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

Optimal Foraging00:48

Optimal Foraging

13.6K
How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment.
13.6K
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

281
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
281
Growth Models with Integration: Problem Solving01:27

Growth Models with Integration: Problem Solving

9
In population modeling, integration provides a systematic way to determine accumulated quantities from known rates of change. One such application arises in ecology, where the total weight of a fish population in a body of water is referred to as its biomass. When the rate of growth of this biomass is known as a function of time, calculus can be used to determine the total biomass at a future date.Growth Rate and Biomass FunctionLet the growth rate of the fish population be represented by a...
9
Mathematical Modeling: Problem Solving01:29

Mathematical Modeling: Problem Solving

249
Mathematical modeling transforms real-world scenarios into mathematical expressions, allowing for structured problem-solving and analysis. This process involves defining the situation, assigning variables to measurable quantities, selecting an appropriate model, and solving the resulting equation. Such models are invaluable in finance, providing precise methods to evaluate investments, loans, and repayment structures.A widely used example is the calculation of fixed monthly payments on a loan,...
249
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

282
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...
282
Survival Tree01:19

Survival Tree

382
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
382

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

Surveillance and Epidemiological Characteristics of Enterohemorrhagic <i>Escherichia coli</i> (EHEC) Infection in the Republic of Korea.

Public health weekly report·2026
Same author

Erratum: Guidelines for the Use of Botulinum Toxin in Otolaryngology From the Korean Society of Laryngology, Phoniatrics and Logopedics Guideline Task Force.

Clinical and experimental otorhinolaryngology·2026
Same author

Understanding Spaceflight-Induced Oxidative Stress and the Critical Role of Diet and Microbiome.

Antioxidants (Basel, Switzerland)·2026
Same author

A Pathomics-Based Prognostic Model for Disease-Free Survival in Resected Gastric Cancer.

Cancers·2026
Same author

Electrochemiluminescence Biosensing Platform Based on CRISPR/Cas12a and DNA Nanotweezer-Mediated Catalytic Hairpin Assembly Amplification.

Analytical chemistry·2026
Same author

Effects of Isolated Pea Protein on Extrusion-Induced Gelation and Gel-like Network Formation in Low-Moisture Meat Analog Systems.

Gels (Basel, Switzerland)·2026
Same journal

Spatial patterns of climatic and ecological effects of photovoltaic power plants in Northwest China.

Journal of environmental management·2026
Same journal

Spatiotemporal response of urban bike-sharing ridership to weather, air quality, and future climate change in major U.S. cities.

Journal of environmental management·2026
Same journal

Urbanisation impacts avian biodiversity on stream ecosystems - insights from a large geographical scale.

Journal of environmental management·2026
Same journal

How green is hydrogen production? A unified life cycle carbon accounting framework and dynamic standard optimization across major economies.

Journal of environmental management·2026
Same journal

Energy-efficient pulsed photocatalysis with engineered biochar-ferrite nanocomposites for the reductive degradation of chlortoluron in water.

Journal of environmental management·2026
Same journal

Divergent biodiversity responses of multitrophic aquatic communities to hydrological connectivity and land-use intensity gradients.

Journal of environmental management·2026
関連記事をすべて見る

関連する実験動画

Updated: Jan 14, 2026

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
08:16

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

466

都市の炭素隔離を最大化するための深層学習ベースの代理モデリングと都市森林配分の最適化の統合

Da Seul Kim1, Dong Kun Lee2, Eun Sub Kim3

  • 1Department of Landscape Architecture and Rural System Engineering, Seoul National University, Seoul, Republic of Korea.

Journal of environmental management
|January 12, 2026
PubMed
まとめ
この要約は機械生成です。

深層学習フレームワークを使用した都市植林の最適化は、炭素隔離を最大化します。既存の森林の近くに戦略的に植えることは、気候緩和のための純生産性（NPP）と景観の接続性を向上させます。

キーワード:
遺伝的アルゴリズム最適化自然に基づく解決策純生産性（NPP）空間意思決定支援システム都市植林

さらに関連する動画

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

13.4K
Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.7K

関連する実験動画

Last Updated: Jan 14, 2026

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
08:16

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

466
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

13.4K
Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.7K

科学分野:

  • 都市生態学
  • 気候変動緩和
  • 地理空間分析

背景:

  • 都市植林は炭素隔離に不可欠ですが、現在の戦略では空間的変動と生態学的接続性が無視されることがよくあります。
  • 面積拡大目標は、炭素吸収を最大化するための最も効果的なアプローチではない可能性があります。

研究 の 目的:

  • 都市植林のための統合最適化フレームワークを開発および適用すること。
  • 都市環境における純生産性（NPP）と炭素隔離を最大化すること。
  • 戦略的なグリーンインフラ計画を通じて生態学的接続性を向上させること。

主な方法:

  • 人工ニューラルネットワーク（ANN）と遺伝的アルゴリズム（GA）を組み合わせた深層学習代理モデルを開発しました。
  • NPPを予測するために、地形、気候、土地利用、景観変数でANNをトレーニングしました。
  • 要因の重要性のためにSHapley Additive exPlanations（SHAP）を利用し、植林パッチの最適化のためにGAを利用しました。

主要な成果:

  • ANNモデルはNPPを正確に予測しました（テストデータでR²=0.82）。
  • 既存の森林への近接性がNPP向上のための重要な要因であると特定されました。
  • GA最適化により、緑地近くの植林が接続性の向上を通じてNPPを大幅に向上させることが示されました。

結論:

  • データ駆動型フレームワークは、炭素隔離のための都市植林を効果的に最適化します。
  • 生態学的接続性を優先する植林の戦略的な配置は、単純な面積拡大よりも効率的です。
  • このアプローチは、炭素ニュートラルな未来のための適応型都市グリーンインフラ計画をサポートします。