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Amoeba-Inspired Heuristic Search Dynamics for Exploring Chemical Reaction Paths
We propose a nature-inspired model for simulating chemical reactions in a computationally resource-saving manner. The model was developed by extending our previously proposed heuristic search algorithm, called “AmoebaSAT [Aono et al. 2013],” which was inspired by the spatiotemporal dynamics of a sin...
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| 出版年: | Orig Life Evol Biosph |
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| 主要な著者: | , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Springer Netherlands
2015
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4510922/ https://ncbi.nlm.nih.gov/pubmed/26129639 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s11084-015-9450-5 |
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