Exploring the Suitability of a Genetic Algorithm as Tool for Boosting Efficiency in Monte Carlo Estimation of Leaf Area of Eelgrass
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Springer International Publishing
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http://link.springer.com/content/pdf/10.1007/978-3-319-17747-2_23
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Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. On the suitability of an allometric proxy for nondestructive estimation of average leaf dry weight in eelgrass shoots I: sensitivity analysis and examination of the influences of data quality, analysis method, and sample size on precision;Theoretical Biology and Medical Modelling;2018-03-06
2. A Takagi–Sugeno-Kang Fuzzy Model Formalization of Eelgrass Leaf Biomass Allometry with Application to the Estimation of Average Biomass of Leaves in Shoots: Comparing the Reproducibility Strength of the Present Fuzzy and Related Crisp Proxies;Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications;2018
3. On the Use of Parallel Genetic Algorithms for Improving the Efficiency of a Monte Carlo-Digital Image Based Approximation of Eelgrass Leaf Area I: Comparing the Performances of Simple and Master-Slaves Structures;Nature-Inspired Design of Hybrid Intelligent Systems;2016-12-10
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