Jove
Visualize
お問い合わせ
JoVE
x logofacebook logolinkedin logoyoutube logo
JoVEについて
概要リーダーシップブログJoVEヘルプセンター
著者向け
出版プロセス編集委員会範囲と方針査読よくある質問投稿
図書館員向け
推薦の声購読アクセスリソース図書館諮問委員会よくある質問
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experimentsアーカイブ
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教員リソースセンター教員サイト
利用規約
プライバシーポリシー
ポリシー

関連する概念動画

Dynamic Equilibrium02:20

Dynamic Equilibrium

53.3K
A reversible chemical reaction represents a chemical process that proceeds in both forward (left to right) and reverse (right to left) directions. When the rates of the forward and reverse reactions are equal, the concentrations of the reactant and product species remain constant over time and the system is at equilibrium. A special double arrow is used to emphasize the reversible nature of the reaction. The relative concentrations of reactants and products in equilibrium systems vary greatly;...
53.3K
The Anchoring-and-Adjustment Heuristic01:25

The Anchoring-and-Adjustment Heuristic

7.4K
In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the...
7.4K
Turbulent Flow: Problem Solving01:09

Turbulent Flow: Problem Solving

184
Carbonation is a process used to dissolve carbon dioxide gas in a liquid, commonly used in the production of carbonated beverages. Achieving efficient carbonation requires careful control of temperature, pressure, and flow conditions. By adjusting these parameters, carbonation efficiency can be maximized, producing a higher concentration of CO2 in the liquid.
Temperature is a key factor in CO2 solubility. In this case, the CO2 gas and the liquid are cooled to 20°C. Lower temperatures...
184
Production Efficiency01:01

Production Efficiency

17.0K
Net production efficiency (NPE) is the efficiency at which organisms assimilate energy into biomass for the next trophic level. Due to low metabolic rates and less energy spent on thermoregulatory processes, the NPE of ectotherms (cold-blooded animals) is 10 times higher than endotherms (warm-blooded animals).
17.0K
Heuristics01:21

Heuristics

149
Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
149
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

100
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
100

こちらも読む

関連記事

共著者、ジャーナル、引用グラフによってこの研究に関連する記事。

並び替え
Same author

LoRASculpt: Harmonious Low-Rank Adaptation for Multimodal Large Language Models.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Towards clinical-level interpretation of dental panoramic radiography using an instance-guided vision-language model.

Nature biomedical engineering·2026
Same author

Systemic immune-inflammation index predicts post-thrombectomy outcomes and reveals a mediating role in the association between neurocardiac stress and prognosis: a multicenter study.

Frontiers in neurology·2026
Same author

Holistic Invariant Retracing for Distortion-Resilient Multi-Modal Learning in Spatial Transcriptomics.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Differentiable Clustering Graph Convolutional Network for Hyperspectral Unmixing: Methodology and Benchmark.

IEEE transactions on neural networks and learning systems·2026
Same author

MUP-SAM: Multi-scale vision mamba UNet prompt generation for SAM in multi-organ medical image segmentation.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Multiphysics Investigation on Thermal Characteristics of Internal Bio-Inspired V-Ribbed Cooling Channels for Outer Rotor PMSM.

Biomimetics (Basel, Switzerland)·2026
Same journal

Smart Logistics Model for Supply Chain Management via Brain-Inspired Geometric Deep Networks.

Biomimetics (Basel, Switzerland)·2026
Same journal

A Systematic Taxonomy of the Sunflower Optimization Algorithm: Variants, Hybridization Strategies, Applications, and Research Directions.

Biomimetics (Basel, Switzerland)·2026
Same journal

Toward a Compositional Theory of Trust in Embodied Intelligence: A QNLP Framework for Modeling Context, Interaction, and Trustworthiness.

Biomimetics (Basel, Switzerland)·2026
Same journal

Empirical Logic for Bio-Inspired Soft Computing: Illustrative Applications in Control Engineering and Cluster Analysis.

Biomimetics (Basel, Switzerland)·2026
Same journal

A Modified Multi-Strategy Dhole Optimization Algorithm and Its Engineering Applications.

Biomimetics (Basel, Switzerland)·2026
関連記事をすべて見る

関連する実験動画

Updated: Sep 10, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.0K

貿易ハブの位置と割り当て方法のための新型人工イーグルインスピレーションの最適化アルゴリズム

Shuhan Hu1, Gang Hu1, Bo Du2

  • 1Department of Applied Mathematics, Xi'an University of Technology, Xi'an 710054, China.

Biomimetics (Basel, Switzerland)
|August 27, 2025
PubMed
まとめ
この要約は機械生成です。

新しい人工イーグル最適化アルゴリズム (AEOA) は,貿易ハブの位置と割り当て問題を効果的に解決し,改善された物流のための建設と輸送コストを削減します.

キーワード:
人工の鷹インテリジェント・最適化アルゴリズム低コストの輸送貿易センターの位置

さらに関連する動画

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.8K
Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization
06:00

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Published on: August 27, 2021

5.4K

関連する実験動画

Last Updated: Sep 10, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.0K
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.8K
Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization
06:00

Electroantennography-based Bio-hybrid Odor-detecting Drone using Silkmoth Antennae for Odor Source Localization

Published on: August 27, 2021

5.4K

科学分野:

  • 運用研究
  • コンピューター・インテリジェンス
  • 最適化アルゴリズム

背景:

  • 都市間の効率的な貨物輸送は経済活動にとって極めて重要です.
  • 貿易ハブの位置と配分に関する既存の方法は,費用対効果が低く,最適ではないかもしれません.
  • 建設と輸送コストを最小限に抑えることは,物流ネットワークの設計の重要な目標です.

研究 の 目的:

  • 貿易拠点の位置と配置に関する新しい方法を提案する.
  • この複雑な問題を解くための人工イーグル最適化アルゴリズム (AEOA) を開発する.
  • 商品の移転に伴う全体的なコストを削減する.

主な方法:

  • 建設と輸送コストを目的として,貿易ハブの位置と割り当てモデルを策定しました.
  • の移動行動に触発された新しい人工最適化アルゴリズム (AEOA) を開発しました.
  • AEOAに状況認識,自由探索,飛行戦略を組み込みました.

主要な成果:

  • AEOAは他の8つのアルゴリズムと比較して12のベンチマーク機能のうち11で優れたパフォーマンスを示しました.
  • 定量分析は,AEOAのより速い収束速度とより高い安定性を確認しました.
  • シミュレートされたケーススタディは,最適なハブを選択し,コストを削減するメソッドの能力を示しました.

結論:

  • AEOAによって推進された貿易ハブの位置と配分方法は,効果的に物流コストを最小限に抑えます.
  • AEOAは複雑な最適化問題の 堅牢で効率的なアルゴリズムです
  • このアプローチは,河南省のケーススタディで示されたように,物流計画における政府の意思決定に貴重なツールを提供します.