Mutated Leader Optimisation Algorithm-Based Microclimate Modelling on Greenhouse Concerning Flower Plant Growth

Q1 Social Sciences
Renuka Vinod Chimankare, Subra Das, Karmjeet Kaur, Dhiraj B. Magare
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引用次数: 0

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.
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
由于模型的不规则性和可变参数的不确定性,温室中的小气候建模非常复杂。评估温室的气候变化很具挑战性,因为条件总是在不断变化。因此,有必要确定管理小气候的最佳方法,以促进植物健康生长。为了最大限度地促进开花植物的生长,本研究创建了一种改进的领导者优化算法(MLA)来控制温室内部环境。实施过程中使用了位于印度旁遮普和莫哈里的双跨结构温室。推荐的方法分析了一系列特征,包括二氧化碳(CO2)浓度、温度和湿度,以跟踪温室的环境。使用 MATLAB 工具实施的建议方法对开花植物的湿度、温度和二氧化碳含量进行了研究。所评估的参数与传统技术(如大逃杀优化算法 (BRO)、粒子群优化算法 (PSO) 和 BAT 算法 (BAT))进行了比较。同时还计算了拟议模型和现有模型的成本和能耗。此外,还分析了微气候参数的误差指标,包括平均绝对误差 (MAE)、最大绝对误差 (MaxAE)、均方误差 (MSE)、均方根误差 (RMSE) 和标准偏差 (STD),并与传统方法进行了比较。比较结果突出显示了建议的 MLA 对开花植物的温度、湿度和二氧化碳水平的最小误差指标。结果分析证明,在预测开花植物的二氧化碳浓度、适宜温度和完美湿度的适当范围方面,建议的 MLA 模型优于之前的模型。这表明,与现有的开花植物培育方法相比,建议的 MLA 方法非常有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Environmental Assessment Policy and Management
Journal of Environmental Assessment Policy and Management Social Sciences-Geography, Planning and Development
CiteScore
7.00
自引率
0.00%
发文量
18
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.
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