Prediction the inside environment variables in greenhouses is very important because they play a vital role in greenhouse cultivation and energy lost especially in cold and hot regions.The greenhouse environment is an...Prediction the inside environment variables in greenhouses is very important because they play a vital role in greenhouse cultivation and energy lost especially in cold and hot regions.The greenhouse environment is an uncertain nonlinear system which classical modeling methods have some problems to solve it.So the main goal of this study is to select the best method between Artificial Neural Network(ANN)and Support Vector Machine(SVM)to estimate three different variables include inside air,soil and plant temperatures(Ta,Ts,Tp)and also energy exchange in a polyethylene greenhouse in Shahreza city,Isfahan province,Iran.The environmental factors which influencing all the inside temperatures such as outside air temperature,wind speed and outside solar radiation were collected as data samples.In this research,13 different training algorithms were used for ANN models(MLPRBF).Based on K-fold cross validation and Randomized Complete Block(RCB)methodology,the best model was selected.The results showed that the type of training algorithm and kernel function are very important factors in ANN(RBF and MLP)and SVM models performance,respectively.Comparing RBF,MLP and SVM models showed that the performance of RBF to predict Ta,Tp and Ts variables is better according to small values of RMSE and MAPE and large value of R2 indices.The range of RMSE and MAPE factors for RBF model to predict Ta,Tp and Ts were between 0.07 and 0.12C and 0.28-0.50%,respectively.Generalizability and stability of the RBF model with 5-fold cross validation analysis showed that this method can use with small size of data groups.The performance of best model(RBF)to estimate the energy lost and exchange in the greenhouse with heat transfer models showed that this method can estimate the real data in greenhouse and then predict the energy lost and exchange with high accuracy.展开更多
Recently, we have investigated the hypothesis radiative demonstrating that the two penetrated thicknesses (in air and linen) are not compatible with a single energy of the protons. Furthermore, we deduced that the dis...Recently, we have investigated the hypothesis radiative demonstrating that the two penetrated thicknesses (in air and linen) are not compatible with a single energy of the protons. Furthermore, we deduced that the distribution of energy, released by the above particles, on the burial linen has not a linear trend when the body-burial linen distance changes. Now, in this article we want to deduce the I(z) relationship, between the Image Intensity of the colour produced by protons on a linen and the z distance from the source (of Protons) and the same linen. To achieve the result in an analytical form and make a comparison with the same function extracted from the Shroud, we used the empirical expression Range-Energy for protons in air of Wilson-Brobeck. Thus, we obtain a result I(z) = Im [1 − (z/R)5/9] that is different from the one extracted from the Turin Linen I(z) = IM (1 − z/R0). We have also the same information using the Range-Energy curves for protons of Rogozinski. The result is negative for the radiative hypothesis that is unable to produce the Shroud Body Image. Therefore, to investigate the above unknown process of formation, it is necessary to think about another one.展开更多
This paper presents a security constrained unit commitment(SCUC)suitable for power systems with a large share of wind energy.The deterministic spinning reserve requirement is supplemented by an adjustable fraction of ...This paper presents a security constrained unit commitment(SCUC)suitable for power systems with a large share of wind energy.The deterministic spinning reserve requirement is supplemented by an adjustable fraction of the expected shortfall from the supply of wind electric generators(WEGs),computed using the stochastic feature of wind and loosely represented in the security constraint with scenarios.The optimization tool commits and dispatches generating units while simultaneously determining the geographical procurement of the required spinning reserve as well as load-following ramping reserve,by mixed integer quadratic programming(MIQP).Case studies are used to investigate various effects of grid integration on reducing the overall operation costs associated with more wind power in the system.展开更多
基金supported by a grant(961/06)from Ramin Agriculture and Natural Resources University of Khuzestan,Iran.
文摘Prediction the inside environment variables in greenhouses is very important because they play a vital role in greenhouse cultivation and energy lost especially in cold and hot regions.The greenhouse environment is an uncertain nonlinear system which classical modeling methods have some problems to solve it.So the main goal of this study is to select the best method between Artificial Neural Network(ANN)and Support Vector Machine(SVM)to estimate three different variables include inside air,soil and plant temperatures(Ta,Ts,Tp)and also energy exchange in a polyethylene greenhouse in Shahreza city,Isfahan province,Iran.The environmental factors which influencing all the inside temperatures such as outside air temperature,wind speed and outside solar radiation were collected as data samples.In this research,13 different training algorithms were used for ANN models(MLPRBF).Based on K-fold cross validation and Randomized Complete Block(RCB)methodology,the best model was selected.The results showed that the type of training algorithm and kernel function are very important factors in ANN(RBF and MLP)and SVM models performance,respectively.Comparing RBF,MLP and SVM models showed that the performance of RBF to predict Ta,Tp and Ts variables is better according to small values of RMSE and MAPE and large value of R2 indices.The range of RMSE and MAPE factors for RBF model to predict Ta,Tp and Ts were between 0.07 and 0.12C and 0.28-0.50%,respectively.Generalizability and stability of the RBF model with 5-fold cross validation analysis showed that this method can use with small size of data groups.The performance of best model(RBF)to estimate the energy lost and exchange in the greenhouse with heat transfer models showed that this method can estimate the real data in greenhouse and then predict the energy lost and exchange with high accuracy.
文摘Recently, we have investigated the hypothesis radiative demonstrating that the two penetrated thicknesses (in air and linen) are not compatible with a single energy of the protons. Furthermore, we deduced that the distribution of energy, released by the above particles, on the burial linen has not a linear trend when the body-burial linen distance changes. Now, in this article we want to deduce the I(z) relationship, between the Image Intensity of the colour produced by protons on a linen and the z distance from the source (of Protons) and the same linen. To achieve the result in an analytical form and make a comparison with the same function extracted from the Shroud, we used the empirical expression Range-Energy for protons in air of Wilson-Brobeck. Thus, we obtain a result I(z) = Im [1 − (z/R)5/9] that is different from the one extracted from the Turin Linen I(z) = IM (1 − z/R0). We have also the same information using the Range-Energy curves for protons of Rogozinski. The result is negative for the radiative hypothesis that is unable to produce the Shroud Body Image. Therefore, to investigate the above unknown process of formation, it is necessary to think about another one.
文摘This paper presents a security constrained unit commitment(SCUC)suitable for power systems with a large share of wind energy.The deterministic spinning reserve requirement is supplemented by an adjustable fraction of the expected shortfall from the supply of wind electric generators(WEGs),computed using the stochastic feature of wind and loosely represented in the security constraint with scenarios.The optimization tool commits and dispatches generating units while simultaneously determining the geographical procurement of the required spinning reserve as well as load-following ramping reserve,by mixed integer quadratic programming(MIQP).Case studies are used to investigate various effects of grid integration on reducing the overall operation costs associated with more wind power in the system.
