Machine Learning Journal DOI | IJSREAT ML Research Publication

Machine Learning Journal DOI – IJSREAT

The International Journal of Scientific Research in Engineering & Technology (IJSREAT) (e-ISSN: 2583-1240) is a bi-monthly, international, peer-reviewed, open-access and multidisciplinary online journal dedicated to research across Science, Engineering and Technology. Researchers searching for a machine learning journal DOI can explore IJSREAT for scholarly research in Machine Learning, Artificial Intelligence, Data Science, intelligent computing and emerging technology applications.

IJSREAT provides a platform for academicians, researchers, engineers, students and industry professionals to publish original research contributions, review articles and technical studies. The journal encourages interdisciplinary research connecting Machine Learning and computer science with healthcare, cybersecurity, robotics, IoT, cloud computing and other engineering applications.

🔗 Machine Learning Journal DOI Publication

A machine learning journal DOI provides a persistent identifier for an eligible published research article. IJSREAT provides a DOI-inclusive publication option according to its stated article processing charges and publication information.

A Digital Object Identifier can support stable identification and citation of scholarly Machine Learning research. Authors should verify the DOI assigned to their individual article and confirm applicable DOI registration details before using it in citations, academic profiles, repositories or research records.

🧠 Machine Learning and Computer Science Scope

IJSREAT welcomes original research papers, review articles and technical notes covering a broad range of Machine Learning, Artificial Intelligence and computer science topics.

• 🧠 Supervised Learning: Classification, regression, predictive modeling and data-driven learning algorithms.
• 🔍 Unsupervised Learning: Clustering, dimensionality reduction, representation learning and pattern discovery.
• 🎮 Reinforcement Learning: Learning-based decision systems for gaming, robotics and autonomous applications.
• 🌐 Federated Learning: Distributed Machine Learning, privacy-aware learning and decentralized model training.
• ⚡ Edge Machine Learning: Intelligent inference and learning for edge devices, IoT and resource-constrained environments.
• 📊 Predictive Analytics: Forecasting, anomaly detection, business analytics and healthcare applications.
• 🤖 Artificial Intelligence: Explainable AI, intelligent systems, autonomous technologies and AI-enabled applications.
• 👁️ Computer Vision: Image classification, segmentation, object detection, biometrics and medical image analysis.
• 🗣️ Natural Language Processing: Sentiment analysis, summarization, translation, chatbots and virtual assistants.
• 🛡️ ML for Cybersecurity: Malware detection, intrusion detection, anomaly identification and intelligent security systems.
• 🌐 ML for IoT: Smart cities, connected devices, sensor analytics, edge intelligence and fog computing.
• ☁️ ML and Cloud Computing: Cloud-based Machine Learning, scalable model deployment and distributed intelligent systems.

🌍 International Machine Learning Research

Researchers preparing manuscripts for a machine learning journal DOI can submit studies involving learning algorithms, predictive models, deep learning, intelligent decision systems, data-driven applications and emerging computational methods.

The multidisciplinary scope of IJSREAT supports research connecting Machine Learning with Artificial Intelligence, Data Science, cybersecurity, cloud computing, IoT, robotics, healthcare and other areas of computer science and engineering.

🔎 Google Scholar and Machine Learning Research

The supplied IJSREAT indexing and abstracting information includes Google Scholar. Researchers searching for a machine learning journal DOI can consider the DOI publication option together with the journal's stated open-access model and supplied indexing information.

Authors should independently verify current Google Scholar indexing or abstracting status and individual article discoverability through the relevant official service. Discoverability may depend on article metadata, indexing processes and other technical factors.

⚡ Fast Publication and Rapid Publication for ML Research

Machine Learning is a rapidly evolving area of computer science and technology. IJSREAT states an initial acknowledgment within 12 hours, expert review within 2 days and decision notification within 3 days as part of its stated publication workflow.

These are stated workflow targets rather than guarantees. Actual fast publication and rapid publication timelines may vary according to manuscript quality, reviewer availability, revision requirements and editorial considerations.

💰 Low Cost Machine Learning Journal DOI

IJSREAT follows an open-access publication model with a stated low cost article processing structure. For Indian authors, the stated fee is ₹1200 + 18% GST without DOI and ₹1400 + 18% GST with DOI. For authors outside India, the stated DOI-inclusive fee is $80 USD.

The low cost DOI option may be relevant to students, researchers, academicians and industry professionals working in Machine Learning and computer science. Authors should confirm the latest APC, DOI requirements and applicable publication terms before submission.

🏛️ UGC CARE and Machine Learning Publication

UGC CARE status may be an important consideration when researchers evaluate journals for academic publication. Authors searching for a machine learning journal DOI should independently verify current UGC CARE status and their institution's publication requirements through appropriate official sources.

Indexing and recognition information can change over time. Researchers should review current official information before relying on a particular status for academic, institutional or professional purposes.

🔬 Peer Review, Plagiarism Protection and COPE

IJSREAT describes a peer-reviewed publication process for submitted manuscripts. Machine Learning researchers should present original contributions, appropriate experimental methodology, clearly documented datasets and models where applicable, meaningful evaluation metrics and accurate scholarly references.

The journal also describes plagiarism screening and adherence to COPE publication ethics principles. Originality, responsible authorship, transparent methodology and proper citation are important elements of responsible Machine Learning research publication.

🚀 Machine Learning Journal DOI Publication Process

1. 📤 Submit Online: Submit your Machine Learning research manuscript through the IJSREAT editorial management system.
2. 📩 Initial Response: Receive acknowledgment according to the stated editorial workflow.
3. 🔬 Expert Review: The manuscript proceeds through the applicable peer review process.
4. 📋 Decision Notification: Receive an editorial decision after completion of the review process.
5. 🔗 DOI Processing: Accepted manuscripts using the DOI option proceed through the applicable DOI publication workflow.
6. 📄 Publication & Certificate: Access the published PDF and applicable digital certificate after publication.

🖥️ Advanced Editorial Management System

IJSREAT provides an editorial management environment designed to support authors throughout the publication workflow. Researchers submitting to a machine learning journal DOI can use the system for manuscript submission, status updates and publication-related documents.

• 👤 Author Dashboard: Personalized access to submission history and manuscript status.
• 📊 Real-Time Tracking: Follow manuscript progress through applicable editorial stages.
• 📑 Automated Documents: Support for acceptance letters and copyright-related documents.
• ⬇️ Easy Downloads: Access certificates and published research papers.

📚 Indexing and Abstracting Information

The supplied IJSREAT indexing and abstracting information includes Google Scholar, Scribd, ISSUU, Elsevier Mendeley, EuroPub, DRJI, Academic Keys, Edocr, I2OR, PDFSR, ResearchBIB, SSRN, WorldCAT, Exlibris, Thomson Reuters Research ID, Semantic Scholar, Dimensions and PlumX. Authors should independently verify current coverage and status for each service before relying on a particular indexing or abstracting claim.

🌟 Machine Learning Journal DOI – IJSREAT

Researchers searching for a machine learning journal DOI can explore IJSREAT for studies involving supervised and unsupervised learning, reinforcement learning, federated learning, edge Machine Learning, predictive analytics, Artificial Intelligence, computer vision, NLP, cybersecurity and other emerging areas of computer science.

IJSREAT combines a broad Machine Learning and technology scope with open-access publishing, a stated low cost DOI option and a workflow built around fast publication and rapid publication objectives. For editorial queries, contact editorinchief@ijsreat.com.