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Machine learning-based forecasting of ground surface settlement induced by metro shield tunneling construction.
Sci Rep
December 2024
School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan, 430070, China.
Urban rail transit systems, represented by subways, have significantly alleviated the traffic pressure brought by urbanization and have addressed issues such as traffic congestion. However, as a commonly used construction method for subway tunnels, shield tunneling inevitably disturbs the surrounding soil, leading to uneven ground surface settlement, which can impact the safety of nearby buildings. Therefore, it is crucial to promptly obtain and predict the ground surface settlement induced by shield tunneling construction to enable safety warnings and evaluations.
View Article and Find Full Text PDFUtilizing Artificial neural networks (ANN) to regulate Smart cities for sustainable Urban Development and Safeguarding Citizen rights.
Sci Rep
December 2024
Department of Architecture, Rafsanjan Branch, Islamic Azad University, Rafsanjan, Iran.
The advent of smart cities has brought about a paradigm shift in urban management and citizen engagement. By leveraging technological advancements, cities are now able to collect and analyze extensive data to optimize service delivery, allocate resources efficiently, and enhance the overall well-being of residents. However, as cities become increasingly interconnected and data-dependent, concerns related to data privacy and security, as well as citizen participation and representation, have surfaced.
View Article and Find Full Text PDFOptimizing VGG16 deep learning model with enhanced hunger games search for logo classification.
Sci Rep
December 2024
Department of Computer Science, Birzeit University, P.O. Box 14, Birzeit, West Bank, Palestine.
Accurate classification of logos is a challenging task in image recognition due to variations in logo size, orientation, and background complexity. Deep learning models, such as VGG16, have demonstrated promising results in handling such tasks. However, their performance is highly dependent on optimal hyperparameter settings, whose fine-tuning is both labor-intensive and time-consuming.
View Article and Find Full Text PDFBidirectional recurrent neural network approach for predicting cervical cancer recurrence and survival.
Sci Rep
December 2024
School of Engineering and Technology, Sunway University, No. 5, Jalan Universiti, Bandar Sunway, Petaling Jaya, 47500, Selangor Darul Ehsan, Malaysia.
Cervical cancer is a deadly disease in women globally. There is a greater chance of getting rid of cervical cancer in case of earliest diagnosis. But for some patients, there is a chance of recurrence.
View Article and Find Full Text PDFA machine learning based classifier for topological quantum materials.
Sci Rep
December 2024
Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka, 1205, Bangladesh.
Prediction and discovery of new materials with desired properties are at the forefront of quantum science and technology research. A major bottleneck in this field is the computational resources and time complexity related to finding new materials from ab initio calculations. In this work, an effective and robust deep learning-based model is proposed by incorporating persistent homology with graph neural network which offers an accuracy of and an F1 score of in classifying topological versus non-topological materials, outperforming the other state-of-the-art classifier models.
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