A Modified Particle Swarm Optimization Algorithm for Solving DNA Problem
| Autor: | Talha Ali Khan, Nham Tram, Sai Ho Ling, Ananda Mohan Sanagavarapu |
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| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Similarity (geometry) Computer science Computation Swarm behaviour Particle swarm optimization 02 engineering and technology DNA sequencing Standard deviation chemistry.chemical_compound 020901 industrial engineering & automation chemistry 0202 electrical engineering electronic engineering information engineering Biochemical reactions 020201 artificial intelligence & image processing Algorithm DNA |
| Zdroj: | 2019 60th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS). |
| DOI: | 10.1109/itms47855.2019.8940635 |
| Popis: | DNA Sequencing is a complex problem since DNA computation depends on the biochemical reactions of DNA molecules that resulted in an improper or unwanted results. Thus, researchers are focusing to make the molecular computation for the DNA sequences design problem more consistent. Designing of DNA sequencing consists of several difficult and inconsistent designing parameters and typical optimization approaches do not perform well. As a result, a Modified Particle Swarm Optimization Algorithm (MPSO) is proposed to elucidate this problem. Four objective functions that are continuity, similarity, hairpin, and H-measure are used to evaluate this multi-objective problem. Different methods are used to explain DNA problem but to solve it with MPSO the multi-objective problem is converted into a single-objective problem. MPSO is presented to minimize the objective functions subject to two constraints. Average and Standard deviation values of the objective functions are used to calculate the efficiency of the presented method. The results obtained are compared with the other approaches and it showed that MPSO gives better performance. |
| Databáze: | OpenAIRE |
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