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Frontiers in Engineering and Technology (FET)

Publisher :

IAEME Publication

Scopus Profile
Peer reviewed only
Scopus Profile
Open Access
  • Machine Learning Algorithms
  • Natural Language Processing (NLP)
  • Deep Learning

    • +11

e-ISSN :

3065-4262

Issue Frequency :

Monthly

Est. Year :

2020

Mobile :

1234567809

DOI :

YES

Country :

India

Language :

English

APC :

YES

Impact Factor Assignee :

Google Scholar

Email :

editor@iaeme.com

Journal Descriptions

Frontiers in Engineering and Technology (FET) aims to provide a high-quality platform for researchers, academicians, industry professionals, and policymakers to share and disseminate innovative research and technological advancements in the field of engineering and technology. The journal seeks to promote interdisciplinary collaboration, drive technological innovation, and address global challenges through cutting-edge research and practical applications. Frontiers in Engineering and Technology (FET) publishes high-quality, peer-reviewed research articles, review papers, and case studies that explore innovative advancements and technological breakthroughs in the field of engineering and technology. The journal aims to provide a platform for researchers, academicians, and industry professionals to share knowledge and promote interdisciplinary research.


Frontiers in Engineering and Technology (FET) is :

International, Peer-Reviewed, Open Access, Refereed, Machine Learning Algorithms, Natural Language Processing (NLP), Deep Learning, Computer Vision, Data Science, Artificial Intelligence, Machine Learning, Big Data, Cybersecurity, Information Protection, Software Engineering and Development, Networking, Communication, Computational Intelligence and Automation , Online Monthly Journal

UGC Approved, ISSN Approved: P-ISSN , E-ISSN - 3065-4262, Established in - 2020, Impact Factor

Provide Crossref DOI

Not indexed in Scopus, WoS, DOAJ, PubMed, UGC CARE

Indexing

Scopus Profile
Google Scholar
Scopus Profile
Research Gate
Scopus Profile
Academia

Publications of FET

  • dott image January, 2022

AN EXTENSIVE INVESTIGATION INTO ADVANCED DATA SCIENCE METHODOLOGIES, MACHINE LEARNING ALGORITHMS, STATISTICAL INFERENCE, BIG DATA ANALYTICS, AND THEIR...

Data science has emerged as a multidisciplinary field that integrates advanced methodologies, machine learning algorithms, statistical inference, and big data analytics to drive intelligent ...

  • dott image March, 2025

AUTONOMOUS THREAT INTELLIGENCE AND MACHINE LEARNING-BASED CYBER DEFENSE MECHANISMS FOR SECURING IOT AND EDGE COMPUTING ECOSYSTEMS

The proliferation of the Internet of Things (IoT) and Edge Computing has significantly expanded the attack surface for cyber threats. Traditional security mechanisms struggle to keep pace wi...

  • dott image January, 2025

HARNESSING BIG DATA ANALYTICS FOR OPTIMIZING BUSINESS INTELLIGENCE AND ENHANCING CONSUMER INSIGHTS

Big Data Analytics (BDA) has revolutionized the way businesses operate, offering data-driven insights that optimize business intelligence (BI) and enhance consumer understanding. This paper ...

  • dott image July, 2023

ENHANCING NATURAL LANGUAGE PROCESSING THROUGH TRANSFORMER MODELS AND LARGE SCALE PRETRAINED NETWORKS

Natural Language Processing (NLP) has seen significant advancements with the introduction of Transformer models and large-scale pre-trained networks. These architectures have enabled improve...

  • dott image March, 2023

INTEGRATING AI POWERED EDGE COMPUTING FOR SCALABLE AND EFFICIENT INTERNET OF THINGS APPLICATIONS

The rapid expansion of the Internet of Things (IoT) has led to challenges in data processing, latency, and energy efficiency. Traditional cloud computing models struggle with real-time data ...

  • dott image May, 2021

COST-EFFICIENT AND ENERGY-AWARE MULTI-OBJECTIVE OPTIMIZATION ALGORITHMS FOR DATA PROCESSING IN HETEROGENEOUS BIG DATA FRAMEWORKS

As Big Data applications continue to grow, energy efficiency and cost management have become critical concerns in heterogeneous computing environments. Traditional resource allocation and jo...

  • dott image March, 2020

AUTONOMOUS ORCHESTRATION OF VIRTUALIZED RESOURCES IN CLOUD ENVIRONMENTS USING REINFORCEMENT LEARNING AND DISTRIBUTED CONTROL MECHANISMS

Cloud computing environments require intelligent orchestration of virtualized resources to optimize performance, minimize costs, and ensure scalability. Traditional resource allocation mecha...

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