One challenging issue in daily solar radiation classification involves addressing the geometric differences in daily solar radiation patterns caused by geographic location and seasonal influences. A standardization me...
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Reliable modeling of river sediments transport is important as it is a defining factor of the economic viability of dams, the durability of hydroelectric-equipment, river susceptibility to pollution, suitability for n...
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Reliable modeling of river sediments transport is important as it is a defining factor of the economic viability of dams, the durability of hydroelectric-equipment, river susceptibility to pollution, suitability for navigation, and potential for aesthetics and fish habitat. The capability of a new machine learning model, fuzzy c-means based neuro-fuzzy system calibrated using the hybrid particle swarm optimization-gravitational search algorithm(ANFIS-FCM-PSOGSA) in improving the estimation accuracy of river suspended sediment loads(SSLs) is investigated in the current study. The outcomes of the proposed method were compared with those obtained using the fuzzy c-means based neuro-fuzzy system calibrated using particle swarm optimization(ANFIS-FCM-PSO), ANFIS-FCM, and sediment rating curve(SRC) models. Various input combinations involving lagged river flow(Q) and suspended sediment(S) values were used for model development. The effect of Q and S on the model's accuracy also was assessed by including the difference between lagged Q and S values as inputs. The model performance was assessed using the root mean square error(RMSE), mean absolute error(MAE), Nash-Sutcliffe Efficiency(NSE), and coefficient of determination(R2) and several graphical comparison methods. The results showed that the proposed model enhanced the prediction performance of the ANFIS-FCM-PSO(or ANFIS-FCM) models by 8.14%(1.72%), 14.7%(5.71%), 12.5%(2.27%), and 25.6%(1.86%),in terms of the RMSE, MAE, NSE and R2, respectively. The current study established the potential of the proposed ANFIS-FCM-PSOGSA model for simulation of the cumulative sediment load. The modeling results revealed the potential effects of the river flow lags on the sediment transport quantification.
Perovskite solar cells(PSCs)have attracted significant interest in the photovoltaic field because of their remarkable efficiency,low cost,and straightforward fabrication process[1].However,the long-term stability of P...
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Perovskite solar cells(PSCs)have attracted significant interest in the photovoltaic field because of their remarkable efficiency,low cost,and straightforward fabrication process[1].However,the long-term stability of PSCs remains a *** major source of instability is the low mechanical reliability of heterointerfaces[2].Specifically,a thermal expansion coefficient mismatch between adjacent functional layers and inevitable temperature variations during day/night cycles can lead to interfacial sliding and void formation.
This study focuses on the application of the YOLOv3 (You Only Look Once version 3) object detection algorithm for the analysis of concrete cracks and fatigue within Smart Cities. Concrete infrastructure plays a crucia...
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In this paper, a novel method called sub-manifolds sparsity preserving discriminant analysis is proposed for the task of image set based face recognition. The proposed method /approach aims to learn the discriminative...
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ISBN:
(纸本)9798400712715
In this paper, a novel method called sub-manifolds sparsity preserving discriminant analysis is proposed for the task of image set based face recognition. The proposed method /approach aims to learn the discriminative feature by integrating the relationship between hidden sub-manifolds in image set data. Firstly, each image set is modeled as a nonlinear manifold with a Gaussian mixture model comprising a number of Gaussian components, i.e., sub-manifolds, to handle the underlying local manifold structure. And then, it tries to preserve the sparse reconstructive relationship between these sub-manifolds when learning an embedding subspace in which the sample images within same sub-manifold and the sub-manifolds with same class label are compacted, and meanwhile the sub-manifolds with different class labels are separated. Since the sparse reconstructive relationship contains natural discriminative information, the proposed method can enhance its discriminative power for image set based face recognition. Experimental results show that the proposed method achieves better recognition performance and demonstrate its superiority over the state-of-the-art approaches.
This one-day hybrid workshop builds on previous feminist CSCW workshops to explore feminist theoretical and methodological approaches that have provided us with useful tools to see things differently and make space fo...
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Artificial intelligence (AI) permeates all fields of life, which resulted in new challenges in requirements engineering for artificial intelligence (RE4AI), e.g., the difficulty in specifying and validating requiremen...
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Construction progress monitoring plays a crucial role in ensuring the timely and efficient completion of infrastructure projects within smart cities. This paper proposes a novel approach utilizing the Deep AlexNet arc...
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On February 7, 2021, a rockfall in the Rishiganga Valley killed about 200 people. For the integration of seismic, social media, and remote sensing, a case study on this tragedy has been conducted. This study explores ...
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Unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) has received wide attention for its ability to significantly reduce latency with flexible mobile aerial nodes. However, the existing works merely consi...
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