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関連する概念動画

The Uncertainty Principle04:08

The Uncertainty Principle

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Werner Heisenberg considered the limits of how accurately one can measure properties of an electron or other microscopic particles. He determined that there is a fundamental limit to how accurately one can measure both a particle’s position and its momentum simultaneously. The more accurate the measurement of the momentum of a particle is known, the less accurate the position at that time is known and vice versa. This is what is now called the Heisenberg uncertainty principle. He...
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Uncertainty in Measurement: Reading Instruments02:46

Uncertainty in Measurement: Reading Instruments

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Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
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Uncertainty: Overview00:59

Uncertainty: Overview

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In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
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Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

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Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
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Uncertainty in Measurement: Significant Figures03:34

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All the digits in a measurement, including the uncertain last digit, are called significant figures or significant digits. Note that zero may be a measured value; for example, if a scale that shows weight to the nearest pound reads “140,” then the 1 (hundreds), 4 (tens), and 0 (ones) are all significant (measured) values.
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Uncertainty: Confidence Intervals00:54

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The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
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Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
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都市ドローン物流のための適応型空域配分モデル：不確実性下での多目的最適化

Yao Zhu1, Xin Sun2, Tongdi Hou2

  • 1Business School, Yancheng Polytechnic College, Yancheng, 224005, Jiangsu, China. yphz5223@outlook.com.

Scientific reports
|January 19, 2026
PubMed
まとめ
この要約は機械生成です。

この研究は、都市の無人航空機（UAV）物流のためのハイブリッドフレームワークを導入し、複雑な環境での効率性と安全性を強化します。DRL-ROモデルは、堅牢な都市レベルのUAV交通管理のために不確実性に対処します。

キーワード:
適応型空域配分深層強化学習分散ロバスト最適化多目的最適化都市無人航空機物流

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科学分野:

  • 物流・輸送科学
  • 人工知能・ロボット工学
  • 都市計画・管理

背景:

  • 都市の無人航空機（UAV）物流は、限られた空域、需要の変動性、不確実性といった課題に直面しています。
  • 静的な配分方法は、動的な都市環境には不十分です。

研究 の 目的:

  • 都市UAV物流管理のための適応型フレームワークを開発すること。
  • 空域制限、需要変動、不確実性の課題に対処すること。

主な方法:

  • DRL-RO（深層強化学習と離散ロバスト最適化）ハイブリッドフレームワークを開発しました。
  • 3層の不確実性モデリングシステムと注意機構強化ポリシーネットワークを採用しました。
  • Paretoフロンティア近似のために改良されたMOEA/D-DRLアルゴリズムを使用しました。

主要な成果:

  • フレームワークは、深圳での高い成功率で、サブ二次計算複雑性を達成しました。
  • 階層的な空域管理戦略は、流通効率、飛行安全性、コストのバランスを取りました。
  • ワッサースタイン球制約は、極端なシナリオにおける堅牢性とスケーラビリティを保証しました。

結論:

  • DRL-ROフレームワークは、都市UAV交通管理のための堅牢なソリューションを提供します。
  • 都市規模のUAVシステムに理論的サポートと技術的ソリューションを提供します。
  • この研究は、UAV物流における効率性、安全性、コストの効果的なバランスを示しています。