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101–150 von 156 Ergebnissen
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    Flexible Stochastic Frontier Approach to Predict Spot Speed in Two-Lane Highways

    Couto, António | Online Contents | 2016
    Schlagwörter: Learning models (Stochastic processes)

    Pore Structure Identification Method for Pervious Concrete Based on Improved UNet and Fusion Algorithm

    Yu, Fan / Li, Kailang / Zhang, Hua et al. | Springer Verlag | 2023
    Schlagwörter: Deep learning

    Transportation Mode Detection by Using Smartphones and Smartwatches with Machine Learning

    Hasan, Raed Abdullah / Irshaid, Hafez / Alhomaidat, Fadi et al. | Springer Verlag | 2022
    Schlagwörter: Machine learning

    Generalized Linear Models to Identify the Impact of Road Geometric Design Features on Crash Frequency in Rural Roads

    Khedher, Moataz Bellah Ben / Yun, Dukgeun | Springer Verlag | 2022
    Schlagwörter: Machine learning

    Flood Hazard Rating Prediction for Urban Areas Using Random Forest and LSTM

    Kim, Hyun Il / Kim, Byung Hyun | Springer Verlag | 2020
    Schlagwörter: Machine learning

    Prediction of the Impact of Typhoons on Transportation Networks with Support Vector Regression

    Hu, Ta-Yin | Online Contents | 2015
    Schlagwörter: Machine learning

    SEMA: A Site Equipment Management Assistant for Construction Management

    Tsai, Meng-Han / Yang, Cheng-Hsuan / Wang, Chen-Hsuan et al. | Springer Verlag | 2022
    Schlagwörter: Deep learning

    Enhancing Vibration-based Damage Assessment with 1D-CNN: Parametric Studies and Field Applications

    Park, Soyeon / Kim, Sunjoong | Springer Verlag | 2024
    Schlagwörter: Deep Learning

    Predicting the Compressive Strength and the Effective Porosity of Pervious Concrete Using Machine Learning Methods

    Le, Ba-Anh / Vu, Viet-Hung / Seo, Soo-Yeon et al. | Springer Verlag | 2022
    Schlagwörter: Machine learning

    Development of Point Cloud Data-Denoising Technology for Earthwork Sites Using Encoder-Decoder Network

    Choi, Yeongjun / Park, Suyeul / Kim, Seok | Springer Verlag | 2022
    Schlagwörter: Deep learning

    Deep Learning-Based Prediction of Fire Occurrence with Hydroclimatic Condition and Drought Phase over South Korea

    Sung, Jang Hyun / Ryu, Young / Seong, Kee-Won | Springer Verlag | 2022
    Schlagwörter: Deep learning

    High Speed Rail Learning System (HSRLS) – Taking Advantage of Online Technologies in Railway Education

    Freier Zugriff
    Pasi T. Lautala, Ph.D., P.E. | DOAJ | 2015
    Schlagwörter: Web-based teaching and learning

    Inferring Trip Destination Purposes for Trip Records Collected through Smartphone Apps

    Liu, Yicong / Miller, Eric J. / Habib, Khandker Nurul | ASCE | 2023
    Schlagwörter: Machine learning model

    A Framework for Improving Object Recognition of Structural Components in Construction Site Photos Using Deep Learning Approaches

    Park, Sang Mi / Lee, Jae Hee / Kang, Leen Seok | Springer Verlag | 2023
    Schlagwörter: Deep learning

    Machine Learning Based Compressive Strength Prediction Model for CFRP-confined Columns

    Yu, Yong / Hu, Tianyu | Springer Verlag | 2024
    Schlagwörter: Machine learning

    Explainable Boosting Machine for Predicting Wind Shear-Induced Aircraft Go-around based on Pilot Reports

    Khattak, Afaq / Chan, Pak-wai / Chen, Feng et al. | Springer Verlag | 2023
    Schlagwörter: Machine learning

