Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

4.0K
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...
4.0K
Precipitation Processes01:12

Precipitation Processes

4.5K
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...
4.5K
Precipitation Gravimetry01:03

Precipitation Gravimetry

12.8K
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...
12.8K
Precipitation Titration: Endpoint Detection Methods01:19

Precipitation Titration: Endpoint Detection Methods

4.5K
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...
4.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

LGALS1-CD276 Paracrine axis between tumor and endothelial cells promotes tumor angiogenesis and progression in bladder cancer.

Cell death and differentiation·2026
Same author

The formation and function of tertiary lymphoid structures.

Biomarker research·2026
Same author

CDK1 Phosphorylates KAT8 at Ser348 to Stabilize the MSL Complex and Promote H4K16 Acetylation in Non-Small Cell Lung Cancer.

Cells·2026
Same author

A Plug-and-Play Platform for Customizing Multivalent Degraders and Degrader-Drug Conjugates.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

RGB-D Perception-Enhanced 3D Gaussian Splatting SLAM: A Robust Framework for Mapping Underground Spaces.

IEEE transactions on visualization and computer graphics·2026
Same author

Multi-Omics Profiling of Long Noncoding RNAs in Clear Cell Renal Cell Carcinoma for Characterization and Clinical Applications.

International journal of biological sciences·2026

Related Experiment Video

Updated: Jan 1, 2026

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

2.0K

Short-term rainfall forecast model based on the improved BP-NN algorithm.

Yang Liu1, Qingzhi Zhao2, Wanqiang Yao1

  • 1College of Geomatics, Xi'an University of Science and Technology, Xi'an, 710054, China.

Scientific Reports
|December 26, 2019
PubMed
Summary

This study enhances rainfall forecasting by integrating multiple atmospheric parameters with an improved Back Propagation Neural Network (BP-NN) algorithm. The new model significantly boosts true forecast rates, offering a more reliable prediction of precipitation events.

More Related Videos

A Protocol for Conducting Rainfall Simulation to Study Soil Runoff
10:35

A Protocol for Conducting Rainfall Simulation to Study Soil Runoff

Published on: April 3, 2014

21.3K
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.9K

Related Experiment Videos

Last Updated: Jan 1, 2026

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

2.0K
A Protocol for Conducting Rainfall Simulation to Study Soil Runoff
10:35

A Protocol for Conducting Rainfall Simulation to Study Soil Runoff

Published on: April 3, 2014

21.3K
A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.9K

Area of Science:

  • Meteorology and atmospheric science
  • Geospatial science and technology
  • Artificial intelligence and machine learning

Background:

  • Existing rainfall forecasting methods often rely on single predictors like Zenith Total Delay (ZTD) or Precipitable Water Vapor (PWV) from Global Navigation Satellite Systems (GNSS).
  • Rainfall occurrence is influenced by numerous atmospheric parameters, necessitating a multi-variable approach for accurate forecasting.
  • The limitations of single-predictor models highlight the need for advanced algorithms capable of processing complex atmospheric data.

Purpose of the Study:

  • To develop and validate a short-term rainfall forecasting model using an improved Back Propagation Neural Network (BP-NN) algorithm.
  • To investigate the contribution of multiple atmospheric parameters (temperature, humidity, dew temperature, pressure, PWV) to rainfall prediction.
  • To enhance the accuracy and reliability of rainfall forecasts compared to existing methods.

Main Methods:

  • Utilized an improved Back Propagation Neural Network (BP-NN) algorithm for rainfall forecasting.
  • Incorporated multiple atmospheric parameters including temperature, relative humidity, dew temperature, pressure, and Precipitable Water Vapor (PWV).
  • Validated the model using three years of data from two GNSS stations and collocated weather stations in Singapore (2010-2012).

Main Results:

  • Correlation analysis confirmed the significant contribution of individual meteorological parameters to rainfall.
  • The proposed multi-parameter BP-NN model achieved a True Forecast Rate (TFR) exceeding 96%.
  • The model demonstrated a False Forecast Rate (FFR) of approximately 40%, with a TFR improvement of about 10% over existing methods.

Conclusions:

  • The improved BP-NN model effectively forecasts short-term rainfall by integrating multiple atmospheric parameters.
  • The model's high TFR and comparable FFR validate its reliability and practicality for rainfall prediction.
  • This approach offers a significant advancement in meteorological forecasting accuracy using GNSS-derived data and AI.