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A Standard Deviation Selection in Evolutionary Algorithm for Grouper Fish Feed Formulation

机译:石斑鱼饲料配方进化算法的标准偏差选择

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Malaysia is one of the major producer countries for fishery production due to its location in the equatorial environment. Grouper fish is one of the potential markets in contributing to the income of the country due to its desirable taste, high demand and high price. However, the demand of grouper fish is still insufficient from the wild catch. Therefore, there is a need to farm grouper fish to cater to the market demand. In order to farm grouper fish, there is a need to have prior knowledge of the proper nutrients needed because there is no exact data available. Therefore, in this study, primary data and secondary data are collected even though there is a limitation of related papers and 30 samples are investigated by using standard deviation selection in Evolutionary algorithm. Thus, this study would unlock frontiers for an extensive research in respect of grouper fish feed formulation. Results shown that the fitness of standard deviation selection in evolutionary algorithm is applicable. The feasible and low fitness, quick solution can be obtained. These fitness can be further predicted to minimize cost in farming grouper fish.
机译:马来西亚是由于其位于赤道环境中的渔业生产的主要生产国之一。由于其理想的味道,高需求和高价格,石斑鱼是潜在的市场之一,促进了国家的收入。然而,石斑鱼鱼的需求仍然从野生捕获中不足。因此,需要农园鱼来迎合市场需求。为了农养动物,需要先验知道所需的适当营养素,因为没有可用的确切数据。因此,在本研究中,即使在进化算法中使用标准偏差选择,也会收集主要数据和次要数据,并且通过使用标准偏差选择来研究30个样本。因此,本研究将解锁用于针对石斑鱼饲料配方的广泛研究的边疆。结果表明,在进化算法中的标准偏差选择的适应性是适用的。可以获得可行和低的健身,快速解决方案。可以进一步预测这些适应度以最大限度地减少农业石斑鱼鱼的成本。

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