gross predict; gross prediction

简明释义

粗略预计

英英释义

例句

1.The economist made a gross predict 粗略预测 about the country's GDP growth for next year.

经济学家对该国明年的GDP增长做出了粗略预测。

2.When planning the budget, they had to make a gross predict 粗略预测 of the expenses involved.

在制定预算时，他们不得不做出一份费用的粗略预测。

3.During the meeting, she offered a gross predict 粗略预测 of sales figures for the upcoming quarter.

在会议上，她对即将到来的季度销售数字做出了粗略预测。

4.In his report, he included a gross prediction 粗略预测 of the market trends over the next five years.

在他的报告中，他包含了未来五年市场趋势的粗略预测。

5.The weather service provided a gross prediction 粗略预测 of the hurricane's path based on initial data.

气象服务根据初步数据提供了飓风路径的粗略预测。

作文

In today's rapidly changing world, making accurate predictions has become a crucial skill in various fields, from economics to environmental science. However, it is important to recognize that not all predictions are created equal. Some predictions can be termed as gross predict, which refers to an oversimplified or exaggerated forecast that fails to account for the complexities of reality. In contrast, a more nuanced approach is necessary for effective decision-making and planning.The term gross prediction highlights the pitfalls associated with relying solely on simplistic models or assumptions. For instance, in the realm of economic forecasting, a gross predict might suggest that a country's GDP will grow by a certain percentage based solely on historical data, without considering external factors such as political instability, global market fluctuations, or technological advancements. This kind of oversimplification can lead to misguided policies and ineffective strategies.Similarly, in environmental science, a gross prediction could involve estimating the impact of climate change based on limited data, ignoring the multitude of variables that contribute to environmental degradation. For example, predicting that a particular region will experience a rise in temperature without considering local geography, socio-economic factors, and existing environmental policies can result in inadequate preparation for future challenges.To avoid the dangers of gross predict and gross prediction, it is essential to adopt a more comprehensive approach to forecasting. This involves integrating diverse data sources, employing advanced analytical techniques, and engaging in interdisciplinary collaboration. By doing so, we can create more accurate and reliable models that reflect the complexities of real-world situations.Moreover, it is vital to communicate the uncertainties inherent in any prediction. Acknowledging the limitations of our forecasts can help stakeholders make more informed decisions. For instance, policymakers should be made aware that a gross prediction may not capture the full range of possible outcomes, thus encouraging them to consider multiple scenarios and develop contingency plans.In conclusion, while predictions play a significant role in shaping our understanding of future events, it is crucial to recognize the potential hazards of gross predict and gross prediction. By striving for accuracy and embracing complexity, we can enhance our ability to navigate the uncertainties of the future. Through careful analysis and thoughtful consideration of various factors, we can move beyond oversimplified forecasts and work towards more sustainable and effective solutions to the challenges we face in our world today.

在当今快速变化的世界中，做出准确的预测已成为各个领域的重要技能，从经济学到环境科学。然而，重要的是要认识到，并非所有的预测都是平等的。一些预测可以被称为粗略预测，指的是一种过于简化或夸大的预测，未能考虑现实的复杂性。相比之下，更细致的方法对于有效的决策和规划是必要的。术语粗略预测突显了仅仅依赖简化模型或假设所带来的陷阱。例如，在经济预测领域，粗略预测可能仅根据历史数据建议一个国家的GDP将增长一定百分比，而不考虑政治不稳定、全球市场波动或技术进步等外部因素。这种过度简化可能导致误导性的政策和无效的战略。同样，在环境科学中，粗略预测可能涉及基于有限数据估计气候变化的影响，忽略导致环境退化的众多变量。例如，预测某一地区的温度将上升而不考虑当地地理、社会经济因素和现有环境政策，可能导致对未来挑战的准备不足。为了避免粗略预测和粗略预测的危险，采取更全面的预测方法至关重要。这涉及整合多样化的数据来源、采用先进的分析技术以及进行跨学科的合作。通过这样做，我们可以创建更准确和可靠的模型，反映现实情况的复杂性。此外，沟通任何预测中固有的不确定性也至关重要。承认我们预测的局限性可以帮助利益相关者做出更明智的决策。例如，政策制定者应该意识到，粗略预测可能无法捕捉到所有可能的结果，从而鼓励他们考虑多种情景并制定应急计划。总之，尽管预测在塑造我们对未来事件的理解中发挥着重要作用，但至关重要的是要认识到粗略预测和粗略预测的潜在危害。通过追求准确性和拥抱复杂性，我们可以增强我们应对未来不确定性的能力。通过仔细分析和对各种因素的深思熟虑，我们可以超越过于简化的预测，朝着更可持续和有效的解决方案迈进，以应对当今世界面临的挑战。