Subha M. Roy, C.M. Pareek, Rajendra Machavaram, C.K. Mukherjee
{"title":"利用混合ANN-PSO技术优化多孔池圆形阶梯梯级曝气器的曝气性能","authors":"Subha M. Roy, C.M. Pareek, Rajendra Machavaram, C.K. Mukherjee","doi":"10.1016/j.inpa.2021.09.002","DOIUrl":null,"url":null,"abstract":"<div><p>Artificial aeration system for aquaculture ponds becomes essential to meet the oxygen requirement posed by the aquatic species. The performance of an aerator is generally measured in terms of standard aeration efficiency (SAE), which is significantly affected by the different geometric and dynamic parameters of the aerator. Therefore, to enhance the aeration performance of an aerator, these parameters need to be optimized. In the present study, a perforated pooled circular stepped cascade (PPCSC) aerator was developed, and the geometric and dynamic parameters of the developed aerator were optimized using the hybrid ANN-PSO technique for maximizing its aeration efficiency. The geometric parameters include consecutive step width ratio (<em>W<sub>i-1</sub>/W<sub>i</sub></em>) and the perforation diameter to the bottom-most radius ratio (<em>d/R<sub>b</sub></em>), whereas the dynamic parameter includes the water flow rate (<em>Q</em>). A 3–6-1 ANN model coupled with particle swarm optimization (PSO) approach was used to obtain the optimum values of geometric and dynamic parameters corresponding to the maximum SAE. The optimal values of the consecutive step width ratio (<em>W<sub>i-1</sub>/W<sub>i</sub></em>), the perforation diameter to the bottom-most radius ratio (<em>d/R<sub>b</sub></em>), and the water flow rate (<em>Q</em>) for maximizing the SAE were found to be 1.15, 0.002 7 and 0.016 7 m<sup>3</sup>/s, respectively. The cross-validation results showed a deviation of 3.07 % between the predicted and experimental SAE values, thus confirming the adequacy of the proposed hybrid ANN-PSO technique.</p></div>","PeriodicalId":53443,"journal":{"name":"Information Processing in Agriculture","volume":"9 4","pages":"Pages 533-546"},"PeriodicalIF":7.7000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214317321000767/pdfft?md5=8a911d121f12c7ab663eba8a5dcc8b68&pid=1-s2.0-S2214317321000767-main.pdf","citationCount":"14","resultStr":"{\"title\":\"Optimizing the aeration performance of a perforated pooled circular stepped cascade aerator using hybrid ANN-PSO technique\",\"authors\":\"Subha M. Roy, C.M. Pareek, Rajendra Machavaram, C.K. Mukherjee\",\"doi\":\"10.1016/j.inpa.2021.09.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Artificial aeration system for aquaculture ponds becomes essential to meet the oxygen requirement posed by the aquatic species. The performance of an aerator is generally measured in terms of standard aeration efficiency (SAE), which is significantly affected by the different geometric and dynamic parameters of the aerator. Therefore, to enhance the aeration performance of an aerator, these parameters need to be optimized. In the present study, a perforated pooled circular stepped cascade (PPCSC) aerator was developed, and the geometric and dynamic parameters of the developed aerator were optimized using the hybrid ANN-PSO technique for maximizing its aeration efficiency. The geometric parameters include consecutive step width ratio (<em>W<sub>i-1</sub>/W<sub>i</sub></em>) and the perforation diameter to the bottom-most radius ratio (<em>d/R<sub>b</sub></em>), whereas the dynamic parameter includes the water flow rate (<em>Q</em>). A 3–6-1 ANN model coupled with particle swarm optimization (PSO) approach was used to obtain the optimum values of geometric and dynamic parameters corresponding to the maximum SAE. The optimal values of the consecutive step width ratio (<em>W<sub>i-1</sub>/W<sub>i</sub></em>), the perforation diameter to the bottom-most radius ratio (<em>d/R<sub>b</sub></em>), and the water flow rate (<em>Q</em>) for maximizing the SAE were found to be 1.15, 0.002 7 and 0.016 7 m<sup>3</sup>/s, respectively. The cross-validation results showed a deviation of 3.07 % between the predicted and experimental SAE values, thus confirming the adequacy of the proposed hybrid ANN-PSO technique.</p></div>\",\"PeriodicalId\":53443,\"journal\":{\"name\":\"Information Processing in Agriculture\",\"volume\":\"9 4\",\"pages\":\"Pages 533-546\"},\"PeriodicalIF\":7.7000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2214317321000767/pdfft?md5=8a911d121f12c7ab663eba8a5dcc8b68&pid=1-s2.0-S2214317321000767-main.pdf\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information Processing in Agriculture\",\"FirstCategoryId\":\"1091\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2214317321000767\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRICULTURE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Processing in Agriculture","FirstCategoryId":"1091","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214317321000767","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
Optimizing the aeration performance of a perforated pooled circular stepped cascade aerator using hybrid ANN-PSO technique
Artificial aeration system for aquaculture ponds becomes essential to meet the oxygen requirement posed by the aquatic species. The performance of an aerator is generally measured in terms of standard aeration efficiency (SAE), which is significantly affected by the different geometric and dynamic parameters of the aerator. Therefore, to enhance the aeration performance of an aerator, these parameters need to be optimized. In the present study, a perforated pooled circular stepped cascade (PPCSC) aerator was developed, and the geometric and dynamic parameters of the developed aerator were optimized using the hybrid ANN-PSO technique for maximizing its aeration efficiency. The geometric parameters include consecutive step width ratio (Wi-1/Wi) and the perforation diameter to the bottom-most radius ratio (d/Rb), whereas the dynamic parameter includes the water flow rate (Q). A 3–6-1 ANN model coupled with particle swarm optimization (PSO) approach was used to obtain the optimum values of geometric and dynamic parameters corresponding to the maximum SAE. The optimal values of the consecutive step width ratio (Wi-1/Wi), the perforation diameter to the bottom-most radius ratio (d/Rb), and the water flow rate (Q) for maximizing the SAE were found to be 1.15, 0.002 7 and 0.016 7 m3/s, respectively. The cross-validation results showed a deviation of 3.07 % between the predicted and experimental SAE values, thus confirming the adequacy of the proposed hybrid ANN-PSO technique.
期刊介绍:
Information Processing in Agriculture (IPA) was established in 2013 and it encourages the development towards a science and technology of information processing in agriculture, through the following aims: • Promote the use of knowledge and methods from the information processing technologies in the agriculture; • Illustrate the experiences and publications of the institutes, universities and government, and also the profitable technologies on agriculture; • Provide opportunities and platform for exchanging knowledge, strategies and experiences among the researchers in information processing worldwide; • Promote and encourage interactions among agriculture Scientists, Meteorologists, Biologists (Pathologists/Entomologists) with IT Professionals and other stakeholders to develop and implement methods, techniques, tools, and issues related to information processing technology in agriculture; • Create and promote expert groups for development of agro-meteorological databases, crop and livestock modelling and applications for development of crop performance based decision support system. Topics of interest include, but are not limited to: • Smart Sensor and Wireless Sensor Network • Remote Sensing • Simulation, Optimization, Modeling and Automatic Control • Decision Support Systems, Intelligent Systems and Artificial Intelligence • Computer Vision and Image Processing • Inspection and Traceability for Food Quality • Precision Agriculture and Intelligent Instrument • The Internet of Things and Cloud Computing • Big Data and Data Mining