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Full-Text Articles in Electrical and Computer Engineering
Optimized And Automated Machine Learning Techniques Towards Iot Data Analytics And Cybersecurity, Li Yang
Optimized And Automated Machine Learning Techniques Towards Iot Data Analytics And Cybersecurity, Li Yang
Electronic Thesis and Dissertation Repository
The Internet-of-Things (IoT) systems have emerged as a prevalent technology in our daily lives. With the wide spread of sensors and smart devices in recent years, the data generation volume and speed of IoT systems have increased dramatically. In most IoT systems, massive volumes of data must be processed, transformed, and analyzed on a frequent basis to enable various IoT services and functionalities. Machine Learning (ML) approaches have shown their capacity for IoT data analytics. However, applying ML models to IoT data analytics tasks still faces many difficulties and challenges. The first challenge is to process large amounts of dynamic …
Data Preprocessing For Machine Learning Modules, Rawan El Moghrabi
Data Preprocessing For Machine Learning Modules, Rawan El Moghrabi
Undergraduate Student Research Internships Conference
Data preprocessing is an essential step when building machine learning solutions. It significantly impacts the success of machine learning modules and the output of these algorithms. Typically, data preprocessing is made-up of data sanitization, feature engineering, normalization, and transformation. This paper outlines the data preprocessing methodology implemented for a data-driven predictive maintenance solution. The above-mentioned project entails acquiring historical electrical data from industrial assets and creating a health index indicating each asset's remaining useful life. This solution is built using machine learning algorithms and requires several data processing steps to increase the solution's accuracy and efficiency. In this project, the …
Machine Learning With Big Data For Electrical Load Forecasting, Alexandra L'Heureux
Machine Learning With Big Data For Electrical Load Forecasting, Alexandra L'Heureux
Electronic Thesis and Dissertation Repository
Today, the amount of data collected is exploding at an unprecedented rate due to developments in Web technologies, social media, mobile and sensing devices and the internet of things (IoT). Data is gathered in every aspect of our lives: from financial information to smart home devices and everything in between. The driving force behind these extensive data collections is the promise of increased knowledge. Therefore, the potential of Big Data relies on our ability to extract value from these massive data sets. Machine learning is central to this quest because of its ability to learn from data and provide data-driven …
Smart City Management Using Machine Learning Techniques, Mostafa Zaman
Smart City Management Using Machine Learning Techniques, Mostafa Zaman
Theses and Dissertations
In response to the growing urban population, "smart cities" are designed to improve people's quality of life by implementing cutting-edge technologies. The concept of a "smart city" refers to an effort to enhance a city's residents' economic and environmental well-being via implementing a centralized management system. With the use of sensors and actuators, smart cities can collect massive amounts of data, which can improve people's quality of life and design cities' services. Although smart cities contain vast amounts of data, only a percentage is used due to the noise and variety of the data sources. Information and communication technology (ICT) …