Renuka Vinod Chimankare, Subra Das, Karmjeet Kaur, Dhiraj B. Magare
{"title":"基于变异领导者优化算法的温室小气候建模,关注花卉植物生长","authors":"Renuka Vinod Chimankare, Subra Das, Karmjeet Kaur, Dhiraj B. Magare","doi":"10.1142/s1464333223500205","DOIUrl":null,"url":null,"abstract":"Microclimate modelling in a greenhouse is complicated due to the model’s irregularity and uncertainty of variable parameters. Evaluating the greenhouse’s changing climate is challenging since the conditions are always changing. As a result, it is necessary to determine the best way to manage the microclimate for the healthy development of growing plants. In order to maximise the growth of blooming plants, a modified leader optimisation algorithm (MLA) is created in this study to control the inside environment of a greenhouse. The implementation is done using greenhouses with a double-span structure located in Punjab and Mohali in India. The recommended approach analyses a number of characteristics, including carbon dioxide (CO2) concentration, temperature, and humidity, to keep track of the greenhouse’s environment. The humidity, temperature and CO2 content of flowering plants are studied using the proposed method implemented using MATLAB tool. The evaluated parameters are compared to conventional techniques like Battle Royale Optimisation (BRO), Particle Swarm Optimisation Algorithm (PSO), and BAT algorithm (BAT). Cost and energy consumption are also calculated for both proposed and existing models. Additionally, for the microclimatic parameters, error metrics, including Mean Absolute Error (MAE), Maximum Absolute Error (MaxAE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and Standard Deviation (STD) are analysed and compared with the conventional approaches. The comparative outcomes highlight the minimal error metrics of a suggested MLA for temperature, humidity, and CO2 levels in blooming plants. The result analysis proves that the proposed MLA model is better than the previous models for predicting the proper range of CO2 concentration, suitable temperature, and perfect humidity for flowering plants. This demonstrates the effectiveness of the proposed MLA approach compared to the established methods for developing blooming plants.","PeriodicalId":35909,"journal":{"name":"Journal of Environmental Assessment Policy and Management","volume":"7 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mutated Leader Optimisation Algorithm-Based Microclimate Modelling on Greenhouse Concerning Flower Plant Growth\",\"authors\":\"Renuka Vinod Chimankare, Subra Das, Karmjeet Kaur, Dhiraj B. Magare\",\"doi\":\"10.1142/s1464333223500205\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Microclimate modelling in a greenhouse is complicated due to the model’s irregularity and uncertainty of variable parameters. Evaluating the greenhouse’s changing climate is challenging since the conditions are always changing. As a result, it is necessary to determine the best way to manage the microclimate for the healthy development of growing plants. In order to maximise the growth of blooming plants, a modified leader optimisation algorithm (MLA) is created in this study to control the inside environment of a greenhouse. The implementation is done using greenhouses with a double-span structure located in Punjab and Mohali in India. The recommended approach analyses a number of characteristics, including carbon dioxide (CO2) concentration, temperature, and humidity, to keep track of the greenhouse’s environment. The humidity, temperature and CO2 content of flowering plants are studied using the proposed method implemented using MATLAB tool. The evaluated parameters are compared to conventional techniques like Battle Royale Optimisation (BRO), Particle Swarm Optimisation Algorithm (PSO), and BAT algorithm (BAT). Cost and energy consumption are also calculated for both proposed and existing models. Additionally, for the microclimatic parameters, error metrics, including Mean Absolute Error (MAE), Maximum Absolute Error (MaxAE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and Standard Deviation (STD) are analysed and compared with the conventional approaches. The comparative outcomes highlight the minimal error metrics of a suggested MLA for temperature, humidity, and CO2 levels in blooming plants. The result analysis proves that the proposed MLA model is better than the previous models for predicting the proper range of CO2 concentration, suitable temperature, and perfect humidity for flowering plants. This demonstrates the effectiveness of the proposed MLA approach compared to the established methods for developing blooming plants.\",\"PeriodicalId\":35909,\"journal\":{\"name\":\"Journal of Environmental Assessment Policy and Management\",\"volume\":\"7 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Environmental Assessment Policy and Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1142/s1464333223500205\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Environmental Assessment Policy and Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s1464333223500205","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
Microclimate modelling in a greenhouse is complicated due to the model’s irregularity and uncertainty of variable parameters. Evaluating the greenhouse’s changing climate is challenging since the conditions are always changing. As a result, it is necessary to determine the best way to manage the microclimate for the healthy development of growing plants. In order to maximise the growth of blooming plants, a modified leader optimisation algorithm (MLA) is created in this study to control the inside environment of a greenhouse. The implementation is done using greenhouses with a double-span structure located in Punjab and Mohali in India. The recommended approach analyses a number of characteristics, including carbon dioxide (CO2) concentration, temperature, and humidity, to keep track of the greenhouse’s environment. The humidity, temperature and CO2 content of flowering plants are studied using the proposed method implemented using MATLAB tool. The evaluated parameters are compared to conventional techniques like Battle Royale Optimisation (BRO), Particle Swarm Optimisation Algorithm (PSO), and BAT algorithm (BAT). Cost and energy consumption are also calculated for both proposed and existing models. Additionally, for the microclimatic parameters, error metrics, including Mean Absolute Error (MAE), Maximum Absolute Error (MaxAE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and Standard Deviation (STD) are analysed and compared with the conventional approaches. The comparative outcomes highlight the minimal error metrics of a suggested MLA for temperature, humidity, and CO2 levels in blooming plants. The result analysis proves that the proposed MLA model is better than the previous models for predicting the proper range of CO2 concentration, suitable temperature, and perfect humidity for flowering plants. This demonstrates the effectiveness of the proposed MLA approach compared to the established methods for developing blooming plants.
期刊介绍:
The Journal of Environmental Assessment Policy and Management is an interdisciplinary, peer reviewed, international journal covering policy and decision-making relating to environmental assessment (EA) in the broadest sense. Uniquely, its specific aim is to explore the horizontal interactions between assessment and aspects of environmental management (not just the vertical interactions within the broad field of impact assessment) and thereby to identify comprehensive approaches to environmental improvement involving both qualitative and quantitative information. As the concepts associated with sustainable development mature, links between environmental assessment and management systems become all the more essential.