当前我国空气污染形势日益严峻,空气质量的急剧下降致使人们的身体健康受到严重地危害,同时也妨碍了社会和经济的可持续发展。对PM_(2.5)浓度进行预测,从而监督空气污染状况,防止严重污染的发生受到我国及世界各国人民的广泛关注。因此...当前我国空气污染形势日益严峻,空气质量的急剧下降致使人们的身体健康受到严重地危害,同时也妨碍了社会和经济的可持续发展。对PM_(2.5)浓度进行预测,从而监督空气污染状况,防止严重污染的发生受到我国及世界各国人民的广泛关注。因此提出有效的模型对PM_(2.5)浓度进行准确预测成为时下一个重要问题。本文提出了PLS-M5P(Partial Least Square-M5P)模型用于PM_(2.5)浓度预测。实验结果表明,在空气质量预测方面,与传统的预测模型如BP神经模型相比,PLS-M5P模型树有以下几个优势:(1)能提供直观的数学方程,并能够从获得的数学方程中更深入地理解预测结果。(2)使用PLS-M5P模型生成的树状图可以显示因素的重要性,并且树状图的建立能使决策者更清晰地认识预测过程。(3)建模和预测所用时间很短,而且总是收敛的。(4)预测的精度更高。展开更多
In the scope of solar energy-based electrical needs in rural tropical regions, the present article develops and confronts experimental power models from the using of manufacturer data and a new model made with the met...In the scope of solar energy-based electrical needs in rural tropical regions, the present article develops and confronts experimental power models from the using of manufacturer data and a new model made with the meteorological and electrical data acquired. These data are registered through an acquisition station around a monocrystalline photovoltaic panel, designed and realized in the scope of this work. After the acquisition of meteorological data, a choice of the most relevant meteorological variable as input vectors to express the output powers obtained was carried out. Around the Single-Diode model, seven models are performed with analytics equations, iterative methods and an optimization method with a multi-objective function to get internal parameters. The proposed experimental model is made by a combination of the solution got at STC of an iterative method, with the value of nameplate and the use of an open circuit voltage equation with experimental coefficient to predict power output in operating conditions, and it’s demonstrated more efficient. The optimization of a multi-objective function using Nonlinear Squares (NLS) through the Leveng-Marqued method to solve the parameter estimation of a PV panel has been well done and the results are useful, like classic iterative method and less time-consuming.展开更多
Dye effluents with low BOD/COD ratio and varied chemical structures are usually very recalcitrant to microbial degradation. Therefore, different process was used for the treatment of dye effluent. Heterogeneous photoc...Dye effluents with low BOD/COD ratio and varied chemical structures are usually very recalcitrant to microbial degradation. Therefore, different process was used for the treatment of dye effluent. Heterogeneous photocatalyst process has been widely used as leading green technology for dye removal. The process utilizes a semiconductor photocatalyst (such as TiO2 or ZnO) and UV light to oxidize the recalcitrant organic compounds to inorganic ions, carbon dioxide and water. Photocatalytic process needs to photorectors and hydraulic parameters play an important role in mass transfer phenomenon in photocatalytic reactors. These fundamental parameters are flow rate, relative roughness and Reynolds number. This research experimentally evaluates flow rate and artificial relative roughness in order to determine the factors influencing the removal efficiency and reaction rate. For this purpose, a cascade photocatalytic reactor is constructed which consists of similar Plexiglas plates coated by various roughness. Numerical simulation usually overcomes complex reactor models which takes reasonable cost respect to experimental study. Here, OpenFOAM software is also utilized to perform a numerical study. Regime and velocity of sewage are simulated in photocatalytic flow with/without considering relative roughness.展开更多
The most common index for representing structural condition of the pavement is the structural number.The current procedure for determining structural numbers involves utilizing falling weight deflectometer and ground-...The most common index for representing structural condition of the pavement is the structural number.The current procedure for determining structural numbers involves utilizing falling weight deflectometer and ground-penetrating radar tests,recording pavement surface deflections,and analyzing recorded deflections by back-calculation manners.This procedure has two drawbacks:falling weight deflectometer and ground-penetrating radar are expensive tests;back-calculation ways has some inherent shortcomings compared to exact methods as they adopt a trial and error approach.In this study,three machine learning methods entitled Gaussian process regression,M5P model tree,and random forest used for the prediction of structural numbers in flexible pavements.Dataset of this paper is related to 759 flexible pavement sections at Semnan and Khuzestan provinces in Iran and includes“structural number”as output and“surface deflections and surface temperature”as inputs.The accuracy of results was examined based on three criteria of R,MAE,and RMSE.Among the methods employed in this paper,random forest is the most accurate as it yields the best values for above criteria(R=0.841,MAE=0.592,and RMSE=0.760).The proposed method does not require to use ground penetrating radar test,which in turn reduce costs and work difficulty.Using machine learning methods instead of back-calculation improves the calculation process quality and accuracy.展开更多
