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相关概念视频

Flame Photometry: Overview01:02

Flame Photometry: Overview

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Flame photometry, also known as flame emission spectrometry, is a technique used for the qualitative and quantitative analysis of elements present in a sample using a flame as the source of excitation energy. The concept of flame photometry was realized in the early 1860s by Kirchhoff and Bunsen, who discovered that specific elements emit characteristic radiation when excited in flames. The first instrument developed for this purpose was used to measure sodium (Na) in plant ash using a Bunsen...
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Laminar flow occurs when a fluid moves smoothly in parallel layers with minimal mixing and turbulence. In fluid mechanics, ensuring laminar flow within a pipe is essential for precise control of flow characteristics, especially in engineering applications. The key factor in determining whether flow remains laminar is the Reynolds number, a dimensionless quantity that depends on the fluid's velocity, density, viscosity, and the pipe's diameter. A Reynolds number of 2100 or lower...
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Laminar flow represents a smooth, orderly fluid motion where particles move along parallel paths, resulting in minimal mixing between layers. Streamlined particle paths characterize this flow regime and occur under conditions where viscous forces dominate over inertial forces. The distinction between laminar, transitional, and turbulent flow is primarily determined by the Reynolds number, a dimensionless quantity calculated as:
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In the growing field of wind energy, incorporating wind turbine models into transient stability analysis is essential. Induction and synchronous machines are the primary models used, with induction machines being prevalent due to their simplicity and reliability.
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Fluid dynamics is the study of fluids in motion. Velocity vectors are often used to illustrate fluid motion in applications like meteorology. For example, wind—the fluid motion of air in the atmosphere—can be represented by vectors indicating the speed and direction of the wind at any given point on a map. Another method for representing fluid motion is a streamline. A streamline represents the path of a small volume of fluid as it flows. When the flow pattern changes with time, the...
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Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
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相关实验视频

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Experimental Methodology for Estimation of Local Heat Fluxes and Burning Rates in Steady Laminar Boundary Layer Diffusion Flames
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基于LSTM的长期,短期和中期风速预测模型,通过改进的火焰优化算法进行优化.

Runze Li1, Jianzhou Wang2, Jingrui Li1

  • 1Institute of Systems Engineering, Macau University of Science and Technology, Macau, 999078, China.

Environmental science and pollution research international
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概括
此摘要是机器生成的。

准确的风速预测对于稳定的风力发电至关重要. 本研究介绍了一种优化的长短期记忆 (LSTM) 系统,使用了改进的火焰优化算法,提高了风能系统的预测准确性.

关键词:
模糊信息的细分化模糊信息的细分化.改进了火焰优化算法.长期和短期内存 网络内存预测风速的预测

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科学领域:

  • 可再生能源系统可再生能源系统
  • 人工智能在能源中的作用
  • 时间序列预测时间序列预测

背景情况:

  • 风速波动对风力轮机和电网构成重大风险,需要精确的预测方法.
  • 准确的风速预测对于可靠的风力发电和电网稳定性至关重要.
  • 现有的预测模型经常与风速数据固有的不稳定性作斗争.

研究的目的:

  • 开发一个增强的风速预测系统,以改善风力发电.
  • 优化长期短期记忆 (LSTM) 网络,使用一种新的群集智能算法.
  • 评估拟议系统在短期,中期和长期风速预测方面的表现.

主要方法:

  • 实施了一个三模块系统:数据预处理,优化和预测.
  • 采用模糊信息粒度用于数据预处理,以处理输入数据的模糊性.
  • 采用改进的火焰优化 (MFO) 算法来调整LSTM预测模型参数.
  • 应用了优化的LSTM模型来预测风速时间序列.

主要成果:

  • 拟议的系统在短期预测中实现了3.15%的平均绝对百分比误差 (MAPE).
  • 中期预测的MAPE为4.38%,显示出强的业绩.
  • 长期预测的结果为18.28%的MAPE,表明在不同的时间范围内有效.
  • 实验结果显示,与以前的风速预测模型相比,实验结果具有显著的优势.

结论:

  • 改进的火焰优化算法有效优化了LSTM网络的风速预测.
  • 拟议的系统在预测各种时间尺度上的风速方面表现出卓越的准确性和可靠性.
  • 这种方法为提高风力发电的稳定性和效率提供了一个有希望的解决方案.