accumulate error

简明释义

1. 积累误差; 2. 聚集误差; 3. 总偏差;

英英释义

例句

1.The GPS system can accumulate error 累积误差 over time if not calibrated regularly.

如果不定期校准，GPS系统可能会随着时间的推移而累积误差.

2.When performing repeated calculations, it's important to check for accumulate error 累积误差 in your results.

在进行重复计算时，检查结果中的累积误差是很重要的.

3.In robotics, accumulate error 累积误差 can affect the precision of movements over time.

在机器人技术中，累积误差会影响运动的精确度.

4.Scientists must account for accumulate error 累积误差 when analyzing experimental data.

科学家在分析实验数据时必须考虑到累积误差.

5.In long-term measurements, even small inaccuracies can lead to significant accumulate error 累积误差.

在长期测量中，即使是小的误差也会导致显著的累积误差.

作文

In the world of science and engineering, precision is paramount. Every calculation, measurement, and experiment relies on accuracy to yield reliable results. However, one of the most significant challenges faced in these fields is the phenomenon known as accumulate error. This term refers to the gradual build-up of errors that can occur during calculations or measurements over time. Understanding how accumulate error works is essential for anyone involved in research, data analysis, or any field that requires precision.When conducting experiments, researchers often take multiple measurements to ensure accuracy. Each measurement, however, carries a certain degree of uncertainty. For instance, if a scientist measures the temperature of a substance several times, each reading might slightly differ due to factors such as instrument calibration, environmental conditions, or human error. As these small discrepancies add up, they can lead to a significant deviation from the true value, which is where accumulate error becomes critical.One common example of accumulate error can be seen in the field of navigation. When pilots or sailors chart a course, they rely on various instruments to guide them. If each instrument has a minor error, those errors can accumulate over the distance traveled, leading to a substantial miscalculation of their position. This is why navigators must regularly recalibrate their instruments and verify their positions to minimize the impact of accumulate error.In mathematics, accumulate error is particularly relevant in numerical methods used to solve equations. When approximating solutions, each step in the calculation can introduce a small error. If these errors are not adequately managed, they can compound, resulting in a final solution that is far from accurate. Therefore, mathematicians and engineers must employ techniques such as error analysis and correction algorithms to mitigate the effects of accumulate error.Moreover, in the realm of computer science, accumulate error can manifest in algorithms that process large datasets. When data is aggregated from various sources, inconsistencies can arise due to differences in data collection methods or formats. As this data is processed, the errors can accumulate, leading to skewed results. Data scientists must implement rigorous validation and cleaning processes to address potential accumulate error before drawing conclusions from their analyses.To combat accumulate error, it is crucial to adopt best practices in measurement and calculation. This includes using high-quality instruments, regularly calibrating equipment, and applying statistical methods to assess and mitigate errors. Additionally, maintaining detailed records of measurements and calculations can help identify patterns of error that may need addressing.In conclusion, accumulate error is a pervasive issue across various fields, from scientific research to engineering and data analysis. Recognizing its impact and implementing strategies to minimize its effects is vital for achieving accurate and reliable results. By understanding the nature of accumulate error and taking proactive measures, professionals can enhance the integrity of their work and contribute to the advancement of knowledge in their respective domains.

在科学和工程的世界中，精确性至关重要。每一个计算、测量和实验都依赖于准确性，以产生可靠的结果。然而，这些领域面临的最大挑战之一是被称为累积误差的现象。这个术语指的是在计算或测量过程中，随着时间的推移而逐渐积累的错误。理解累积误差的工作原理对任何参与研究、数据分析或任何需要精确性的领域的人来说都是至关重要的。在进行实验时，研究人员通常会进行多次测量以确保准确性。然而，每次测量都带有一定程度的不确定性。例如，如果科学家对某种物质的温度进行多次测量，每次读数可能会因仪器校准、环境条件或人为错误等因素而略有不同。当这些小差异累加时，它们可能导致与真实值的显著偏差，这就是累积误差变得至关重要的地方。累积误差的一个常见例子可以在导航领域看到。当飞行员或水手绘制航线时，他们依赖各种仪器来引导他们。如果每个仪器都有轻微的误差，这些误差可能会在行驶的距离上累积，从而导致位置的重大错误计算。这就是为什么导航员必须定期重新校准他们的仪器并验证他们的位置，以最小化累积误差的影响。在数学中，累积误差在用于求解方程的数值方法中特别相关。当近似解时，计算中的每一步都可能引入小错误。如果这些错误没有得到妥善管理，它们可能会累积，导致最终解远离准确。因此，数学家和工程师必须采用诸如误差分析和修正算法等技术来减轻累积误差的影响。此外，在计算机科学领域，累积误差可以在处理大型数据集的算法中表现出来。当数据从各种来源聚合时，由于数据收集方法或格式的差异，可能会出现不一致性。当这些数据被处理时，错误可能会累积，导致结果失真。数据科学家必须实施严格的验证和清理过程，以解决在分析中可能出现的累积误差。为了应对累积误差，采取最佳的测量和计算实践至关重要。这包括使用高质量的仪器、定期校准设备以及应用统计方法来评估和减轻错误。此外，保持详细的测量和计算记录可以帮助识别可能需要解决的错误模式。总之，累积误差是各个领域普遍存在的问题，从科学研究到工程和数据分析。认识到其影响并实施减少其影响的策略对于实现准确和可靠的结果至关重要。通过理解累积误差的性质并采取主动措施，专业人士可以增强他们工作的完整性，并为各自领域的知识进步做出贡献。