Construction site noise is the most significant cause of noise disputes in South Korea. We conducted an annoyance evaluation to produce annoyance prediction models for four kinds of construction noise that cause the most complaints, namely construction machinery noise from pile drivers, excavators, and concrete pumping vehicles and noise from concrete mold removal working. We adjusted these four noises recorded at construction sites to noise stimuli with 35–80 dB(A), and subjects evaluated annoyance with a score for these stimuli. Participants in the experiment listened to one or two noises at the same time and evaluated their annoyance. We created multiple linear regression models and logistic regression models for annoyance scores of the subjects using acoustic features of noise stimuli and personal and situational variables. Acoustic features included traditional indicators such as L_eq, L_max, and sound quality indices. We calculated mean, maximum, and percentile values of sound quality indices such as loudness, sharpness, roughness, and fluctuation strength. The personal variables were results from a demographic survey and attitudes toward noise, while the situational variables were results from a survey on the living environment and past experiences about noise. Also, we considered the health condition and residence environment of the subjects. Using multiple linear regression, we confirmed that the acoustic features and personal and situational variables influence annoyance from construction noise. Also, we calculated the importance of each variable to the annoyance. Finally, to confirm that the percentage of highly annoyed persons (%HA) varies with personal and situational variables, we classified subjects in accordance with the variables and created a %HA curve for each group. From the result, we confirmed that there is a large difference in %HA in accordance with the health condition of the subjects.

建筑工地噪音是韩国引起噪音纠纷的最重要原因。我们对4种投诉最多的施工噪声，即打桩机、挖掘机和混凝土泵送车辆的工程机械噪声和混凝土脱模工作的噪声，进行了烦扰度评估，生成了四种施工噪声的烦扰度预测模型。我们将在建筑工地记录的这四种噪音调整为 35–80 dB(A) 的噪音刺激，受试者用这些刺激的分数来评估烦恼。实验参与者同时听一两个噪音并评估他们的烦恼。我们使用噪声刺激的声学特征以及个人和情境变量为受试者的烦恼分数创建了多元线性回归模型和逻辑回归模型。_方程, _Lmax，以及音质指标。我们计算了响度、锐度、粗糙度和波动强度等声音质量指标的平均值、最大值和百分位值。个人变量来自人口调查和对噪音的态度，而情境变量来自对生活环境和过去噪音经历的调查。此外，我们还考虑了受试者的健康状况和居住环境。使用多元线性回归，我们确认了声学特征以及个人和情境变量会影响建筑噪音的烦恼。此外，我们计算了每个变量对烦恼的重要性。最后，为了确认高度恼怒者的百分比 (%HA) 随个人和情境变量而变化，我们根据变量对受试者进行分类，并为每组创建了 %HA 曲线。从结果中我们确认，根据受试者的健康状况，%HA 存在很大差异。