In order to realize the financial benefit evaluation of the investment project, the investment project of power transmission and transformation of a power grid enterprise in Sichuan province is taken as an example. First, the overall cost of the investment project is analyzed and introduced, and the sales revenue, running costs, taxes and surcharges in the four years from 2016 to 2019 are calculated, and the financial benefit evaluation index and calculation method are determined. Then, the Fuzzy optimal back propagation neural network (BPNN) is constructed based on BPNN and fuzzy optimization strategy for cost–benefit analysis. Then an improved Gravitational search algorithm (IGSA) algorithm based on GSA algorithm is proposed applied to the optimization of fuzzy optimal BPNN. Finally, the influence of some uncertainty factors on the financial benefit of investment project is measured through break-even analysis and sensitivity analysis. The results show that the operation index of the substation is stable and the electricity sold shows an increasing trend after its operation. The financial situation of the investment project is optimistic with high economic benefits. The internal rate of return of the capital can reach 17.13%, and the payback period of the investment is less than 7 years. The sensitivity of the internal rate of return of project investment from high to low is unit price of electricity sold, electricity sold and operation cost. The output value of the samples trained by the fuzzy optimal BPNN is close to the expected value, with a small error of about 0.3% at most, and the training speed is fast and the training effect is good. The actual output result of the financial evaluation index is basically consistent with the expected output result of the expert survey, with a small error. Moreover, the application of the model to other similar investment projects still has good financial benefit evaluation results and good generalization ability. In conclusion, BPNN can be used to calculate the cost and benefit and predict the financial benefit of investment projects. According to the forecast results, a feasible investment scheme is proposed, which can be used for reference in the financial benefit evaluation of similar investment projects.

为了实现投资项目的财务效益评价，以四川某电网企业输变电投资项目为例。首先，对投资项目的总体成本进行分析和介绍，计算出2016年至2019年这四年的销售收入，运行成本，税金及附加，确定财务效益评价指标和计算方法。然后，基于BPNN和模糊优化策略，构建了模糊最优反向传播神经网络（BPNN），进行了成本效益分析。然后，提出了一种基于GSA算法的改进引力搜索算法（IGSA），将其应用于模糊最优BPNN的优化。最后，通过盈亏平衡分析和敏感性分析来衡量一些不确定因素对投资项目财务收益的影响。结果表明，变电站运行指标稳定，运行后售电量呈上升趋势。投资项目财务状况乐观，经济效益高。资金内部收益率可达17.13％，投资回收期不到7年。项目投资内部收益率从高到低的敏感度是售电单价，售电和运营成本。由模糊最优BPNN训练的样本的输出值接近预期值，最大误差约为0.3％，训练速度快，训练效果好。财务评价指标的实际输出结果与专家调查的预期输出结果基本一致，误差很小。而且，该模型在其他类似投资项目中的应用仍然具有良好的财务效益评价结果和良好的归纳能力。总之，BPNN可用于计算成本和收益并预测投资项目的财务收益。根据预测结果，提出了一种可行的投资方案，可供类似投资项目的财务效益评价参考。而且，该模型在其他类似投资项目中的应用仍然具有良好的财务效益评价结果和良好的归纳能力。总之，BPNN可用于计算成本和收益并预测投资项目的财务收益。根据预测结果，提出了一种可行的投资方案，可供类似投资项目的财务效益评价参考。而且，该模型在其他类似投资项目中的应用仍然具有良好的财务效益评价结果和良好的归纳能力。总之，BPNN可用于计算成本和收益并预测投资项目的财务收益。根据预测结果，提出了一种可行的投资方案，可供类似投资项目的财务效益评价参考。