计算机科学 ›› 2022, Vol. 49 ›› Issue (6A): 667-674.doi: 10.11896/jsjkx.210800088
朱旭辉, 沈国娇, 夏平凡, 倪志伟
ZHU Xu-hui, SHEN Guo-jiao, XIA Ping-fan, NI Zhi-wei
摘要： 政府和社会资本合作(PPP) 项目能够完善基础设施建设、保障民生与促进经济发展,但也存在资金退出困难、建设周期长、参与主体多等缺陷,项目运营失败将直接损害各方投资者的收益,造成社会资源的浪费,故亟需对PPP融资风险进行科学、准确地预测。文中提出一种基于螺旋进化萤火虫算法(SEGSO) 和BP神经网络(BPNN) 的预测模型,并将其应用于PPP融资模式风险预测。首先采用佳点集理论进行种群初始化,引入交互机制、精英种群策略以及螺旋进化方式,提出螺旋进化萤火虫算法。然后运用SEGSO算法进行参数寻优,搜索BPNN的最优参数组合,构建基于SEGSO和BPNN的预测模型SEGSO-BPNN。最后在5个测试函数上验证了SEGSO算法的性能优势,在7个UCI标准数据集上的实验结果表明了所提模型的显著性和有效性。将所提模型应用于中国PPP项目的风险预测,取得了较好的效果,为PPP融资风险预测提供了一种新方法。
中图分类号:
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