principal dimension

简明释义

主要尺寸

英英释义

例句

1.The principal dimension 主要维度 of the project was its environmental impact assessment.

该项目的主要维度是其环境影响评估。

2.The principal dimension 主要维度 of our strategy is to enhance user experience through technology.

我们战略的主要维度是通过技术提升用户体验。

3.In our analysis, we identified the principal dimension 主要维度 of customer satisfaction as product quality.

在我们的分析中，我们确定客户满意度的主要维度是产品质量。

4.The study focused on the principal dimension 主要维度 of economic growth in developing countries.

这项研究聚焦于发展中国家经济增长的主要维度。

5.Researchers are investigating the principal dimension 主要维度 of social behavior in urban areas.

研究人员正在调查城市地区社会行为的主要维度。

作文

In the realm of science and mathematics, various concepts are often discussed to help us understand complex systems. One such term that frequently arises is principal dimension, which refers to the most significant aspect or factor within a multidimensional space that influences the behavior of a system. Understanding the principal dimension can be crucial in fields such as physics, engineering, and even social sciences, where multiple variables interact in intricate ways.For instance, consider a study on climate change. Researchers might analyze numerous factors such as temperature, carbon dioxide levels, and sea levels. Among these, the principal dimension could be identified as the increase in carbon dioxide levels, as it has a profound impact on global temperatures and weather patterns. By isolating this principal dimension, scientists can better predict future changes in climate and develop strategies for mitigation.Similarly, in the field of economics, understanding the principal dimension is vital for analyzing market trends. Economists often deal with a multitude of variables like consumer behavior, interest rates, and inflation. Identifying the principal dimension among these factors allows economists to focus their models on the most influential variables, leading to more accurate predictions and effective policymaking. For example, during a recession, the principal dimension might be the unemployment rate, as it directly affects consumer spending and overall economic health.Moreover, in the realm of data science, the concept of principal dimension plays a pivotal role in dimensionality reduction techniques such as Principal Component Analysis (PCA). This statistical method transforms a large set of variables into a smaller one while retaining most of the information. The principal dimension here represents the directions in which the data varies the most. By focusing on these dimensions, data scientists can simplify complex datasets, making them easier to analyze and visualize. This is particularly useful in fields like genetics, where researchers deal with thousands of variables representing different genes, and identifying the principal dimension can lead to significant discoveries about genetic diseases.In conclusion, the term principal dimension encapsulates the idea of focusing on the most critical factors within a complex system. Whether in climate science, economics, or data analysis, identifying the principal dimension allows researchers and professionals to streamline their efforts and achieve more meaningful results. By honing in on these key dimensions, we can enhance our understanding of intricate systems and make informed decisions based on solid evidence. As we continue to explore various scientific and analytical fields, the concept of principal dimension will undoubtedly remain a cornerstone of effective research and problem-solving strategies.

在科学和数学的领域中，常常会讨论各种概念以帮助我们理解复杂系统。其中一个经常出现的术语是主维度，它指的是在多维空间中影响系统行为的最重要的方面或因素。理解主维度在物理学、工程学甚至社会科学等领域中至关重要，因为这些领域中的多个变量以复杂的方式相互作用。例如，考虑对气候变化的研究。研究人员可能会分析许多因素，如温度、二氧化碳水平和海平面。在这些因素中，主维度可以被识别为二氧化碳水平的增加，因为它对全球温度和天气模式有深远的影响。通过孤立这个主维度，科学家可以更好地预测未来的气候变化，并制定减缓策略。同样，在经济学领域，理解主维度对分析市场趋势至关重要。经济学家通常处理众多变量，如消费者行为、利率和通货膨胀。识别这些因素中的主维度使经济学家能够将他们的模型集中在最具影响力的变量上，从而导致更准确的预测和有效的政策制定。例如，在经济衰退期间，主维度可能是失业率，因为它直接影响消费者支出和整体经济健康。此外，在数据科学领域，主维度的概念在降维技术（如主成分分析）中起着关键作用。这种统计方法将大量变量转化为较小的变量集合，同时保留大部分信息。在这里，主维度代表数据变化最大的方向。通过关注这些维度，数据科学家可以简化复杂的数据集，使其更易于分析和可视化。这在遗传学等领域尤为有用，因为研究人员处理数千个代表不同基因的变量，识别主维度可以导致对遗传疾病的重要发现。总之，术语主维度概括了关注复杂系统中最关键因素的思想。无论是在气候科学、经济学还是数据分析中，识别主维度使研究人员和专业人士能够精简他们的工作，取得更有意义的结果。通过聚焦这些关键维度，我们可以增强对复杂系统的理解，并根据扎实的证据做出明智的决策。随着我们继续探索各种科学和分析领域，主维度的概念无疑将继续作为有效研究和解决问题策略的基石。