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Classification of Titrimetric Analysis Based on Reaction Types01:01

Classification of Titrimetric Analysis Based on Reaction Types

Titrimetric analysis in solution chemistry involves measuring the volume of solutions and is often called volumetric analysis. The standard solution of known concentration in the burette is called the titrant, whereas the solution of unknown concentration in the flask is called the analyte, or titrand. Titrimetric analyses can be classified into four types based on the reactions between the titrant and analyte.
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Metal oxide gas sensor drift compensation using a dynamic classifier ensemble based on fitting.

Hang Liu1, Zhenan Tang

  • 1College of Electronic Science and Technology, Dalian University of Technology, No.2 Linggong Road, Dalian 116024, China. liuhang@dlut.edu.cn

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Summary
This summary is machine-generated.

This study introduces a dynamic weighted ensemble method to overcome sensor drift in gas sensing. The novel approach achieves high accuracy in gas discrimination over extended periods, outperforming existing methods.

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Area of Science:

  • Environmental Science
  • Chemical Sensing Technology

Background:

  • Sensor drift is a significant challenge in gas sensing, impacting long-term accuracy and reliability.
  • Accurate gas discrimination is crucial for environmental monitoring and industrial safety applications.

Purpose of the Study:

  • To develop a robust method for gas discrimination that mitigates the effects of sensor drift.
  • To improve the accuracy and longevity of gas sensing systems.

Main Methods:

  • A novel ensemble method with dynamic weights based on fitting (DWF) was proposed.
  • The DWF method combines support vector machine (SVM) classifiers trained on data from different time periods.
  • Classifier weights are dynamically predicted using fitting functions derived from optimal weights during training.

Main Results:

  • The DWF method demonstrated superior performance in gas discrimination compared to competing methods.
  • The method maintained high accuracy over extended periods, effectively addressing sensor drift.
  • Optimization potential exists by selecting fitting functions that better match weight variations over time.

Conclusions:

  • The DWF method offers a promising solution for accurate and stable gas discrimination in the presence of sensor drift.
  • This approach enhances the reliability of gas sensing systems for long-term applications.
  • Further refinement of fitting functions can lead to even greater performance improvements.