基金项目:山东省自然科学基金青年科学基金项目（ZR2023QE340） |
|
| A dynamic weight assessment model for Indoor Environmental Quality (IEQ) |
|
ZHOU Hanyu,XU Yabing,ZHAO Pengwen,WANG Lixiong,LIU Gang
|
| Abstract: |
| This study develops an advanced dynamic weighting evaluation model for Indoor
Environmental Quality (IEQ) assessment that addresses the critical limitations of conventional fixedweight
approaches. Indoor environmental quality, encompassing thermal, visual, acoustic
environments and indoor air quality, plays a pivotal role in occupant comfort and well-being.
Traditional IEQ evaluation models have predominantly relied on static weighting schemes that fail to
capture the dynamic interactions between environmental factors and their varying influence on overall
comfort perception under different conditions. The research is initiated to overcome the recognized
shortcomings of existing evaluation methods that cannot adequately represent the nonlinear
relationships between individual IEQ factors and overall comfort. While numerous studies have
attempted to develop reliable IEQ weight models, most maintain fixed weights for each
environmental parameter regardless of actual conditions. This conventional approach proves
insufficient as substantial evidence demonstrates that the relative importance of different factors
changes significantly depending on environmental states, particularly when certain parameters reach
extreme or uncomfortable levels. Our comprehensive methodology combines extensive field
investigations with sophisticated mathematical modeling techniques. The research team conducted
thorough subjective and objective surveys across various building types in cold climate regions,
establishing a robust database of 1 468 samples. This carefully compiled database captures detailed
occupant responses to diverse environmental conditions, providing the essential foundation for model
development. The study employed standardized CBE occupant survey protocols to ensure data
consistency and reliability throughout the research process.The core innovation of this study lies in its
novel application of variable-weight theory to IEQ assessment. The proposed dynamic weighting
model represents a significant advancement through several key features. It establishes statedependent
weighting functions that automatically adjust factor importance based on real-time
environmental conditions. The model incorporates specialized penalty-type variable-weight
mechanisms that specifically address extreme discomfort scenarios, and develops a systematic
approach for determining critical thresholds and tuning parameters through empirical data analysis.
Rigorous model validation is conducted through carefully designed experiments under 50 distinct
environmental conditions, systematically varying temperature, illumination, noise levels and CO2
concentrations. These controlled experiments spanned the complete spectrum from optimal comfort
conditions to severely compromised IEQ states, generating comprehensive performance evaluation
data. The validation process included detailed comparisons between the dynamic model’s predictions,
traditional constant-weight model outputs, and actual occupant voting results. The research findings
demonstrate several important outcomes. The dynamic weighting model shows marked improvement
in evaluation accuracy, particularly in extreme environmental conditions where traditional models
typically fail. The study reveals clear nonlinear relationships between individual factor weights andtheir respective comfort levels, such as the substantial increase in thermal environment weight when temperatures fall outside comfort ranges. The model
successfully identifies critical thresholds where specific parameters become disproportionately influential on overall satisfaction. Comparative analysis
confirms that the dynamic model’s predictions align much more closely with actual occupant voting patterns than conventional approaches. This research
makes substantial theoretical contributions to building science by providing empirical evidence supporting the nonlinear nature of comfort perception in built
environments. It develops a comprehensive mathematical framework for implementing variable-weight theory in IEQ assessment and establishes
methodological standards for integrating large-scale occupant surveys with mathematical modeling. The study significantly advances our understanding of how
different IEQ factors interact under varying conditions, offering new insights into environmental comfort dynamics.The practical applications of this research
hold considerable importance for both building design and operation. Design professionals can utilize the model to optimize environmental systems by
identifying priority parameters under specific conditions. Facility managers gain a sophisticated diagnostic tool for addressing comfort issues in occupied
buildings. The model supports more nuanced energy efficiency strategies by identifying when environmental parameters can be adjusted without significantly
impacting comfort. Additionally, it provides a robust framework for post-occupancy evaluation and building performance assessment.Future research directions
identified by this study include extending the model to different climate zones and building types, investigating potential cross-cultural differences in comfort
perception, integrating with smart building technologies for real-time IEQ optimization, and exploring additional environmental parameters that may influence
comfort. These avenues promise to further enhance our understanding and management of indoor environmental quality.This research represents a fundamental
shift in IEQ assessment methodology, moving from static, linear models to dynamic systems that better reflect the complex reality of human comfort
perception. By successfully bridging mathematical modeling techniques with architectural science, it opens new possibilities for data-driven, human-centric
building design that can simultaneously enhance occupant well-being and promote sustainable resource use. The model’s robust validation and practical
applicability make it particularly valuable in contemporary architectural practice and research, where both human health and environmental responsibility are
increasingly prioritized. The study establishes a new standard for IEQ assessment frameworks that more accurately capture the dynamic nature of humanenvironment
interactions in built spaces. |
| Key words: Indoor Environmental Quality (IEQ) occupant overall satisfaction IEQ model variable-weight model dynamic weighting |
