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相关概念视频

Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

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The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
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Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

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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...
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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.
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Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
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Design Consideration01:22

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Designing a structure involves a series of considerations, primarily the material's ultimate strength, calculated through tests that measure changes under increased force until the material reaches its breaking point or limit. The ultimate load, where the material breaks, is divided by its original cross-sectional area, resulting in the ultimate normal stress or strength. The ultimate shearing stress is another significant factor taken into account.
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相关实验视频

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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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河流系统的最佳废物负载分配基于一个新的多目标子优化算法.

Shekoofeh Haghdoost1, Mohammad Hossein Niksokhan1, Mohammad G Zamani2

  • 1Faculty of Environment, University of Tehran, Tehran, Iran.

Environmental science and pollution research international
|November 27, 2023
PubMed
概括
此摘要是机器生成的。

一个新的优化模型,多目标优化算法 (MOCOA),优于现有的河流水质管理方法. MOCOA有效地分配废物负载,在更清洁的河流系统中在违规指数和不平等值方面取得更好的结果.

关键词:
子优化算法 (COA) 是一个算法.多目标优化 (MOO) 是指多目标优化.非主导排序的遗传算法 (NSGA-II)帕雷托的前面废物负载分配 (WLA) 是指废物负载的分配.

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科学领域:

  • 环境科学 环境科学
  • 水资源管理 水资源管理
  • 计算智能是一种计算智能.

背景情况:

  • 由于废物排放的增加和有限的自我清洁能力,河流水污染越来越令人担忧.
  • 现有的方法,如非主导排序基因算法-II (NSGA-II),已在河水质量管理方面表现出有效性.
  • 需要新的优化模型来应对复杂的废物负载分配挑战.

研究的目的:

  • 引入和评估一个新的优化框架,即多目标优化算法 (MOCOA),用于河流水质管理.
  • 在废物负载分配问题中,比较MOCOA与NSGA-II的性能.
  • 评估MOCOA在平衡排放目标与环境保护方面的能力.

主要方法:

  • 开发了一个新的优化框架,包括非主导排序和排名选择.
  • 实施了MOCOA对一个点源废物负载分配问题在Jajrood河,伊朗.
  • 将一个模拟模型与一个混合优化模型 (Cuckoo优化算法+NSGA-II) 联系起来,创建一个多目标算法.

主要成果:

  • 与NSGA-II相比,MOCOA在违规指数和不平等值方面表现出更高的帕雷托前线.
  • 对于相同的种群大小,MOCOA比NSGA-II (1.31-2.36) 取得了明显更好的帕雷托前端范围 (0.379-2.28).
  • MOCOA在人口规模较小的情况下实现了最佳股权,这表明效率更高.

结论:

  • MOCOA是一种有效和高效的算法,用于河流系统中的废物负载分配.
  • 拟议的MOCOA框架为优化河流水质提供了与NSGA-II相比显著的优势.
  • 这项研究为环境当局在管理河流污染方面提供了宝贵的工具.