• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.175-182
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• 2021

The greenhouse is a complex system. It is subject to multiple input disturbances that are highly dependent on meteorological conditions, which are generally nonlinear and have a great influence on the agricultural production. The objective of this paper is to study the fuzzy logic technique as one of the most efficient technologies to control the greenhouse. The fuzzy logic controller (FLC) was developed to activate the actuator based on a ventilator was installed in an experimental greenhouse to obtain a desired temperature of the microclimate despite the externals disturbances.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.3
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• pp.9-19
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• 2015

Internal air temperature of greenhouse is an important variable that can be influenced by the complex interaction between outside weather and greenhouse inside climate. This paper focuses on a data-based model approach to predict internal air temperature of the greenhouse. External air temperature, solar radiation, wind speed and wind direction were measured next to an experimental greenhouse supported by the Electronics and Telecommunications Research Institute and used as input variables for the model. Internal air temperature was measured at the center of three sections of the greenhouse and used as an output variable. The proposed model consisted of a transfer function including the four input variables and tested the prediction accuracy according to the sampling interval of the input variables, the orders of model polynomials and the time delay variable. As a result, a second-order model was suitable to predict the internal air temperature having the predictable time of 20-30 minutes and average errors of less than ${\pm}1K$. Afterwards mechanistic interpretation was conducted based on the energy balance equation, and it was found that the resulting model was considered physically acceptable and satisfied the physical reality of the heat transfer phenomena in a greenhouse. The proposed data-based model approach is applicable to any input variables and is expected to be useful for predicting complex greenhouse microclimate involving environmental control systems.

• 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 Rural Living Science
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• v.8 no.2
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• pp.111-117
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• 1997

In this study we tried to give a decision on propriety of working conditions, to present ideas on reducing work loads. and to grope for efficiency of agricultural works. For this we examined the actual conditions of working environment, farmer's clothes, working posture, working methods, working time, resting state, fatigue recovery methods during cultivating lettuce in the winter greenhouse. And Ive improved harmful factors that affect farmer's health by considering results of previous study and farmer's subjective sensation. And we measured, compared, and analyzed the farmer's work loads before and after improvement. The results of this study are as follows ; 1. According to examine the actual conditions of cultivating lettuce in the winter greenhouse, farmers have experienced physical and mental chronic fatigue on the basis of the hot and humid crops-centered working environment, the rough ground condition, inconsistent arrangement of working stand and sorter, heavy-weared habits. and unsuitable working posture. 2. When we improved harmful factors that affect farmer's health, conformed the positive effects on important work efficiency index such as heart rate, electromyovolume, body temperature, and microclimate inside clothing and work loads were decreased by improving the hot and humid working environment, eliminating the hillock and obstacles of working path. deliver way, arranging the working stand and sorter consistantly, decreasing the clothing weight, improving the working postures and methods as using assistant appliances, alloting the working time and sequence effectively and presenting the light gymnastic exercises and rest for fatigue restoration.

• Journal of Bio-Environment Control
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• v.1 no.2
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• pp.123-134
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• 1992

In order to verify the usability of the greenhouse for aquaculture with nutrient culture synchronously and to obtain the fundamental data fir the establishment of efficient farming technology, the characteristics of microclimate and the growth of leafy vegetables were examined. Tilapia averaged 428.6 g grew to 784 g(1.83 times) for 147 days from May 29 to Oct. 21 and fingerlings averaged 12.9 g grew by 1.37 times for 61 days from Sep. 13 to Nov. 12. The growth of vegetables such as water dropwort, leaf lettuce, Chinese cabbage, and Welsh onion in the greenhouse was better for aquaculture with nutrient culture than for nutrient culture only. Between above two greenhouses, pH and EC of nutrient solution was same but the temperature different by about 2$^{\circ}C$. Average day temperature, relative humidity, and $CO_2$ concentration were higher by 2.9$^{\circ}C$, 6%, and 200 ppm in the greenhouse for aquaculture with nutrient culture, respectively. Net assimilation rate of vegetables in the greenhouse was a little higher for aquaculture with nutrient culture than for nutrient culture only. Therefore, provided aquaculture and nutrient culture are carried out in the same greenhouse, the saving effect of heating cost as well as the additional promotive effects of vegetable and tilapia growth can be obtained.

