Milkfish Feed Optimization Using Adaptive Particle Swarm Optimization (PSO) Algorithm

被引：0

作者：

Ahmadie, Beryl Labique ^{[1
]}

Luqyana, Wanda Athira ^{[1
]}

Mahmudy, Wayan Firdaus ^{[1
]}

Arifando, Rio ^{[1
]}

机构：

[1] Univ Brawijaya, Fac Comp Sci, Malang, Indonesia

来源：

PROCEEDINGS OF 2019 4TH INTERNATIONAL CONFERENCE ON SUSTAINABLE INFORMATION ENGINEERING AND TECHNOLOGY (SIET 2019) | 2019年

关键词：

Milkfish; Adaptive Particle Swarm Optimization; Evolutionary Computing;

D O I：

10.1109/siet48054.2019.8986094

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Milkfish is a cultivation commodity that contributes quite significantly on a national scale. But in practice, milkfish cultivation requires a large number of production costs, especially in the provision of fish feed. This research will discuss how to optimize the composition of milkfish feed, minimize costs without lowering production yields, and still pay attention to the nutritional needs of milkfish cultivation. The optimization method, Particle Swarm Optimization (PSO) is applied to the formulation process and the composition of milkfish feed to meet the nutritional needs of fish with minimal cost. Improvements to the PSO resulted in Adaptive Particle Swarm Optimization (APSO). This improvement conducted to strengthen PSO's ability to explore broad areas of search for solutions efficiently. The results of computational analysis prove that APSO produces a better solution than PSO.

引用

页码：28 / 32

页数：5

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