基于麻雀搜索算法优化支持向量回归的装配式建筑施工安全投入优化

为提高装配式建筑施工安全水平，减少社会经济损失，对施工安全资源投入的合理分配进行研究。选取20组装配式建筑施工安全投入与事故经济损失数据作为样本，通过基于麻雀搜索算法优化的支持向量回归模型对样本进行非线性拟合，以事故经济损失最小化为目标函数，安全投入资源为约束条件，构建安全投入优化模型。以某装配式建设项目为例进行实证分析，结果表明:基于麻雀搜索算法-支持向量回归的施工安全投入优化方法能有效降低安全事故损失、节约投入资金，具有良好的优化效果，可为装配式建筑施工安全投入决策提供科学有效的依据。

Optimization of safety investment in prefabricated building construction based on sparrow search algorithm optimized support vector regression

In order to improve the safety level of the prefabricated building construction process and reduce the casualties and economic losses caused by construction safety accidents, a study was conducted on how to make a reasonable allocation of construction safety resources. Firstly, the data of safety resources invested and accident economic losses due to accidents in the construction process of 20 completed prefabricated building construction projects were selected as samples. Secondly, the Sparrow Search Algorithm (SSA) was used to find the optimal parameters of the Support Vector Regression (SVR) model, and the SSA-SVR model was used to fit the data samples nonlinearly. Thirdly, the accident economic loss minimization was taken as the objective and the safety investment resources were taken as the constraints to construct the safety investment optimization model. Finally, a case study was done with an assembly construction project to verify the feasibility of the model. The research results prove that the construction safety investment optimization method based on SSA-SVR can effectively reduce the loss of safety accidents during the construction of prefabricated buildings and the capital invested by construction companies. And this model has a good safety investment optimization effect ,it can provide a scientific and effective basis for the safety investment decision of prefabricated building construction.