intercompare

简明释义

英[ˌɪntəkəmˈpeə]美[ˌɪntərkəˈlʌmnər]

v. 对……作相互比较

第 三 人 称 单 数 i n t e r c o m p a r e s

现 在 分 词 i n t e r c o m p a r i n g

过 去 式 i n t e r c o m p a r e d

过 去 分 词 i n t e r c o m p a r e d

英英释义

单词用法

同义词

反义词

例句

1.In our study, we will intercompare 相互比较 the results from different climate models to assess their accuracy.

在我们的研究中，我们将相互比较不同气候模型的结果，以评估它们的准确性。

2.During the conference, scientists will intercompare 相互比较 their methodologies and results.

在会议期间，科学家们将相互比较他们的方法论和结果。

3.The goal of this project is to intercompare 相互比较 various techniques for measuring air quality.

这个项目的目标是相互比较测量空气质量的各种技术。

4.The researchers decided to intercompare 相互比较 the data collected from various geographic locations.

研究人员决定相互比较来自不同地理位置的数据。

5.To ensure reliability, we need to intercompare 相互比较 the findings with previous studies.

为了确保可靠性，我们需要相互比较这些发现与之前的研究。

作文

In the realm of science and research, the ability to intercompare different data sets and methodologies is crucial for ensuring accuracy and reliability. When researchers conduct experiments, they often gather vast amounts of data that need to be analyzed and interpreted. To validate their findings, it is essential to intercompare their results with those obtained by other scientists in similar studies. This process not only helps in confirming the validity of the results but also allows researchers to identify any discrepancies that may arise due to variations in experimental conditions or techniques.For instance, if two laboratories are conducting experiments on the same chemical reaction, they must intercompare their results to determine if they are consistent. If one lab reports a significantly different outcome, it prompts further investigation into the methods used or the potential influence of external factors. By intercomparing their findings, researchers can work collaboratively to refine their approaches and enhance the overall quality of scientific inquiry.Moreover, intercomparison is not limited to experimental results; it also applies to theoretical models. In fields such as climate science, various models are developed to predict future climate patterns. Scientists often intercompare these models to assess their accuracy and reliability. By analyzing how different models perform under similar conditions, researchers can gain insights into the strengths and weaknesses of each approach. This collaborative effort ultimately leads to more robust predictions and better-informed policy decisions regarding climate change.In addition to its importance in scientific research, the concept of intercomparison extends to various industries, including finance, engineering, and technology. For example, when developing new software, companies often intercompare their products with competitors to identify unique features and areas for improvement. This competitive analysis is vital for innovation and helps businesses stay relevant in a rapidly changing market.Furthermore, intercomparing data across different regions or demographics can uncover significant trends that may not be apparent when looking at isolated data sets. For instance, public health officials might intercompare vaccination rates across different communities to identify areas with lower uptake. This information is crucial for targeted outreach efforts and improving overall public health outcomes.In conclusion, the practice of intercomparing data, results, and methodologies is fundamental across various fields. It fosters collaboration, enhances accuracy, and drives innovation. Whether in scientific research, industry, or public health, the ability to intercompare effectively allows stakeholders to make informed decisions based on reliable information. As we continue to advance in our respective fields, embracing the value of intercomparison will undoubtedly lead to greater understanding and progress.

在科学和研究领域，intercompare 不同数据集和方法的能力对于确保准确性和可靠性至关重要。当研究人员进行实验时，他们通常会收集大量需要分析和解释的数据。为了验证他们的发现，必须将他们的结果与其他科学家在类似研究中获得的结果进行intercompare。这一过程不仅有助于确认结果的有效性，还使研究人员能够识别由于实验条件或技术的变化而可能出现的任何差异。例如，如果两个实验室正在对同一化学反应进行实验，他们必须 intercompare 他们的结果以确定它们是否一致。如果一个实验室报告出显著不同的结果，这将促使对所使用的方法或外部因素的潜在影响进行进一步调查。通过 intercomparing 他们的发现，研究人员可以合作改进他们的方法，提高科学研究的整体质量。此外，intercomparison 不仅限于实验结果；它也适用于理论模型。在气候科学等领域，开发了各种模型来预测未来的气候模式。科学家们经常 intercompare 这些模型，以评估其准确性和可靠性。通过分析不同模型在相似条件下的表现，研究人员可以深入了解每种方法的优缺点。这种协作努力最终导致更强有力的预测和更明智的气候变化政策决策。除了在科学研究中的重要性，intercomparison 的概念还扩展到金融、工程和技术等各个行业。例如，在开发新软件时，公司通常会 intercompare 他们的产品与竞争对手，以识别独特功能和改进领域。这种竞争分析对于创新至关重要，并有助于企业在快速变化的市场中保持相关性。此外，在不同地区或人群之间 intercomparing 数据可以揭示出一些趋势，而这些趋势在孤立的数据集中可能并不明显。例如，公共卫生官员可能会 intercompare 不同社区的疫苗接种率，以识别接种率较低的地区。这些信息对于有针对性的宣传工作和改善整体公共卫生结果至关重要。总之，intercomparing 数据、结果和方法的实践在各个领域都是基础。它促进了合作，增强了准确性，并推动了创新。无论是在科学研究、行业还是公共卫生中，有效地 intercompare 的能力使利益相关者能够基于可靠的信息做出明智的决策。随着我们在各自领域的不断进步，拥抱 intercomparison 的价值无疑将导致更大的理解和进步。