Forward osmosis(FO), as an emerging technology, is influenced by different factors such as operating conditions,module characteristics, and membrane properties. The general aim of this study was to develop a suitable(...Forward osmosis(FO), as an emerging technology, is influenced by different factors such as operating conditions,module characteristics, and membrane properties. The general aim of this study was to develop a suitable(flexible,comprehensive, and convenient to use) computational tool which is able to simulate osmosis through an asymmetric membrane oriented in pressure retarded osmosis(PRO) mode in a wide variety of scenarios. For this purpose, an agent-based model was created in NetLogo platform, which is an easy-to-use application environment with graphical visualization abilities and well suited for modeling a complex system evolving over time. The simulation results were validated with empirical data obtained from literature and a great agreement was observed. The effect of various parameters on process performance was investigated in terms of temperature,cross-flow velocity, length of the module, pure water permeability coefficient, and structural parameter of the membrane. Results demonstrated that the increase in all parameters, except structural parameter of the membrane and the length of module led to the increase of average water flux. Moreover, nine different draw solutes were selected in order to assess the influence of net bulk osmotic pressure difference between the draw solution(DS) and feed solution(FS)(known as the driving force of FO process) on water flux. Based on the findings of this paper, the performance of FO process(PRO mode) can be efficiently evaluated using the NetL ogo platform.展开更多
This research introduces a novel approach to improve and optimize the predictive capacity of consumer purchase behaviors on e-commerce platforms. This study presented an introduction to the fundamental concepts of the...This research introduces a novel approach to improve and optimize the predictive capacity of consumer purchase behaviors on e-commerce platforms. This study presented an introduction to the fundamental concepts of the logistic regression algorithm. In addition, it analyzed user data obtained from an e-commerce platform. The original data were preprocessed, and a consumer purchase prediction model was developed for the e-commerce platform using the logistic regression method. The comparison study used the classic random forest approach, further enhanced by including the K-fold cross-validation method. Evaluation of the accuracy of the model’s classification was conducted using performance indicators that included the accuracy rate, the precision rate, the recall rate, and the F1 score. A visual examination determined the significance of the findings. The findings suggest that employing the logistic regression algorithm to forecast customer purchase behaviors on e-commerce platforms can improve the efficacy of the approach and yield more accurate predictions. This study serves as a valuable resource for improving the precision of forecasting customers’ purchase behaviors on e-commerce platforms. It has significant practical implications for optimizing the operational efficiency of e-commerce platforms.展开更多
文摘Forward osmosis(FO), as an emerging technology, is influenced by different factors such as operating conditions,module characteristics, and membrane properties. The general aim of this study was to develop a suitable(flexible,comprehensive, and convenient to use) computational tool which is able to simulate osmosis through an asymmetric membrane oriented in pressure retarded osmosis(PRO) mode in a wide variety of scenarios. For this purpose, an agent-based model was created in NetLogo platform, which is an easy-to-use application environment with graphical visualization abilities and well suited for modeling a complex system evolving over time. The simulation results were validated with empirical data obtained from literature and a great agreement was observed. The effect of various parameters on process performance was investigated in terms of temperature,cross-flow velocity, length of the module, pure water permeability coefficient, and structural parameter of the membrane. Results demonstrated that the increase in all parameters, except structural parameter of the membrane and the length of module led to the increase of average water flux. Moreover, nine different draw solutes were selected in order to assess the influence of net bulk osmotic pressure difference between the draw solution(DS) and feed solution(FS)(known as the driving force of FO process) on water flux. Based on the findings of this paper, the performance of FO process(PRO mode) can be efficiently evaluated using the NetL ogo platform.
文摘This research introduces a novel approach to improve and optimize the predictive capacity of consumer purchase behaviors on e-commerce platforms. This study presented an introduction to the fundamental concepts of the logistic regression algorithm. In addition, it analyzed user data obtained from an e-commerce platform. The original data were preprocessed, and a consumer purchase prediction model was developed for the e-commerce platform using the logistic regression method. The comparison study used the classic random forest approach, further enhanced by including the K-fold cross-validation method. Evaluation of the accuracy of the model’s classification was conducted using performance indicators that included the accuracy rate, the precision rate, the recall rate, and the F1 score. A visual examination determined the significance of the findings. The findings suggest that employing the logistic regression algorithm to forecast customer purchase behaviors on e-commerce platforms can improve the efficacy of the approach and yield more accurate predictions. This study serves as a valuable resource for improving the precision of forecasting customers’ purchase behaviors on e-commerce platforms. It has significant practical implications for optimizing the operational efficiency of e-commerce platforms.
