point by-point computation

简明释义

逐点计算

英英释义

例句

1.During the training phase, point by-point computation is crucial for optimizing the neural network parameters.

在训练阶段，逐点计算对优化神经网络参数至关重要。

2.In image processing, point by-point computation helps in enhancing the quality of each pixel individually.

在图像处理过程中，逐点计算有助于单独增强每个像素的质量。

3.For this simulation, we will perform a point by-point computation to analyze the data thoroughly.

对于这个模拟，我们将进行逐点计算以彻底分析数据。

4.The algorithm requires a point by-point computation to ensure accuracy in the results.

该算法需要进行逐点计算以确保结果的准确性。

5.The software uses point by-point computation to generate accurate 3D models from 2D images.

该软件使用逐点计算从二维图像生成准确的三维模型。

作文

In the realm of mathematics and computer science, the term point by-point computation refers to a method of analyzing or processing data where each point is considered individually. This technique is particularly useful in situations where data sets are large and complex, allowing for a more granular approach to problem-solving. By focusing on each point separately, researchers and analysts can identify patterns, anomalies, and relationships that may not be visible when looking at the data as a whole.For instance, when evaluating the performance of a machine learning model, practitioners often employ point by-point computation to assess how well the model predicts outcomes for each individual data point. This allows them to pinpoint specific areas where the model excels or falters, leading to more informed adjustments and improvements. In essence, this method transforms the analysis from a broad overview into a detailed examination, enhancing the overall understanding of the system being studied.Moreover, point by-point computation can be applied in various fields beyond mathematics and computer science. In the field of economics, for example, analysts might use this approach to evaluate the impact of policy changes on different segments of the population. By examining each demographic group separately, they can gain insights into how different individuals or communities are affected, which can inform more effective policy-making.Similarly, in environmental science, researchers often utilize point by-point computation to analyze ecological data. By assessing the health of individual species or habitats, scientists can better understand the complexities of ecosystems and devise strategies for conservation. This level of detail is crucial when addressing issues such as climate change, where the effects can vary significantly across different regions and populations.The advantages of point by-point computation are clear; however, it is essential to recognize its limitations as well. The primary challenge lies in the volume of data that must be processed. When dealing with extensive datasets, the computational resources required can be significant, potentially leading to longer processing times and increased costs. Therefore, while this method provides valuable insights, it is vital to balance the depth of analysis with practical considerations regarding time and resources.In conclusion, point by-point computation is a powerful analytical tool that offers a detailed perspective on data. By examining each data point individually, researchers and practitioners can uncover insights that drive better decision-making across various fields. However, it is crucial to remain mindful of the challenges associated with this method, ensuring that it is implemented effectively and efficiently. As technology continues to advance, the potential for point by-point computation to revolutionize data analysis and enhance our understanding of complex systems only grows, paving the way for innovative solutions to contemporary problems.

在数学和计算机科学领域，术语逐点计算指的是一种分析或处理数据的方法，其中每个点都被单独考虑。这种技术在数据集庞大且复杂的情况下特别有用，允许以更细致的方式解决问题。通过分别关注每个点，研究人员和分析师可以识别模式、异常和关系，这些在整体数据中可能不可见。例如，在评估机器学习模型的性能时，从业人员通常采用逐点计算来评估模型对每个单独数据点的预测效果。这使他们能够准确找出模型表现优秀或欠佳的特定领域，从而进行更有根据的调整和改进。实际上，这种方法将分析从广泛的概述转变为详细的检查，增强了对所研究系统的整体理解。此外，逐点计算也可以应用于数学和计算机科学以外的多个领域。例如，在经济学领域，分析师可能会使用这种方法来评估政策变化对不同人群的影响。通过分别检查每个群体，他们可以深入了解不同个人或社区受到的影响，从而制定更有效的政策。同样，在环境科学中，研究人员经常利用逐点计算来分析生态数据。通过评估个别物种或栖息地的健康状况，科学家们可以更好地理解生态系统的复杂性，并制定保护策略。在应对气候变化等问题时，这种细致程度至关重要，因为其影响在不同地区和人群之间可能存在显著差异。逐点计算的优势显而易见；然而，认识到它的局限性也很重要。主要挑战在于必须处理的数据量。当处理庞大的数据集时，所需的计算资源可能相当可观，可能导致更长的处理时间和增加的成本。因此，尽管这种方法提供了宝贵的见解，但在时间和资源方面平衡分析的深度是至关重要的。总之，逐点计算是一种强大的分析工具，提供了对数据的详细视角。通过逐个检查每个数据点，研究人员和从业者能够揭示推动各个领域更好决策的见解。然而，务必注意与此方法相关的挑战，确保其有效和高效地实施。随着技术的不断进步，逐点计算在革新数据分析和增强我们对复杂系统理解的潜力只会不断增长，为当代问题的创新解决方案铺平道路。