According to the characteristics of exploration in oil and gas bearing basins , the author designed the model of multi - scheme decision - making of exploration in oil and gas bearing basins with the method of monte carlo and finished the concrete content of model by c + + builder 5 . the paper described the whole procedure of simulation and gained the probability of net cash flow , accumulative net cash flow and financial net cash . the author compared the first exploration scheme with others and revised the result by the method of analytical hierarchy process 以羌塘盆地为实际算例，具体描述了模拟的整个过程，得到了各年净现金流量，累计净现金流量，财务净现值等经济决策指标的概率分布函数和累计概率分布函数，并对羌塘盆地的三个大规模勘探方案作了比较，使用层次分析法对比较结果作了修正。
It is desirable for all related insiders and outsiders to discern all potential risk in advance . this paper , with the adoption of special treatment resulted from abnormal financial position as the indicator of financial distress , the univariate variable analysis and multiple variable analysis as the research approach and some financial ratios as variable , tries to find an optimal financial distress prediction model of chinese manufacturing listed companies based on public accounting data . our finding demonstrate that five general financial ratios and three ratios concerning the cash flow have better predicting ability , the erroneous classification ratio are low . these five general financial ratios are earning per share , return on net assets , return on gross assets , growth rate of net profits , growth rate of net assets ; the three ratios concerning the cash flow are net cash flows from operating activities per share , net re - earnable cash flows / current liability , net cash flows from operating activities / net profit 研究结果表明，在单变量分析中，每股收益、净资产收益率、总资产报酬率、净利润增长率、净资产增长率这5个财务比率的错分率较低、预测能力较强；经营活动净现金流量与净利润之比、每股经营现金流量、可重复赚取的现金净流量与流动负债之比这三个现金流量财务比率对于预测上市公司财务困境具有有效性；多变量分析中，应用费雪判别分析和典则判别分析得到两个判别模型，在典则判别分析中，应用两种方法确定所建模型的最佳分界点，检测证明应用所得两个判别模型进行财务困境预测的准确率很高。
Based on the summary of previous evaluation methods , this paper points out the shortcomings of them , then draw the theory of artificial neural network into risk evaluation , through an example of some kind of investment project and the training and examination of a group investigation sample , it sets up the artificial neural network model . at last , this model is applied to the real case of an engineering project to evaluate its risk level and satisfactory result is made ; in the fifth chapter of this paper , the main risk factors that affect the economic appraisal of the engineering investment project are described through the form of relationship chart . then it is proved by way of deduction of formula that the risky influence that is brought by inflation must be considered in the engineering investment project 本文在对以往评价方法进行归纳总结的基础上，指出其中存在的不足之处，将人工神经网络理论引入到风险评价中，以某一类投资项目为例，通过对一组调查样本的训练和检测，建立了工程投资项目风险评价的人工神经网络模型，并通过实例对模型进行了验证，取得了满意结果；在本文第五部分，对影响工程投资项目经济评价的主要风险因素以关系图的形式进行了描述，然后通过公式推导证明了在工程投资项目中应该考虑通货膨胀带来的风险影响，接着在分析以往建立的经济评价净现金流量表达式存在不足的基础上提出了另外一种方式的表达式，即净现值解析模型，对该模型的求解进行了详细的说明，并分析了如何恰当的选择各风险变量的概率分布，最后在考虑投资者风险偏好的前提下，提出了工程投资项目新的风险度量模型。
