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المؤلفTomar, A.
المؤلفMalik, H.
المؤلفKumr, P.
المؤلفIqbal, A.
تاريخ الإتاحة2023-05-21T08:32:45Z
تاريخ النشر2022
اسم المنشورLecture Notes in Electrical Engineering
المصدرScopus
معرّف المصادر الموحدhttp://dx.doi.org/10.1007/978-981-19-2828-4_1
معرّف المصادر الموحدhttp://hdl.handle.net/10576/43102
الملخصMachine learning (ML) is the subcategory of artificial intelligence (AI), which has the capability to imitate human behavior intelligently as per the task performed by the human. In the modern time, any organization implements AI by using ML so that system's behavior of interchangeably and ambiguously is updated automatically through the experience without any delay. So, current advances in AI have involved ML. The ML starts with data (i.e., any kind of data starting from primary to secondary data). These data are collected and preprocessed to be used as training and testing the ML models being utilized for different applications such as regression, prediction, forecasting, classification, clustering, management, design, optimization, security, IoTs, health care, digitization, automation, control, privacy protection and e-commerce. In this book, the applications AI, ML and its advancement for different applications have been presented into different chapters, including the state-of-the-art and implementation in the various research domains of engineering and science. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
راعي المشروعIn this chapter, Mitali Chugh presented a deep drive into a knowledge management system for improving software processes and products. The author explores the knowledge management literature, identifies the knowledge gaps and enhances future research in this domain. Demonstrated results highlight how software process improvement has been supported by knowledge management.
اللغةen
الناشرSpringer Science and Business Media Deutschland GmbH
الموضوعAdvance computing
Artificial intelligence
Communication
Condition monitoring
Data analytics
Diagnosis
Electric vehicle
Energy storage
Fault detection
Forecasting
Machine learning
Management
Optimization
Power system
Prediction
Renewable energy
Safety analysis
Smart city
Smart grid
العنوانEditorial: Machine Learning, Advances in Computing, Renewable Energy and Communication (MARC)
النوعConference Paper
الصفحات19-Jan
رقم المجلد915
dc.accessType Abstract Only


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