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相关概念视频

Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

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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).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
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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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The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
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Heating and Cooling Curves02:44

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When a substance—isolated from its environment—is subjected to heat changes, corresponding changes in temperature and phase of the substance is observed; this is graphically represented by heating and cooling curves.
For instance, the addition of heat raises the temperature of a solid; the amount of heat absorbed depends on the heat capacity of the solid (q = mcsolidΔT). According to thermochemistry, the relation between the amount of heat absorbed or released by a substance, q, and its...
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Ampere-Maxwell's Law: Problem-Solving01:17

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A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
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Calculation of Electric Flux01:25

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Consider the electric field of an oppositely charged, parallel-plate system and an imaginary box between those plates. Let the bottom face of the box be ABCD, and the top face be FGHK. The electric field between the plates is uniform and points from the positive plate toward the negative plate. The calculation of this field's flux through the box's various faces shows that the net flux through the box is zero. Why does the flux cancel out here?
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A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
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2D 多尺度太阳辐射预测的时变功能建模框架.

Chengdong Shi1, Wei Zhao2, Xiao-Jun Zeng1

  • 1Department of Computer Science, University of Manchester, Manchester, M13 9PL, UK.

Neural networks : the official journal of the International Neural Network Society
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概括
此摘要是机器生成的。

准确的太阳辐射预测需要理解多尺度数据. 一个新的2D时间变量函数建模 (2D-TFM) 框架通过将1D时间序列转换为2D函数序列来改进预测.

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科学领域:

  • 预测可再生能源的使用情况
  • 时间序列分析时间序列分析
  • 机器学习用于能源系统

背景情况:

  • 太阳辐射预测对于能源管理至关重要.
  • 现有的1D时间序列方法与多尺度的时间动态作斗争.
  • 准确的长期太阳辐射预测仍然是一个挑战.

研究的目的:

  • 引入一个新的二维时间变量函数建模 (2D-TFM) 框架.
  • 克服1D表示在捕捉多尺度时间依赖性的局限性.
  • 提高太阳辐射预测的准确性和可解释性.

主要方法:

  • 使用B-spline基础函数扩展将1D太阳辐射时间序列转换为2D功能序列.
  • 使用自适应局部复杂性 (ALC) 节点放置算法优化功能表示.
  • 使用功能性的长短期内存 (LSTM) 网络来学习参数空间映射.

主要成果:

  • 与Seq2Seq-LSTM等现有方法相比,2D-TFM框架显示出更高的预测准确性.
  • 在每小时和每分钟的预测中,实现了根平均平方误差 (RMSE) 和平均绝对百分比误差 (MAPE) 的显著降低.
  • 该模型在任意时间分辨率下提供无网格预测,增强实际应用性.

结论:

  • 拟议的2D-TFM框架有效地捕捉了太阳辐射数据的短期波动和长期趋势.
  • 2D-TFM提供了比传统方法更好的计算效率和可解释性.
  • 该框架增强了用于能源管理系统的太阳辐射预测.