文摘当前我国空气污染形势日益严峻,空气质量的急剧下降致使人们的身体健康受到严重地危害,同时也妨碍了社会和经济的可持续发展。对PM_(2.5)浓度进行预测,从而监督空气污染状况,防止严重污染的发生受到我国及世界各国人民的广泛关注。因此提出有效的模型对PM_(2.5)浓度进行准确预测成为时下一个重要问题。本文提出了PLS-M5P(Partial Least Square-M5P)模型用于PM_(2.5)浓度预测。实验结果表明,在空气质量预测方面,与传统的预测模型如BP神经模型相比,PLS-M5P模型树有以下几个优势:(1)能提供直观的数学方程,并能够从获得的数学方程中更深入地理解预测结果。(2)使用PLS-M5P模型生成的树状图可以显示因素的重要性,并且树状图的建立能使决策者更清晰地认识预测过程。(3)建模和预测所用时间很短,而且总是收敛的。(4)预测的精度更高。
文摘In the scope of solar energy-based electrical needs in rural tropical regions, the present article develops and confronts experimental power models from the using of manufacturer data and a new model made with the meteorological and electrical data acquired. These data are registered through an acquisition station around a monocrystalline photovoltaic panel, designed and realized in the scope of this work. After the acquisition of meteorological data, a choice of the most relevant meteorological variable as input vectors to express the output powers obtained was carried out. Around the Single-Diode model, seven models are performed with analytics equations, iterative methods and an optimization method with a multi-objective function to get internal parameters. The proposed experimental model is made by a combination of the solution got at STC of an iterative method, with the value of nameplate and the use of an open circuit voltage equation with experimental coefficient to predict power output in operating conditions, and it’s demonstrated more efficient. The optimization of a multi-objective function using Nonlinear Squares (NLS) through the Leveng-Marqued method to solve the parameter estimation of a PV panel has been well done and the results are useful, like classic iterative method and less time-consuming.
文摘Dye effluents with low BOD/COD ratio and varied chemical structures are usually very recalcitrant to microbial degradation. Therefore, different process was used for the treatment of dye effluent. Heterogeneous photocatalyst process has been widely used as leading green technology for dye removal. The process utilizes a semiconductor photocatalyst (such as TiO2 or ZnO) and UV light to oxidize the recalcitrant organic compounds to inorganic ions, carbon dioxide and water. Photocatalytic process needs to photorectors and hydraulic parameters play an important role in mass transfer phenomenon in photocatalytic reactors. These fundamental parameters are flow rate, relative roughness and Reynolds number. This research experimentally evaluates flow rate and artificial relative roughness in order to determine the factors influencing the removal efficiency and reaction rate. For this purpose, a cascade photocatalytic reactor is constructed which consists of similar Plexiglas plates coated by various roughness. Numerical simulation usually overcomes complex reactor models which takes reasonable cost respect to experimental study. Here, OpenFOAM software is also utilized to perform a numerical study. Regime and velocity of sewage are simulated in photocatalytic flow with/without considering relative roughness.
文摘The most common index for representing structural condition of the pavement is the structural number.The current procedure for determining structural numbers involves utilizing falling weight deflectometer and ground-penetrating radar tests,recording pavement surface deflections,and analyzing recorded deflections by back-calculation manners.This procedure has two drawbacks:falling weight deflectometer and ground-penetrating radar are expensive tests;back-calculation ways has some inherent shortcomings compared to exact methods as they adopt a trial and error approach.In this study,three machine learning methods entitled Gaussian process regression,M5P model tree,and random forest used for the prediction of structural numbers in flexible pavements.Dataset of this paper is related to 759 flexible pavement sections at Semnan and Khuzestan provinces in Iran and includes“structural number”as output and“surface deflections and surface temperature”as inputs.The accuracy of results was examined based on three criteria of R,MAE,and RMSE.Among the methods employed in this paper,random forest is the most accurate as it yields the best values for above criteria(R=0.841,MAE=0.592,and RMSE=0.760).The proposed method does not require to use ground penetrating radar test,which in turn reduce costs and work difficulty.Using machine learning methods instead of back-calculation improves the calculation process quality and accuracy.