    Development of Data-based Hierarchical Learning Model for Predicting Condition Rating of Bridge Members over Time

    Choi, Youngjin / Kong, Jungsik | Springer Verlag | 2023
    Schlagwörter: Deep learning

    A Hybrid Feature Selection-multidimensional LSTM Framework for Deformation Prediction of Super High Arch Dams

    Cao, Enhua / Bao, Tengfei / Li, Hui et al. | Springer Verlag | 2022
    Schlagwörter: Deep learning

    Shrinkage Crack Detection in Expansive Soil using Deep Convolutional Neural Network and Transfer Learning

    Andrushia, A. Diana / Neebha, T. Mary / Umadevi, S. et al. | Springer Verlag | 2022
    Schlagwörter: Deep learning

    Structural Deformation Sensing Based on Distributed Optical Fiber Monitoring Technology and Neural Network

    Hou, Gong-Yu / Li, Zi-Xiang / Wang, Kai-Di et al. | Springer Verlag | 2021
    Schlagwörter: Machine learning

    What is the Impact of COVID-19 on Residential Water Use?

    Sung, Jang Hyun / Chung, Eun-Sung | Springer Verlag | 2023
    Schlagwörter: Deep learning

    Internal Defect Detection of Structures Based on Infrared Thermography and Deep Learning

    Deng, Lu / Zuo, Hui / Wang, Wei et al. | Springer Verlag | 2023
    Schlagwörter: Deep learning

    Semi-Supervised Land Cover Classification of Remote Sensing Imagery Using CycleGAN and EfficientNet

    Kwak, Taehong / Kim, Yongil | Springer Verlag | 2023
    Schlagwörter: Semi-supervised learning

    Prediction of Asphalt Pavement Fatigue Damage of Expressway Based on Deep Learning

    Tan, Xuxiang / Sun, Huadong / Nan, Feng | Springer Verlag | 2020
    Schlagwörter: Deep learning

    Presenting a Hybrid Scheme of Machine Learning Combined with Metaheuristic Optimizers for Predicting Final Cost and Time of Project

    Bakhshi, Reza / Moradinia, Sina Fard / Jani, Rasool et al. | Springer Verlag | 2022
    Schlagwörter: Hybrid machine learning

    A Controller Algorithm (ILC) for the Variable Differential Pressure Control of Freezing Water in a Central Air Conditioning System

    Ren, Qingchang / Jiang, Hongmei | Springer Verlag | 2019
    Schlagwörter: Iterative learning controller algorithm (ILC)

    Investigation of Meta-heuristics Algorithms in ANN Streamflow Forecasting

    Wei, Yaxing / Hashim, Huzaifa / Chong, K. L. et al. | Springer Verlag | 2023
    Schlagwörter: Machine learning

    Effectiveness of an Immersive VR System for Construction Site Planning Education

    Wang, Kun-Chi / Hsu, Liang-Yu | Springer Verlag | 2024
    Schlagwörter: Learning effect evaluation

    Railway Maintenance Management Using a Stochastic Geometrical Degradation Model

    Golroo, Amir | Online Contents | 2016
    Schlagwörter: Learning models (Stochastic processes)

    Crack Detection of the Urban Underground Utility Tunnel Based on Residual Feature Pyramid Attention Network

    Zhou, Yuan / Li, Chengwei / Wang, Shoubin et al. | Springer Verlag | 2024
    Schlagwörter: Residual learning

    Do Perceptions of Hydrogen Energy Effect on Vehicle Preference? A Learning-Based Model Approach

    Kim, Woojin / Kim, Junghwa / Jang, Jeong Ah et al. | Springer Verlag | 2023
    Schlagwörter: Machine learning

    Effects of user equilibrium assumptions on network traffic pattern

    Kim, Hyunmyung / Oh, Jun-Seok / Jayakrishnan, R. | Springer Verlag | 2009
    Schlagwörter: inductive learning

    Sequential Prediction of the TBM Tunnelling Attitude Based on Long-Short Term Memory with Mechanical Movement Principle

