用于绘制鲶鱼养殖生物絮团池塘水质级别图的马姆达尼模糊推理系统

Herryawan Pujiharsono, D. Kurnianto
{"title":"用于绘制鲶鱼养殖生物絮团池塘水质级别图的马姆达尼模糊推理系统","authors":"Herryawan Pujiharsono, D. Kurnianto","doi":"10.14710/jtsiskom.8.2.2020.84-88","DOIUrl":null,"url":null,"abstract":"The government has launched a program to increase the production of catfish by using biofloc ponds. The biofloc ponds can maintain the quality of water biologically to maximize the growth of fish. However, the level of water quality monitoring is generally only divided into good or bad categories so that it cannot represent the condition of fish growth. Therefore, this study aims to get the level of water quality (0–100 %) using the Mamdani fuzzy inference system (FIS) algorithm based on pH, temperature, and dissolved oxygen (DO). The level of water quality was correlated based on catfish growth conditions. The results showed that the range of values of the water quality level for each condition of catfish growth was 100 % for normal-living fish, 83–99 % for stunted fish growth, and < 83% for threatened fish. The FIS algorithm had 89.92 % of accuracy.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":"26 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mamdani fuzzy inference system for mapping water quality level of biofloc ponds in catfish cultivation\",\"authors\":\"Herryawan Pujiharsono, D. Kurnianto\",\"doi\":\"10.14710/jtsiskom.8.2.2020.84-88\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The government has launched a program to increase the production of catfish by using biofloc ponds. The biofloc ponds can maintain the quality of water biologically to maximize the growth of fish. However, the level of water quality monitoring is generally only divided into good or bad categories so that it cannot represent the condition of fish growth. Therefore, this study aims to get the level of water quality (0–100 %) using the Mamdani fuzzy inference system (FIS) algorithm based on pH, temperature, and dissolved oxygen (DO). The level of water quality was correlated based on catfish growth conditions. The results showed that the range of values of the water quality level for each condition of catfish growth was 100 % for normal-living fish, 83–99 % for stunted fish growth, and < 83% for threatened fish. The FIS algorithm had 89.92 % of accuracy.\",\"PeriodicalId\":56231,\"journal\":{\"name\":\"Jurnal Teknologi dan Sistem Komputer\",\"volume\":\"26 3\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Teknologi dan Sistem Komputer\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14710/jtsiskom.8.2.2020.84-88\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Teknologi dan Sistem Komputer","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14710/jtsiskom.8.2.2020.84-88","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

政府已启动一项计划,利用生物絮凝池提高鲶鱼产量。生物絮团池塘可以从生物角度保持水质,最大限度地促进鱼类生长。然而,水质监测水平一般只分为好坏两类,无法代表鱼类的生长状况。因此,本研究旨在使用基于 pH 值、温度和溶解氧(DO)的马姆达尼模糊推理系统(FIS)算法来获得水质水平(0-100%)。水质水平与鲶鱼的生长条件相关联。结果表明,鲶鱼生长的各种条件下的水质水平值范围是:正常生活的鱼类为 100%,生长迟缓的鱼类为 83-99%,受威胁的鱼类为小于 83%。FIS 算法的准确率为 89.92%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mamdani fuzzy inference system for mapping water quality level of biofloc ponds in catfish cultivation
The government has launched a program to increase the production of catfish by using biofloc ponds. The biofloc ponds can maintain the quality of water biologically to maximize the growth of fish. However, the level of water quality monitoring is generally only divided into good or bad categories so that it cannot represent the condition of fish growth. Therefore, this study aims to get the level of water quality (0–100 %) using the Mamdani fuzzy inference system (FIS) algorithm based on pH, temperature, and dissolved oxygen (DO). The level of water quality was correlated based on catfish growth conditions. The results showed that the range of values of the water quality level for each condition of catfish growth was 100 % for normal-living fish, 83–99 % for stunted fish growth, and < 83% for threatened fish. The FIS algorithm had 89.92 % of accuracy.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
6
审稿时长
6 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信