| 1. | After this digression we return now to our original problem .
在这一段插话以后，现在回到原来的问题。 |
| 2. | For any approximation to be valid it must provide a result that is in some sense close to the solution of the original problem .
任何有效的近似式必须在某种意义上提供一个接近于原问题解的结果。 |
| 3. | Let s address your original problem first
首先让我们解决您原始的问题。 |
| 4. | Quite often the original problem and how it can be resolved
初始的问题往往只是一个更大问题的表象，也可能根本不是问题。 |
| 5. | Original problem statement
原始问题陈述 |
| 6. | The original problem still exists , but the client gets a better result
原来的问题继续存在，但是我们可以得到一个更好的结果。 |
| 7. | The original problem statement did cover security issues , but not in a way that s workable
原始的问题陈述的确涉及到安全性问题，但用的方式并不奏效。 |
| 8. | In general , a computed solution obtained by numerical methods is a approximate solution of the original problem
用数值方法求解实际问题，得到的计算解一般是原问题的近似解。 |
| 9. | The efficacy coefficient method is used to formulate an evaluation function that covers all objective functions of the original problem
对于多目标规划，采用功效系数法建立目标评价函数。 |
| 10. | Then we can reduce the original problem to a boundary value problem defined on the bounded computational domain
这样我们可以将原无界区域上的定解问题约化为定义在有界计算区域上的边值问题。 |
