Machine Learning Algorithms and Applications in Engineering

Machine Learning Algorithms and Applications in Engineering

Perez-Rodriguez, Javier; Fernandez-Navarro, Francisco; Chatterjee, Prasenjit; Yazdani, Morteza

Taylor & Francis Ltd

02/2023

314

Dura

Inglês

9780367569129

15 a 20 dias

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Introduction. Fundamentals of Machine Learning. Machine Learning Algorithms: Theoretical and Mathematical Aspects. An Exhaustive Review of Applications of Machine Learning Applications in Engineering. Applications in Engineering. Design of Highway and Transportation Engineering for the Prediction of Transport Arrivals & Pedestrian Movement Analysis / Traffic Pattern / Congestion Management. Use of Machine Learning in Construction, Surveying, Geo Technical and Geo-Spatial Engineering / Seismic Data Analysis. Machine Learning for Industrial Automation / Smart Grid Management / Driver Monitoring Systems / Autonomous Vehicles. Machine Learning in Grid Integration and Power Distribution / Control and Feedback System / Power Quality / Power Usage Analysis. Machine Learning in Robotics and Intelligent Machines. Machine Learning for Predictive Maintenance and Condition Monitoring / Reliability Engineering. Use of IoT and Big Data Analytics in Manufacturing / Demand Forecasting / Process Optimization / Inventory Planning / Fault Diagnosis for Shop Floor Machinery. Machine Learning for Carbon Emission / Environmental Engineering. Machine Learning for Renewable Energy Policy. Machine Learning in Biomedical Engineering.
deep learning;data;pre-processing;convolutional neural network;logistic regression;association rule mining;traffic pattern;bayesian learning;industrial automation;Polar Codes;UK Biobank;BCI;Random Forest;Deep Neural Network;Deep Neural Network Models;ARIMA Model;EV;LULC Map;Batch Id;Deep Neural Network Learning;Privacy Preserving Data Publishing;Precision Health;Genetic Algorithm Support Vector Machine;Data Set;Correlation Attack;Univariate Time Series Forecasting;F1 Score;Sensitive Information;Missing Values;Hybrid Artificial Intelligence;Cf;NDWI Value;Massive MIMO;Random Forest Prediction