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相关概念视频

Levels of Use of a GIS01:29

Levels of Use of a GIS

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Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
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Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

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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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Modeling and Similitude01:12

Modeling and Similitude

295
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
295
Design Example: Design of an Irrigation Channel01:27

Design Example: Design of an Irrigation Channel

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Trapezoidal channels are widely used in irrigation systems due to their cost-effectiveness and efficiency in conveying water. Trapezoidal channels feature a flat bottom and sloping sides, making them stable and easier to construct compared to other shapes. The bottom width and side slope ratio are determined based on the required flow capacity and site conditions. The side slope is kept gentle for unlined channels to prevent soil erosion.Hydraulic parameters in channel design include the flow...
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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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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.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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Design Example: Maintaining Level of an Embankment01:19

Design Example: Maintaining Level of an Embankment

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Constructing a roadway embankment over uneven terrain requires precise leveling to ensure stability and proper drainage. Surveyors use a leveling instrument and staff to calculate ground elevations and determine the required fill material at each point along the embankment alignment.The process begins by positioning a leveling instrument near a benchmark with a known elevation. A backsight reading establishes the instrument height, which serves as a reference for subsequent measurements. A...
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相关实验视频

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Watershed Planning within a Quantitative Scenario Analysis Framework
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Watershed Planning within a Quantitative Scenario Analysis Framework

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使用人工智能混合算法驱动地下水位的数据.

Mohammadtaghi Rahimi1, Hossein Ebrahimi2

  • 1Department of Civil Engineering, Kish international Branch, Islamic Azad University, Kish Island, Iran.

Scientific reports
|June 26, 2023
PubMed
概括

这项研究引入了一种新的混合人工智能模型 (DL-FF-KNN-ABC-MLP),用于预测胡泽斯坦省的地下水位. 该先进模型在预测地下水波动方面表现出高准确度,这对于水资源管理至关重要.

科学领域:

  • 环境科学 环境科学
  • 水资源管理 水资源管理
  • 人工智能的人工智能

背景情况:

  • 人口增长和工业/农业发展需要强大的定量和质量水资源管理.
  • 通过水位波动监测地下水库至关重要,特别是在诸如胡泽斯坦省这样的干旱地区.
  • 人工智能 (AI) 已经成为全球地下水资源预测和管理的强大工具.

研究的目的:

  • 开发和评估一种新的混合人工智能模型,用于预测库泽斯坦省卡莱-托尔地区的地下水位.
  • 评估DL-FF-KNN-ABC-MLP混合模型在管理和预测地下水资源方面的有效性.
  • 调查拟议的混合模型的数据降噪能力.

主要方法:

  • 开发了一个混合模型,结合了Feed Forward-K-Nearest Neighbors (FF-KNN),人工蜂群-K-Nearest Neighbors (ABC-KNN) 和一个新的DL-FF-KNN-ABC-MLP架构.
  • DL-FF-KNN-ABC-MLP模型采用两块方法:通过FF-DWKNN进行分类,并通过ABC-MLP进行预测.
  • 来自1-5井的数据用于训练和测试AI混合模型,而6-8井用于模型开发和验证.

主要成果:

  • DL-FF-KNN-ABC-MLP模型实现了较低的统计根平均平方误差 (RMSE) 值:0.0451 (测试),0.0597 (列车) 和0.0701 (总).

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  • 混合模型在预测地下水位方面表现出高性能准确性.
  • 新型架构有效地减少了数据噪声,提高了预测可靠性.

    • 结论:

    • DL-FF-KNN-ABC-MLP混合模型对于预测胡泽斯坦省地下水位非常有效.
    • 这种人工智能驱动的方法在地下水资源管理和预测准确性方面取得了重大进展.
    • 该研究强调了先进的混合人工智能模型在干旱地区解决水资源短缺挑战方面的潜力.