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相关概念视频

Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

2.1K
Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
2.1K
Precipitation Processes01:12

Precipitation Processes

596
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...
596
Precipitation Gravimetry01:03

Precipitation Gravimetry

7.6K
Precipitation gravimetry is based on converting an analyte into a sparingly soluble precipitate, which is separated by filtration and weighed. An ideal precipitate should be pure, insoluble, of known composition, and easily filtered from the reaction mixture.
In determining nickel by gravimetric analysis, a precipitant of ethanolic dimethylglyoxime is added to a hot nickel salt solution. This is quickly followed by the dropwise addition of dilute ammonia solution until precipitation occurs. A...
7.6K
Types of Coprecipitation01:10

Types of Coprecipitation

882
Coprecipitation is the contamination of a precipitate by otherwise soluble species and occurs via different processes. In colloidal precipitates, coprecipitation occurs via surface adsorption. For instance, barium sulfate has a primary layer of adsorbed barium ions and a secondary layer of nitrate counterions. This results in contamination of the precipitate by barium nitrate.
Sometimes, ions in a crystal lattice can undergo isomorphous replacement by inclusions of similar charge and size. For...
882
Precipitation Titration Curve: Analysis01:21

Precipitation Titration Curve: Analysis

1.2K
The precipitation titration curve demonstrates the change in concentration of one reactant with the volume of titrant added. During the titration of chloride ions with silver nitrate, the precipitation titration curve is divided into three regions: before, at, and after the equivalence point. Before the equivalence point, low redissolution of the sparingly soluble silver chloride precipitate gives a low silver ion concentration. However, in the second region, representing the equivalence point,...
1.2K
Precipitation Titration: Endpoint Detection Methods01:19

Precipitation Titration: Endpoint Detection Methods

2.1K
In argentometric precipitation titrations, endpoints can be detected visually by the Mohr, Volhard, and Fajans methods. In the Mohr method, adding a soluble chromate indicator gives an initial yellow color to the analyte solution. As the titrant is added, the first excess of silver ions forms a red silver chromate precipitate, marking the endpoint. The solution pH should be maintained at about 8 by adding solid CaCO3.
In the Volhard method, a standard excess of AgNO3 is first added to the...
2.1K

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相关实验视频

Updated: Sep 14, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
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每月降水预测基于二次分解和改进的算法.

Weijie Zhang1, Yuming Zeng1, Shubo Zhou1

  • 1School of Mechanical and Energy Engineering, Guangdong Ocean University, Yangjiang, 529500, China.

Scientific reports
|July 21, 2025
PubMed
概括

这项研究引入了一个新的CEEMDAN-TVMD-IPO-BiLSTM模型,用于准确的区域降水预测. 这种先进的框架显著提高了预测准确性,有助于气候变化适应和灾害管理.

关键词:
这就是为什么BiLSTM.在IPOIPOIPOIPO上市.每月降水量 每月降水量在TVMD上播放.时间特征是时间特征.

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Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information
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科学领域:

  • 环境科学 环境科学
  • 数据科学数据科学数据科学
  • 气候科学 气候科学

背景情况:

  • 降雨预测对于生态平衡和经济稳定至关重要.
  • 降水数据的非线性和随机性质阻碍了准确的预测.
  • 改善区域降水预测对于预防灾害和应对气候变化至关重要.

研究的目的:

  • 为区域降水预测开发一个强大而准确的模型.
  • 为了提高复杂的,非线性降水时间序列数据的预测准确度.
  • 为减轻灾害和适应气候变化政策提供科学基础.

主要方法:

  • 提出了一个新的降水预测模型:CEEMDAN-TVMD-IPO-BiLSTM.
  • 使用CEEMDAN进行初始数据分解.
  • 采用拓优化算法 (TTAO) 来优化二次分解的变量模式分解 (VMD).
  • 优化双向长短期内存 (BiLSTM) 使用改进的优化器 (IPO) 具有混乱的变化.
  • 通过中国广州,长沙和埃梅山的历史月度降水数据验证了该模型.

主要成果:

  • CEEMDAN-TVMD-IPO-BiLSTM模型在每月降水预测方面表现出卓越的表现.
  • 实现了较低的根平均平方误差 (RMSE) 值:32.373 (广州),14.445 (长沙) 和22.447 (伊梅山).
  • 达到高的R2值:0.960 (广州),0.972 (长沙) 和0.977 (伊梅山).
  • 在准确性和稳定性方面表现优于现有的模型.

结论:

  • 拟议的CEEMDAN-TVMD-IPO-BiLSTM模型有效预测区域降水波动.
  • 该模型在降水预测准确度方面取得了重大进展.
  • 为与干旱和洪水管理相关的政策制定提供了有价值的科学见解.