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International Journal of Algorithms Design and Analysis Review Cover

International Journal of Algorithms Design and Analysis Review

E-ISSN: 2584-1866 | Peer-Reviewed Journal (Refereed Journal) | Hybrid Open Access

About the Journal

International Journal of Algorithms Design and Analysis Review is a peer-reviewed hybrid open-access journal launched in 2015 that focuses on original research and practice-driven application with relevance to algorithms designs and analysis. All articles included are peer-reviewed by scholars with colossal … experience in the same fields. Dynamic programming, amortized analysis, and linear programming are major focus areas.

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Journal Information

Title: International Journal of Algorithms Design and Analysis Review
Abbreviation: ijadar
Issues Per Year: 2 Issues
E-ISSN: 2584-1866
Publisher: STM Journals, An imprint of Consortium e-Learning Network Pvt. Ltd.
DOI: 10.37591/IJADAR
Starting Year: 2023
Publication Format: Hybrid Open Access
Language: English
Copyright Policy: CC BY-NC-ND
Type: Peer-reviewed Journal (Refereed Journal)

Address:

STM Journals, An imprint of Consortium e-Learning Network Pvt. Ltd. A-118, 1st Floor, Sector-63, Noida, U.P. India, Pin - 201301

Editorial Board

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ijadar maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

Editor in Chief

Editor

Dr. Sharada Patil, Associate Professor

Sinhagad Institute of business Administration and Research, Pune, India, 411048

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Latest Articles

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Sentiment Analysis: A Comprehensive Review of NLP Techniques on Social Media Data

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Social media, natural language processing (NLP), sentiment analysis, opinion mining, machine learning

Misinformation Detection and Analysis of Social Media Platforms Using Machine Learning and Deep Learning

Social media platforms have become deeply embedded in everyday life, reshaping how people produce, distribute, and engage with information.

Misinformation detection, fake news detection, machine learning, deep learning, CNN–LSTM, natural language processing, social media analytics

A Comparative Study of K-Means, DBSCAN, and Hierarchical Clustering for Content Segmentation in Netflix Movies and TV Shows

Over-the-top (OTT) platforms like Netflix offer a vast and diverse range of movies as well as television programs, resulting in a difficult task of content organization.

OTT platforms, Netflix content analysis, unsupervised learning, clustering algorithms, Word2Vec embeddings, principal component analysis, content segmentation

Recent Routing Protocols in UAV Networks: Classifications, Challenges, and Future Directions

Routing protocols enable reliable communication in Unmanned Aerial Vehicle (UAV) networks, particularly Flying Ad-hoc Networks (FANETs), amid high-speed 3D mobility, dynamic topologies, and energy limits.

UAV; FANETs; Routing Protocol; Topology Based Routing protocols; Position Based Routing Protocols; Hierarchical Based Routing Protocols

Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification

Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions.

Mental health, emotion detection, sentiment analysis, BERT, CNN, explainable AI

Enhancing Smart Grid Resilience Through AI-Based Fault Classification

Traditional power grids can be developed into smart grids, and they are comprised of the latest information and communication technologies (ICTs), which are based on establishing the relationship between the conventional electricity systems along with the usage of smart meters and distributed generation.

Artificial intelligence, distribution network, fault classification, random forest, smart grid
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