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A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
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Percentile-Based Adaptive Immune Plasma Algorithm and Its Application to Engineering Optimization.

Selcuk Aslan1, Sercan Demirci2, Tugrul Oktay1

  • 1Department of Aeronautical Engineering, Erciyes University, Kayseri 38000, Turkey.

Biomimetics (Basel, Switzerland)
|October 27, 2023
PubMed
Summary

The novel percentile immune plasma algorithm (pIPA) improves meta-heuristic techniques by using a percentile-based mechanism for selecting plasma donors and receivers. This enhanced approach boosts problem-solving capabilities in complex engineering tasks.

Keywords:
adaptive selectionbig dataimmune plasma algorithmpath planningpercentileunmanned aerial vehicle

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Area of Science:

  • Computational Intelligence
  • Meta-heuristic Algorithms
  • Biologically Inspired Computing

Background:

  • The immune plasma algorithm (IPA) is a recent meta-heuristic technique inspired by convalescent plasma treatment.
  • The COVID-19 pandemic renewed interest in IPA, highlighting its potential applications.
  • Determining optimal control parameters for IPA, specifically donor and receiver numbers, remains challenging.

Purpose of the Study:

  • To introduce a novel variant of the IPA, termed the percentile IPA (pIPA).
  • To improve the mechanism for determining plasma donors and receivers using a statistical percentile measure.
  • To evaluate the performance of the pIPA in solving benchmark and complex engineering problems.

Main Methods:

  • The study divided the population into two sub-populations using the percentile statistical measure.
  • A novel variant, the percentile IPA (pIPA), was developed based on this sub-population division.
  • The pIPA's performance was tested on 22 numerical benchmark problems and two complex engineering tasks (signal noise filtering and UAV path planning).

Main Results:

  • The percentile-based donor-receiver selection mechanism significantly enhanced the pIPA's problem-solving capabilities.
  • The pIPA demonstrated superior performance compared to well-established and state-of-the-art meta-heuristic algorithms.
  • The algorithm effectively addressed complex engineering challenges, including noise filtering and unmanned aerial vehicle path planning.

Conclusions:

  • The developed percentile IPA (pIPA) offers a significant improvement over the standard IPA.
  • The percentile-based mechanism is crucial for enhancing the algorithm's effectiveness in optimization tasks.
  • pIPA shows promise for application in various complex computational and engineering domains.