Journal of Future Artificial Intelligence and Technologies

About the Journal

Journal Title : Journal of Future Artificial Intelligence and Technologies
Initials : FAITH
Abbreviation : J. Fut. Artif. Intell. Tech.
Frequency : Quarterly (March, June, September, December)
Online ISSN : 3048-3719
Editor in Chief : Assoc. Prof. Dr. De Rosal Ignatius Moses Setiadi
DOI Prefix: 10.62411/faith
Publisher : Future Techno Science

Journal of Future Artificial Intelligence and Technologies (E-ISSN: 3048-3719) is an international journal that delves into the comprehensive spectrum of artificial intelligence, focusing on its foundations, advanced theories, and applications. FREE OF CHARGES for submission and publication. All accepted articles will be published online, assigned a DOI via Crossref, and will be OPEN ACCESS. The peer-review process is designed to be efficient and constructive, with an initial editorial decision typically provided within approximately two weeks, while maintaining rigorous and thorough evaluation standards.

The journal welcomes contributions in areas including, but not limited to:

Core Artificial Intelligence
• Machine Learning
• Deep Learning
• Natural Language Processing
• Reinforcement Learning
• Federated Learning
• Computational Intelligence
• Intelligent Systems
• Generative Artificial Intelligence
• Agentic Artificial Intelligence
Advanced AI Methods and Foundations
• Computer Vision
• AI in Image Processing
• AI in Signal Processing
• AI in Security
• AI for Robotics
• Quantum Computing in AI
Cross-Domain and Applied AI
• Computing Technologies
• Emerging and Cross-domain Applications of AI and Computing Technologies
Future and Bio-Inspired Directions in AI
• Brain-Inspired and Bioinspired AI
• Neuromorphic and Cognitive Computing
• Ambient Intelligence and Human–AI Interaction
• AI Inspired by Biological Perception and Sensing Systems

Special emphasis is given to recent trends and cutting-edge research within these domains.

If you wish to become an author in this journal, please access the About page. You may start by reading the Policies section to understand the guidelines established by

J.FAITH. For manuscript preparation, details can be found in the Author Guidelines section.

All submissions must be made online, and prospective authors are required to register and create an account before submitting manuscripts.

Abstracting, Indexing, and Library Databases:
The Journal of Future Artificial Intelligence and Technologies is indexed and cataloged in several international scholarly databases and academic library systems, ensuring broad visibility and long-term accessibility of published articles.

Current Issue

Vol. 3 No. 2 (2026): September 2026

(in progress)
Authors' Diversity: The authors currently come from a diverse range of countries, including Sri Lanka, Nigeria, India, Indonesia, Hong Kong, Poland, Trinidad and Tobago, and Pakistan.

Published: 2026-09-30

Articles

Hourly UV Index Forecasting Across Climatic Zones in Sri Lanka: A Residual-Correction Hybrid Machine Learning and Deep Learning Approach

Hiruni Navodya Kudagama (University of Colombo, LK)

Samantha Mathara Arachchi (University of Colombo, LK)

K. G. Amidu Yohan (University of Colombo, LK)

C. L. I. S. Fonseka (University of Colombo, LK)

234-256

DOI : https://doi.org/10.62411/faith.3048-3719-372
- pdf Views: 127 times | Download : 95 times
Binary Firefly Algorithm-Based Optimization of TabNet and DNN Models for Customer Churn Prediction

Philip O. Odion (Nigerian Defence Academy, NG)

Maaruf M. Lawal (Ahmadu Bello University, NG)

Sonia S. Joshua (Kaduna State College of Education Gidan Waya, NG)

Abdulrashid Abdulrauf (Federal Polytechnic Kaltungo, NG)

257-274

DOI : https://doi.org/10.62411/faith.3048-3719-376
- pdf Views: 78 times | Download : 81 times
Protocol Weakness-Aware CNN-BiLSTM-Transformer Adaptive Fusion Network with Early-Risk and Uncertainty-Aware IoT Cyberattack Detection

Atheer Alaa Hammad (Shivaji University, IN)

Kavita S. Oza (Shivaji University, IN)

275-302

DOI : https://doi.org/10.62411/faith.3048-3719-384
- pdf Views: 78 times | Download : 63 times
Domain-Driven Feature Engineering and Optimized Stacking Ensemble Learning for Used Car Price Prediction

Dhani Ian Maulana (Universitas Dian Nuswantoro, ID)

De Rosal Ignatius Moses Setiadi (Universitas Dian Nuswantoro, ID)

Yew Kee Wong (Hong Kong Chu Hai College, HK)

Zahir Edrees (International Science and Technology University, PL)

303-327

DOI : https://doi.org/10.62411/faith.3048-3719-326
- pdf Views: 137 times | Download : 66 times
Hypothesizing Objectives and Intents of an Artificial Super Intelligence: The Case for the Anti-Entropy Drive

Craig Ramlal (The University of the West Indies, TT)

Chris Maharaj (The University of the West Indies, TT)

328-341

DOI : https://doi.org/10.62411/faith.3048-3719-401
- pdf Views: 33 times | Download : 49 times
A Hybrid Spatio-Temporal Transformer-LSTM Network for Explainable Crop Yield Prediction Using Multi-Source Remote Sensing in Arid African Regions

Johnson Bisi Oluwagbemi (McPherson University, NG)

Olabisi Josh-Falade (McPherson University, NG)

Ayokunle John Tadema (McPherson University, NG)

Ayobami Emmanuel Mesioye (McPherson University, NG)

342-365

DOI : https://doi.org/10.62411/faith.3048-3719-408
- pdf Views: 40 times | Download : 31 times
M2V-SnakeNet: Multi-View Learning with Frozen DINOv2 for Snake Species and Venom Classification

Hamza Maqsood Khan (University of Engineering and Technology, PK)

Wakeel Ahmad (University of Engineering and Technology, PK)

Syed M. Adnan (University of Engineering and Technology, PK)

366-386

DOI : https://doi.org/10.62411/faith.3048-3719-431
- pdf Views: 23 times | Download : 16 times
Context-Aware Fake News Classification with BERT-LSTM and Bahdanau Attention

Loreta Katok Tohomdet (Airforce Institute of Technology, NG)

Maryam Sufiyanu Masari (Airforce Institute of Technology, NG)

Aisha Tijjani Ramalan (Airforce Institute of Technology, NG)

Ilori Loretta Onyinye (Airforce Institute of Technology, NG)

Abdulrashid Abdulrauf (Federal Polytechnic Kaltungo, NG)

DOI : https://doi.org/10.62411/faith.3048-3719-425
- pdf Views: 17 times | Download : 6 times
Adversarially Robust and Explainable Graph Neural Networks for Fraud Detection in Dynamic Blockchain Networks: A Systematic Solution-Based Literature Review

Oluwaseun Adeniyi Ojerinde (Federal University of Technology Minna, NG)

Ramatu Abubakar (Federal University of Technology, NG)

Benjamin Ilunuamie Alenoghena (Federal University of Technology, NG)

Kehinde Hussein Lawal (Federal University of Technology, NG)

387-418

DOI : https://doi.org/10.62411/faith.3048-3719-428
- pdf Views: 19 times | Download : 2 times

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