Optimization Algorithm Inspired by Seawater Conductivity Variation
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| Natura: | Recurso digital |
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Zenodo
2025
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| _version_ | 1866902116950343680 |
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| author | Zhang, Jincheng |
| author_facet | Zhang, Jincheng |
| contents | <p><span>Seawater electrical conductivity (SEC) is a key physical quantity that describes the electrical conductivity of seawater. Its variations are complexly influenced by temperature, salinity, and pressure. This paper proposes an optimization algorithm inspired by variations in seawater conductivity to simulate the search behavior of seawater microclusters under gradient drift, surge disturbances, local diffusion, and conductive-induced attraction mechanisms. The algorithm systematically describes the position update formula and fitness evaluation method for search particles through mathematical modeling, and proposes an innovative conductive-induced attraction mechanism that enables groups to form search clusters based on conductivity similarity, achieving efficient global convergence. This paper systematically expounds on the algorithm's design principles, mathematical formulas, and update mechanisms, providing a new heuristic approach for continuous optimization problems.</span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17182985 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Optimization Algorithm Inspired by Seawater Conductivity Variation Zhang, Jincheng <p><span>Seawater electrical conductivity (SEC) is a key physical quantity that describes the electrical conductivity of seawater. Its variations are complexly influenced by temperature, salinity, and pressure. This paper proposes an optimization algorithm inspired by variations in seawater conductivity to simulate the search behavior of seawater microclusters under gradient drift, surge disturbances, local diffusion, and conductive-induced attraction mechanisms. The algorithm systematically describes the position update formula and fitness evaluation method for search particles through mathematical modeling, and proposes an innovative conductive-induced attraction mechanism that enables groups to form search clusters based on conductivity similarity, achieving efficient global convergence. This paper systematically expounds on the algorithm's design principles, mathematical formulas, and update mechanisms, providing a new heuristic approach for continuous optimization problems.</span></p> |
| title | Optimization Algorithm Inspired by Seawater Conductivity Variation |
| url | https://doi.org/10.5281/zenodo.17182985 |