Computer simulations of two catching algorithms to improve the efficiency of catching fish

We try to understand the efficiency of two proposed algorithms to catch fish, and use regression analysis, to differentiate between the two models, in this paper. This study was motivated by an ever increasing demand of fish for a rising population in the UK. The output of this industry to the UK economy is substantial to encourage future research into the topic. We use regression analysis to account for standard errors in the data points obtained and calculate the errors in the intercepts for all cases. We find that the food source algorithm (a model which uses major food sources in an arbitrary lake as checkpoints for a gathering of a school of fish) is a more realistic model for catching fish. We observe that the speed of the boat explains ≈ 68% of the variations in time taken to catch the fish and that the area of the lake explains ≈ 50% of the variations in time taken to catch the fish. We also propose further study into this topic will aid the UK economy and provide a sustainable food source for future generations.

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