Development of Decision Support System (DSS) for Greenhouse Ventilation and Cooling Control Article Swipe
YOU?
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· 2022
· Open Access
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· DOI: https://doi.org/10.36877/aafrj.a0000369
The confined heat created by the sunlight and ambient temperature is one of the obstacles to greenhouses in the tropics. A conservatory in tropical regions thus requires a proper ventilation and cooling system to provide an ideal greenhouse temperature to support crop production. The main objective of this study is to develop a Decision Support System (DSS) for optimum greenhouse ventilation and cooling control. An equation model to predict the temperature inside was developed by considering heat generation and heat loss inside the greenhouse. The accuracy of the equation model was validated with secondary data from the on-field greenhouse by statistical evaluation metrics. The statistical evaluation proved that the equation model is good with 2.11°C of Root Mean Square Error (RMSE), 6.22% of Percent BIAS (PBIAS) and 0.94 of Nash-Sutcliffe efficiency (NSE) value. A DSS using Microsoft Excel with Visual Basic for Applications (VBA) is developed based on the equation model to provide the ventilation and cooling system information. Input required for the DSS is a climatic condition, dimension and covering greenhouse material. The output of the DSS is the temperature inside the greenhouse, natural ventilation design, forced ventilation, active cooling system design using an evaporative pad and fan, and fogging system. The DSS can be used as an approach for ventilation and cooling design recommendation for the optimum temperature inside the greenhouse.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.36877/aafrj.a0000369
- https://journals.hh-publisher.com/index.php/AAFRJ/article/download/578/463
- OA Status
- diamond
- Cited By
- 3
- References
- 14
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4388842022
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4388842022Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.36877/aafrj.a0000369Digital Object Identifier
- Title
-
Development of Decision Support System (DSS) for Greenhouse Ventilation and Cooling ControlWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-10-28Full publication date if available
- Authors
-
Diyana Jamaludin, Aini Amini Mohd Shukri, M Saufi M Kassim, Muhammad Hazwan HamzahList of authors in order
- Landing page
-
https://doi.org/10.36877/aafrj.a0000369Publisher landing page
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https://journals.hh-publisher.com/index.php/AAFRJ/article/download/578/463Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
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https://journals.hh-publisher.com/index.php/AAFRJ/article/download/578/463Direct OA link when available
- Concepts
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Greenhouse, Evaporative cooler, Environmental science, Water cooling, Ventilation (architecture), Mean squared error, Simulation, Meteorology, Computer science, Mathematics, Engineering, Statistics, Mechanical engineering, Geography, Horticulture, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 3Per-year citation counts (last 5 years)
- References (count)
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14Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.Decision | 53 |
| abstract_inverted_index.accuracy | 85 |
| abstract_inverted_index.approach | 209 |
| abstract_inverted_index.climatic | 166 |
| abstract_inverted_index.confined | 1 |
| abstract_inverted_index.control. | 63 |
| abstract_inverted_index.covering | 170 |
| abstract_inverted_index.equation | 65, 88, 109, 149 |
| abstract_inverted_index.metrics. | 102 |
| abstract_inverted_index.on-field | 97 |
| abstract_inverted_index.required | 160 |
| abstract_inverted_index.requires | 26 |
| abstract_inverted_index.sunlight | 6 |
| abstract_inverted_index.tropical | 23 |
| abstract_inverted_index.tropics. | 19 |
| abstract_inverted_index.Microsoft | 136 |
| abstract_inverted_index.developed | 73, 145 |
| abstract_inverted_index.dimension | 168 |
| abstract_inverted_index.material. | 172 |
| abstract_inverted_index.objective | 45 |
| abstract_inverted_index.obstacles | 14 |
| abstract_inverted_index.secondary | 93 |
| abstract_inverted_index.validated | 91 |
| abstract_inverted_index.condition, | 167 |
| abstract_inverted_index.efficiency | 130 |
| abstract_inverted_index.evaluation | 101, 105 |
| abstract_inverted_index.generation | 77 |
| abstract_inverted_index.greenhouse | 37, 59, 98, 171 |
| abstract_inverted_index.considering | 75 |
| abstract_inverted_index.evaporative | 195 |
| abstract_inverted_index.greenhouse, | 183 |
| abstract_inverted_index.greenhouse. | 83, 222 |
| abstract_inverted_index.greenhouses | 16 |
| abstract_inverted_index.production. | 42 |
| abstract_inverted_index.statistical | 100, 104 |
| abstract_inverted_index.temperature | 9, 38, 70, 180, 219 |
| abstract_inverted_index.ventilation | 29, 60, 154, 185, 211 |
| abstract_inverted_index.Applications | 142 |
| abstract_inverted_index.conservatory | 21 |
| abstract_inverted_index.information. | 158 |
| abstract_inverted_index.ventilation, | 188 |
| abstract_inverted_index.Nash-Sutcliffe | 129 |
| abstract_inverted_index.recommendation | 215 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 96 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.7746383 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |