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相关概念视频

GIS Software, Hardware, and Sources of GIS Data01:23

GIS Software, Hardware, and Sources of GIS Data

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A Geographic Information System (GIS) combines specialized software and hardware to effectively manage, analyze, and present spatial and related data. GIS software includes critical functionalities such as a user interface for easy navigation, database management tools for handling spatial and attribute data, and data retrieval features for efficient access. Analytical tools transform raw data into insights, while display functions produce maps and reports in various formats for effective...
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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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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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Data Reporting and Recording01:24

Data Reporting and Recording

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Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
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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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Parallel Processing01:20

Parallel Processing

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The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
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相关实验视频

Updated: Jun 5, 2025

Data Communication Based on MQTT in a Polymer Extrusion Process
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基于云的可配置数据流处理架构在农村经济发展中的应用

Haohao Chen1, Fadi Al-Turjman2

  • 1College of Management, Wuhan Technology and Business University, Wuhan, Hubei, China.

PeerJ. Computer science
|December 9, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了RL-CNN-GRU框架,用于增强农业价格预测. 这种新的方法显著提高了准确性,帮助农村信息化和经济发展.

关键词:
云计算是一种云计算.深度学习是一种深度学习.智能农业是一个智能农业.农村经济 农村经济 农村经济

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科学领域:

  • 农业经济学 农业经济学
  • 数据科学数据科学数据科学
  • 机器学习 机器学习

背景情况:

  • 传统的数据处理方法与农业价格预测的复杂性作斗争.
  • 准确的价格预测对于农村信息化,农业效率和经济增长至关重要.

研究的目的:

  • 开发用于预测农产品价格的先进框架.
  • 克服现有的数据处理技术在这个领域的局限性.

主要方法:

  • 这项研究提出了强化学习 - 卷积神经网络通道循环单元 (RL-CNN-GRU) 框架.
  • 该模型集成了1D-CNN用于特征提取和GRU用于时间模式识别.
  • 强化学习被用来优化模型的准确性与多维时间序列数据.

主要成果:

  • 与传统模型相比,RL-CNN-GRU框架显示出更高的性能.
  • 拟议的框架在价格预测中实现了较低的平均平方误差 (MSE) 和平均绝对误差 (MAE).
  • 验证使用公共和专有农业数据集进行.

结论:

  • RL-CNN-GRU框架为农业价格预测提供了更准确的工具.
  • 这种进步支持农业过程中更好的决策,并有助于农村经济发展.
  • 该研究强调了集成机器学习模型在加强农村信息化方面的潜力.