[논문]개체굴 성장 데이터와 양식 FLUPSY 환경 데이터의 빅 데이터 분석

유현주; 장성욱; 정선진

doi:10.14775/ksmpe.2020.19.07.106

[국내논문] 개체굴 성장 데이터와 양식 FLUPSY 환경 데이터의 빅 데이터 분석
Big Data Analysis on Oyster Growth and FLUPSY Environment 원문보기

한국기계가공학회지 = Journal of the Korean Society of Manufacturing Process Engineers, v.19 no.7, 2020년, pp.106 - 111

유현주 (동의대학교 산업기술개발연구소) , 장성욱 (동의대학교 자동차공학과) , 정선진 ((주)씨뱅크)

Abstract ▼ AI-Helper

In the era of the fourth industrial revolution, the application of big data analysis technology is crucial in various industries. In this regard, considerable research is necessary to improve aquafarming productivity, particularly in fish culture, which is one of the primary industries in the world. In this study, a sample experiment using a flop was conducted to improve oyster productivity in fish farms, and a flush was installed in an environment similar to aquaculture farms. Thereafter, the temperature data of the water environment where the formation of burrows considerably improved were collected; the growth rate of burrow seeds was also measured. The gathered experimental data were examined by time series data analysis. Finally, a system that visualizes the analysis results based on big data is proposed. In accord with the results of this study, it is expected that more advanced research on the productivity improvement of oyster aquafarming will be performed.

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문제 정의

The purpose of this experiment was to construct a system for analyzing growth rates based on population growth data and environmental data. From the viewpoint of aquaculture industry, there is a limitation that the growth rate is not remarkably displayed in time.

제안 방법

An individual environment FLUPSY was installed to classify individual object sizes and densities for each FLUPSY, and three FLUPSYs under the same conditions were installed to create an experimental environment. In this experiment, based on the DOE (Design of Experiments), the size and density of the dens for FLUPSY were set as control factors, and three FLUPSYs with the same conditions were placed.
In this study, FLUPSY used in the aquaculture industry was constructed to construct an experimental environment. Based on the stability of the DO value provided by FLUPSY, an experiment was prepared to analyze the water temperature and the growth rate of the seed population.
In this experiment data, there are some parts where the control factor is not sufficiently controlled and the reliability of the measurement data is not secured. However, based on the scalability to Big Data, Small Data analytics was attempted, and it can be said that it was the basis for preparing more detailed experimental measurements in the analysis phase.
In order to measure the growth data of the individual oysters, after the initial set up, the weight and the size were measured seven times at a weekly interval based on the size and density, which are the control factors of the individual oyster FLUPSY. The growth rate of the individual oyster is composed of a recursive algorithm that displays the difference and the difference of the measured round based on the measured value before the measured round, and the measured round continues to the previous round of the next measured round.
An individual environment FLUPSY was installed to classify individual object sizes and densities for each FLUPSY, and three FLUPSYs under the same conditions were installed to create an experimental environment. In this experiment, based on the DOE (Design of Experiments), the size and density of the dens for FLUPSY were set as control factors, and three FLUPSYs with the same conditions were placed.
In this experiment, for the experiment of individual oyster growth, we installed flupsy on the coast of aquaculture, measured environmental data, and measured and visualized and analyzed the data of individual oysters growing in the flupsy environment.
As an application field of statistics that is used for the purpose of designing an efficient experimental method and analyzing the results, we plan an experimental method that collects information from existing variables. To solve the problem to be solved, it is planned to design a statistical analysis method for data for designing, analyzing, designing an experimental process, and collecting data. Traditional DOE introduces the principles of randomization, blocking, and replication, and experiment planning using these principles has been generally used.

참고문헌 (18)

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상세보기
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상세보기
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상세보기
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[국내논문] 개체굴 성장 데이터와 양식 FLUPSY 환경 데이터의 빅 데이터 분석
Big Data Analysis on Oyster Growth and FLUPSY Environment 원문보기

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[국내논문] 개체굴 성장 데이터와 양식 FLUPSY 환경 데이터의 빅 데이터 분석 Big Data Analysis on Oyster Growth and FLUPSY Environment 원문보기

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[국내논문] 개체굴 성장 데이터와 양식 FLUPSY 환경 데이터의 빅 데이터 분석
Big Data Analysis on Oyster Growth and FLUPSY Environment 원문보기

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