• Journal of Bio-Environment Control
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• v.25 no.2
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• pp.123-132
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• 2016

The importance of energy saving technology for managing greenhouse was recently highlighted. For practical use of energy in greenhouse, it is necessary to simulate energy flow precisely and estimate heating/cooling loads of greenhouse. So the main purpose of this study was to develope and to validate greenhouse energy model and to estimate annual/maximum energy loads using Building Energy Simulation (BES). Field experiments were carried out in a multi-span plastic-film greenhouse in Jeju Island ($33.2^{\circ}N$, $126.3^{\circ}E$) for 2 months. To develop energy model of the greenhouse, a set of sensors was used to measure the greenhouse microclimate such as air temperature, humidity, leaf temperature, solar radiation, carbon dioxide concentration and so on. Moreover, characteristic length of plant leaf, leaf area index and diffuse non-interceptance were utilized to calculate sensible and latent heat exchange of plant. The internal temperature of greenhouse was compared to validate the greenhouse energy model. Developed model provided a good estimation for the internal temperature throughout the experiments period (coefficients of determination > 0.85, index of agreement > 0.92). After the model validation, we used last 10 years weather data to calculate energy loads of greenhouse according to growth stage of greenhouse crop. The tendency of heating/cooling loads change was depends on external weather condition and optimal temperature for growing crops at each stage. In addition, maximum heating/cooling loads of reference greenhouse were estimated to 644,014 and $756,456kJ{\cdot}hr^{-1}$, respectively.

• Horticultural Science & Technology
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• v.32 no.4
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• pp.473-483
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• 2014

In this work, the effects of shade combination, shade height and wind regime on greenhouse climate were quantified. A two-dimensional (2-D) computational fluid dynamics (CFD) model was developed based on an 11-span plastic greenhouse in eastern China for wind almost normal to the greenhouse orientation. The model was first validated with air temperature profiles measured in a compartmentalized greenhouse cultivated with mature lettuce (Lactuca sativa L., 'Yang Shan'). Next, the model was employed to investigate the effect of shade combinations on greenhouse microclimate patterns. Simulations showed similar airflow patterns in the greenhouse under different shade combinations. The temperature pattern was a consequence of convection and radiation transfer and was not significantly influenced by shade combination. The use of shade screens reduced air velocity by $0.02-0.20m{\cdot}s^{-1}$, lowered air temperature by $0.2-0.8^{\circ}C$ and raised the humidity level by 0.9-2.0% in the greenhouse. Moreover, it improved the interior climate homogeneity. The assessment of shade performance revealed that the external shade had good cooling and homogeneity performance and thus can be recommended. Furthermore, the effects of external shade height and wind regime on greenhouse climate parameters showed that external shade screens are suitable for installation within 1 m above roof level. They also demonstrated that, under external shade conditions, greenhouse temperature was reduced relative to unshaded conditions by $1.3^{\circ}C$ under a wind speed of $0.5m{\cdot}s^{-1}$, whereas it was reduced by merely $0.5^{\circ}C$ under a wind speed of $2.0m{\cdot}s^{-1}$. Therefore, external shading is more useful during periods of low wind speed.