    Wang, Ruirui / Xiao, Yuhang / Guo, Qian et al. | Springer Verlag | 2024
    Schlagwörter: Deep learning

    Short-Term Holiday Travel Demand Prediction for Urban Tour Transportation: A Combined Model Based on STC-LSTM Deep Learning Approach

    Li, Wanying / Guan, Hongzhi / Han, Yan et al. | Springer Verlag | 2022
    Schlagwörter: Deep learning

    Four Decades of Computing in Civil Engineering

    Adeli, Hojjat | Springer Verlag | 2019
    Schlagwörter: machine learning

    Attendance and Security System Based on Building Video Surveillance

    Sun, Kailai / Zhao, Qianchuan / Zou, Jianhong et al. | Springer Verlag | 2019
    Schlagwörter: Deep learning

    Determinants of Electricity Consumption of Energy-Vulnerable Group Using Ensemble Gradient-Boosting Algorithm

    Kim, Hyunsoo / Kwon, Youngwoo / Choi, Yeol | Springer Verlag | 2022
    Schlagwörter: Machine learning

    A Machine Learning Based Method for Real-Time Queue Length Estimation Using License Plate Recognition and GPS Trajectory Data

    Liu, Dongbo / An, Chengchuan / Yasir, Muhammad et al. | Springer Verlag | 2022
    Schlagwörter: Machine learning

    Training Pattern-Recognition Machines

    A. G. Arkadev / E. M. Braverman | NTIS | 1966
    Schlagwörter: Learning machines

    Prediction of buckling coefficient of stiffened plate girders using deep learning algorithm

    Papazafeiropoulos, George / Vu, Quang-Viet / Truong, Viet-Hung et al. | Springer Verlag | 2019
    Schlagwörter: deep learning

    Data-Driven Approach for the Rapid Simulation of Urban Flood Prediction

    Kim, Hyun Il / Han, Kun Yeun | Springer Verlag | 2020
    Schlagwörter: Machine learning

    Integrated YOLO and CNN Algorithms for Evaluating Degree of Walkway Breakage

    Choi, Min Je / Ku, Dong Gyun / Lee, Seung Jae | Springer Verlag | 2022
    Schlagwörter: Image deep learning

    Application of Convolution Neural Network for Adaptive Traffic Controller System

    Ahmed, Muaid Abdulkareem Alnazir / Khoo, Hooi Ling / Ng, Oon-Ee | Springer Verlag | 2022
    Schlagwörter: Deep reinforcement learning

    A Machine Learning Tool for Pavement Design and Analysis

    Yang, Guangwei / Mahboub, Kamyar C. / Renfro, Ryan L. et al. | Springer Verlag | 2023
    Schlagwörter: Machine learning

    A Possibility of AI Application on Mode-choice Prediction of Transport Users in Hanoi

    Thanh, Truong Thi My / Ly, Hai-Bang / Pham, Binh Thai | Springer Verlag | 2019
    Schlagwörter: Machine learning

    Spanish - Basic Course, Units 31-45 (Audiocassettes)

    NTIS | 1996
    Schlagwörter: Second language learning

    PSO-based Machine Learning Methods for Predicting Ground Surface Displacement Induced by Shallow Underground Excavation Method

    Kong, Fanchao / Tian, Tao / Lu, Dechun et al. | Springer Verlag | 2023
    Schlagwörter: Machine learning methods

    Machine learning based tool for identifying errors in CAD to GIS converted data

    Badhrudeen, Mohamed / Naranjo, Nalin / Movahedi, Ali et al. | Springer Verlag | 2019
    Schlagwörter: Machine Learning

    One-Class Convolutional Neural Network (OC-CNN) Model for Rapid Bridge Damage Detection Using Bridge Response Data

    Yessoufou, Fadel / Zhu, Jinsong | Springer Verlag | 2023
    Schlagwörter: Semi-supervised learning