美国数学建模MCM_ICM论文常用句式总结汇编 下载本文

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The expression of ... can be expanded as: ... ...的表达式可扩展为...

A is exponentially smaller than B, so it can be neglected. A对B来说呈指数级减小,所以可以忽略不计。 Equation (1) is reduced to: 方程(1)化简为:

Substitute the values into equation (3), we get ... 把这些值代入方程3,我们得到... According to our first assumption on Page 1, 根据我们第一页的第一个假设, Thus we arrive at the conclusion: 因此我们得到结论:

From the model of ... ,we find that theoretically, it is almost true that ... 由...模型,我们从理论上证明了... 是真实可信的。 That is the theoretical basis for ... in many application areas. 这是...在很多领域应用的理论基础。

To quantitatively analyze the different requirements of the two applications, we introduce two measures:

为了定量的分析这两种应用的不同要求,我们介绍来两个量度标准。 We give the criterion that ... 我们给出了...的判别标准 According to the criterion of... 根据...的标准

So its expression can be derived from equation (3) with small change. 所以它的表达式可以由方程3做微小改动而推出。 Suppose that ...refers to ... 假设...指的是...

We can get the distribution of... 我们可以得到...的分布 along x and y axes

沿着x和y轴

For a further discussion of this model, please see Appendix A. 参见附录A (detailed in Appendix I) (详见附录一)

... is fitted to the normal distribution,with the mean at 0 and variance of σ=1.342. ...符合均值为0,方差为1.342的正态分布。 conform to符合 Fig.4 shows ... 图4表明...

Thus, if ... is given, ...is determined. 因此,如果给定...,...就也确定了。 For a given r, we can calculate ... 对于给定的r, 我们可以算出... The two distributions are independent. 这两个分布是相互独立的。 By calculation we obtain... 通过计算,我们得到... So it is expressed as below: 所以它可以表示为: ... is ultimately determined by ... ... 最终由...决定

We fix A and examine the change of B with respect to C. 我们固定A然后观测B随C的变化。 the logarithm values of ... ...的对数值

That explains why the value of A decreases as B increases. 这就解释了为什么A的值随B的增加而减少。 If r increases, p(r) increases accordingly. 如果r增长,p(r)也相应地增长。 due to

由于

A is the length of ... in unit of ... A是...的长度,以...为单位。

We can see a \A=B.

我们可以看到在两个曲面之间有一个低谷,表示A=B的那些点。 A and B always change in opposite direction. A和B总是呈相反变化。

So when seeking the minimum of..., we should consider how to balance A and B. 所以当寻求...的最小值时,我们应该考虑如何平衡A和B。 So we set the optimal function as: 所以我们列出最优方程如下:

However, putting equal weight on A and B is not always desirable. 然而,给A和B相同的权数并不总是令人满意的。 In some situations, we must favor one over the other. 在一些情况下,我们必须偏重一方。 input the initialization 输入初值

The program solves the optimal function and output a,b,c and d. 程序求最优解,并输出a,b,c和d的值. In consideration of 考虑到...

We apply this strategy to four typical situations and list the results here. 我们将这种方案应用于四种典型情况,并列出结果如下。 the probability of occurrence 发生的概率

Theoretically, recognization can always be successful. 理论上说,识别应该总是成功的。 the expectation value of ...