• Journal of Bio-Environment Control
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• v.29 no.3
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• pp.285-292
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• 2020

Because the inner environment of greenhouse has a direct impact on crop production, many studies have been performed to develop technologies for controlling the environment in the greenhouse. However, it is difficult to apply the technology developed to all greenhouses because those studies were conducted through empirical experiments in specific greenhouses. It takes a lot of time and cost to develop the models that can be applicable to all greenhouse in real situation. Therefore studies are underway to solve this problem using computer-based simulation techniques. In this study, a model was developed to predict the inner environment of glass greenhouse using CFD simulation method. The developed model was validated using primary and secondary heating experiment and daytime greenhouse inner temperature data. As a result of comparing the measured and predicted value, the mean temperature and uniformity were 2.62℃ and 2.92%p higher in the predicted value, respectively. R² was 0.9628, confirming that the measured and the predicted values showed similar tendency. In the future, the model needs to improve by applying the shape of the greenhouse and the position of the inner heat exchanger for efficient thermal energy management of the greenhouse.

• Horticultural Science & Technology
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• v.29 no.5
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• pp.420-432
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• 2011

Population dynamics of greenhouse whitefly, Trialeurodes vaporariorum (Westwood), were modeled and simulated to compare the temperature effects of air and tomato leaf inside greenhouse using DYMEX model simulator (pre-programed module based simulation program developed by CSIRO, Australia). The DYMEX model simulator consisted of temperature dependent development and oviposition modules. The normalized cumulative frequency distributions of the developmental period for immature and oviposition frequency rate and survival rate for adult of greenhouse whitefly were fitted to two-parameter Weibull function. Leaf temperature on reversed side of cherry tomato leafs (Lycopersicon esculentum cv. Koko) was monitored according to three tomato plant positions (top, > 1.6 m above the ground level; middle, 0.9 - 1.2 m; bottom, 0.3 - 0.5 m) using an infrared temperature gun. Air temperature was monitored at same three positions using a Hobo self-contained temperature logger. The leaf temperatures from three plant positions were described as a function of the air temperatures with 3-parameter exponential and sigmoidal models. Data sets of observed air temperature and predicted leaf temperatures were prepared, and incorporated into the DYMEX simulator to compare the effects of air and leaf temperature on population dynamics of greenhouse whitefly. The number of greenhouse whitefly immatures was counted by visual inspection in three tomato plant positions to verify the performance of DYMEX simulation in cherry tomato greenhouse where air and leaf temperatures were monitored. The egg stage of greenhouse whitefly was not counted due to its small size. A significant positive correlation between the observed and the predicted numbers of immature and adults were found when the leaf temperatures were incorporated into DYMEX simulation, but no significant correlation was observed with the air temperatures. This study demonstrated that the population dynamics of greenhouse whitefly was affected greatly by the leaf temperatures, rather than air temperatures, and thus the leaf surface temperature should be considered for management of greenhouse whitefly in cherry tomato grown in greenhouses.

• Journal of Bio-Environment Control
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• v.6 no.3
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• pp.205-215
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• 1997

An accurate transpiration model for greenhouse tomato crop, which is liable to transpiration depression and yield loss because of low solar radiation and high humidity, could be an efficient tool for the optimum control of greenhouse climate and for the optimization of Irrigation scheduling. The purpose of this study was to develop transpiration model of greenhouse tomato and to carry out the experimental verification. The formulas to calculate the canopy transpiration and temperature simultaneously were derived from the energy balance of canopy. Transpiration and microclimate variables such as net radiation, solar radiation, humidity, canopy and air temperature, etc. were simultaneously measured to estimate parameters of model equations and to verify the suggested model. Leaf boundary layer resistance was calculated as a function of Nusselt number and stomatal diffusive resistance was parameterized by solar radiation and leaf-air vapor pressure deficit. The equation for stomatal diffusive resistance could explain more than 80％ of its variation and the calculated stomatal diffusive resistance showed good agreements with the measured values in situations independent of which the constants of the equation were estimated. The canopy net radiation calculated by Stanghellini's model with slight modification agreed well with the measured values. The present transpiration model, into which afore-mentioned component equations were assembled, was found to predict the canopy temperature, instantaneous and daily transpiration with considerable accuracy in greenhouse climates.