• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.24-30
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• 2024

This paper investigates the identification and modeling of a climate greenhouse. Given real climate data from greenhouse installed in the LAPER laboratory in Tunisia, the objective of this paper is to propose a solution of the problem of nonlinear time variant inputs and outputs of greenhouse internal climate. Based on fuzzy logic technique combined with least mean squares (lms) a robust greenhouse climate model for internal temperature prediction is proposed. The simulation results are presented to demonstrate the effectiveness of the identification approach and the power of the implemented Takagi-Sugeno Fuzzy model based Algorithm.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.135-135
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• 2017

Greenhouse have been developed to provide the plants with good environmental conditions for cultivation crop, two major factors of which are the inside air temperature and humidity. The inside temperature are influenced by the heating systems, ventilators and for systems among others, which in turn are geverned by some type of controller. Likewise, humidity environment is the result of complex mass exchanges between the inside air and the several elements of the greenhouse and the outside boundaries. Most of the existing models are based on the energy balance method and heat balance equation for modelling the heat and mass fluxes and generating dynamic elements. However, greenhouse are classified as complex system, and need to make a sophisticated modeling. Furthermore, there is a difficulty in using classical control methods for complex process system due to the process are non linear and multi-output(MIMO) systems. In order to predict the time evolution of conditions in certain greenhouse as a function, we present here to use of recurrent neural networks(RNN) which has been used to implement the direct dynamics of the inside temperature and inside humidity of greenhouse. For the training, we used algorithm of a backpropagation Through Time (BPTT). Because the environmental parameters are shared by all time steps in the network, the gradient at each output depends not only on the calculations of the current time step, but also the previous time steps. The training data was emulated to 13 input variables during March 1 to 7, and the model was tested with database file of March 8. The RMSE of results of the temperature modeling was $0.976^{\circ}C$, and the RMSE of humidity simulation was 4.11%, which will be given to prove the performance of RNN in prediction of the greenhouse environment.

• Korean Journal of Agricultural Science
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• v.41 no.4
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• pp.455-460
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• 2014

In this study, structural behavior of plastic greenhouse foundation was investigated using rational finite element modeling for structures which have different material properties each other. Because the concrete foundation of plastic greenhouse and soil which surround and support the concrete foundation have very different material property, the boundary between two structures were modeled by a interface element. The interface element was able to represent sliding, separation, uplift and re-bonding of the boundary between concrete foundation and soil. The results of static and dynamic analysis showed that horizontal and vertical displacement of concrete foundation displayed a decreasing tendency with increasing depth of foundation. The second frequency from modal analysis of structure including foundation and soil was estimate to closely related with wind load.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.1
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• pp.7-15
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• 2017

This paper presents the results of the parametric study to investigate the effects of several analysis modeling parameters such as support conditions, member connectivities and cable member stiffness on the main mode shapes and natural frequencies of a representative disaster resilient greenhouse structure. In addition, an ambient vibration test was performed on the representative greenhouse structure and its main mode shapes and natural frequencies were obtained. By comparing the experimental and analysis results, a proper analysis modeling method of the representative greenhouse structure was proposed.

• Journal of the Korean Solar Energy Society
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• v.21 no.3
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• pp.51-60
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• 2001

A greenhouse equipped with latent heat storage system was built to obtain various thermal properties, such as greenhouse air temperature, soil surface temperature, energy flow in latent heat storage, etc., which could be used in validation of greenhouse numerical model to be developed in this study. This numerical model expressed with Newton-Raphson method was programed by C-language and utilized to simulate greenhouse thermal behavior. Greenhouse air temperature and soil surface temperature predicted by the greenhouse model developed in this study were very close to the measured data obtained through almost 3 years of experiment. Therefore, it is concluded that the greenhouse model developed and verified by measured data could be utilized for simulating various thermal behaviors of greenhouses equipped with latent heat storage system to be used for energy saving purposes.

• Proceedings of the Korean Society of Applied Entomolohy Conference
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• 2005.05a
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• pp.92-92
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• 2005

• Proceedings of the Korean Society of Applied Entomolohy Conference
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• 2005.05a
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• pp.93-93
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• 2005

• Journal of Energy Engineering
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• v.28 no.4
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• pp.13-18
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• 2019

The high energy penalty in amine-based post-combustion CO₂ capture process is hampering its industrial scale application. An advanced process is designed by intensive heat integration within the conventional process to reduce the stripper duty. The study presents the technical feasibility for stripper duty reduction by intensive heat integration in CO₂ capture process. A rigorous rate-based model has been used in Aspen Plus® to simulate conventional and advanced process for a 300 MW coal-based power plant. Several design and operational parameters like split ratio, stripper inter-heater location and flowrate were studied to find the optimum values. The results show that advanced configuration with heat integration can reduces the stripper heat by 14%.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.6
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• pp.912-921
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• 2006

This study examines greenhouse gas reduction potentials in cement manufacturing industry of Korea. An energy system model in the MARKAL (MARKet ALlocation) modeling framework was used in order to identify appropriate energy technologies and to quantify their possible implications In terms of greenhouse gas reduction. The model is characterized as mathematical tool for the long term energy system analysis provides an useful informations on technical assessment. Four scenarios are developed that covers the ti me span from 2000 to 2020. Being technology as a fundamental driving factor of the evolution of energy systems, it is essential to study the basic mechanisms of technological change and its role in developing more efficient, productive and clean energy systems. For this reasons, the learning curves on technologies for greenhouse gas reduction is specially considered. The analysis in this study shows that it is not easy to mitigate greenhouse gas with low cost in cement manufacturing industry under the current cap and trade method of Kyoto protocol.

• Korean Management Science Review
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• v.31 no.1
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• pp.41-48
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• 2014

This study presents a bottom-up approach for analyzing greenhouse gas (GHG) emissions for the shipbuilding industry in Korea. The overall procedures for deriving GHG emissions from the Korean shipbuilding industry are presented. Based on the long-term forecast on energy demands of the Korean shipbuilding industry, reference energy system (RES) and energy balance (EB) for the shipbuilding process are derived for bottom-up modeling.