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Related Concept Videos

Distance Measurements by Taping01:18

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Tapes are essential in surveying for accurate, durable, and short-distance measurements. Made from lightweight, nylon-coated steel, they offer flexibility and strength for rugged outdoor use. The nylon coating protects against rust and wear, extending the tape's life. Standard lengths, around 30 meters, are marked in meters and millimeters for precision.Surveyors select tapes based on site conditions and accuracy needs. Lightweight, nylon-coated tapes are commonly used for ease of handling and...
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To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
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A multi-objective stacked regression method for distance based colour measuring device.

Amrinder Singh Brar1, Kawaljeet Singh2

  • 1Department of Computer Science and Engineering, Punjabi University, Patiala, 147002, India. amrinder.web@gmail.com.

Scientific Reports
|March 6, 2024
PubMed
Summary

This study introduces a novel Multi-Objective Stacked Regression (MOSR) model for accurate remote color measurement, overcoming external noise challenges. MOSR significantly improves prediction accuracy and reduces ensemble complexity for distance-based color measurement devices.

Keywords:
Colour measurementEnsemble modelMachine learningMulti-objective optimisationMulti-target regression

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Area of Science:

  • Computer Science
  • Machine Learning
  • Color Science

Background:

  • Accurate color identification from a distance is hindered by measurement noise.
  • Developing robust systems for remote color measurement is crucial.

Purpose of the Study:

  • To develop a novel Multi-target Regression (MTR) model for accurate distance-based color measurement.
  • To introduce the Multi-Objective Stacked Regression (MOSR) method.

Main Methods:

  • Proposed MOSR method utilizes stacking as an ensemble approach.
  • Employs multi-objective evolutionary learning (NSGA-II) for base learner selection.
  • Optimizes for prediction accuracy and minimizes ensemble complexity.

Main Results:

  • MOSR achieved the highest coefficient of determination for all three color targets.
  • Outperformed six state-of-the-art methods on the color dataset.
  • Demonstrated superior performance on 15 out of 18 benchmarked datasets with CART regressors.

Conclusions:

  • The MOSR method is statistically superior to existing methods.
  • MOSR effectively enhances accurate color value measurement in distance-based devices.