International Journal of Advanced Intelligence Paradigms Inderscience Publishers Impact Factor

International Journal of Advanced Intelligence Paradigms - Inderscience | 2024 Cite Score:1.4 | Q4

International Journal of Advanced Intelligence Paradigms With Cite Score

Cite Score and Journal Rank of International Journal of Advanced Intelligence Paradigms

About: International Journal of Advanced Intelligence Paradigms is a peer-reviewed academic journal that focuses on innovative and advanced concepts in artificial intelligence (AI) and related paradigms. The journal aims to explore cutting-edge research and developments in the field of AI, including both theoretical advancements and practical applications.
Objective: The primary objective of the International Journal of Advanced Intelligence Paradigms is to advance the field of artificial intelligence by publishing high-quality research on emerging AI techniques, methodologies, and applications. The journal covers a broad range of topics including machine learning, deep learning, cognitive computing, intelligent systems, and advanced algorithms. It aims to provide a forum for researchers and practitioners to share their latest findings, address complex problems, and contribute to the advancement of AI technologies.
Interdisciplinary Approach: The journal adopts an interdisciplinary approach by integrating research from various fields related to AI, including computer science, mathematics, engineering, cognitive science, and data science. This approach allows for a comprehensive exploration of AI concepts and their applications across different domains. Contributions that bridge these disciplines and offer innovative solutions to complex AI challenges are particularly encouraged.
Impact and Significance: The International Journal of Advanced Intelligence Paradigms has a significant impact on the academic and professional communities involved in artificial intelligence. The research published in the journal contributes to the development of new AI technologies and methodologies, providing valuable insights for researchers, developers, and practitioners. It serves as a key resource for staying informed about the latest advancements and trends in the field of AI.

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Editor-in-Chief: Prof. Valentina E. Balas, Prof. Anca Ralescu

Scope: The International Journal of Advanced Intelligence Paradigms focuses on cutting-edge research and developments in the field of advanced intelligence. It covers a broad range of topics related to artificial intelligence, machine learning, and intelligent systems. Key areas covered by the journal include:
1. Artificial Intelligence (AI): Research on AI technologies, including algorithms, models, and applications in various domains.
Machine Learning: Studies on machine learning techniques and methodologies, including supervised learning, unsupervised learning, reinforcement learning, and deep learning.
Intelligent Systems: Development and application of intelligent systems, including expert systems, decision support systems, and autonomous agents.
Data Science: Research on data science methods and applications, including data analysis, data mining, and big data technologies.
Natural Language Processing (NLP): Exploration of NLP techniques, including text analysis, sentiment analysis, language generation, and machine translation.
Computer Vision: Studies on computer vision technologies, including image recognition, object detection, and visual perception.
Robotics: Research on robotics and automation, including robot design, control systems, and applications in various fields.
AI Ethics and Governance: Examination of ethical and governance issues related to AI, including fairness, transparency, accountability, and regulatory frameworks.
Intelligent Systems Integration: Research on integrating intelligent systems with existing technologies and systems, including interoperability and system design.
AI Applications: Exploration of practical applications of AI in various domains, including healthcare, finance, transportation, and smart cities.
Advanced Computing Techniques: Studies on advanced computing techniques that support intelligent systems, including high-performance computing and distributed systems.
Human-AI Interaction: Research on the interaction between humans and AI systems, including user interfaces, usability, and human-centered design.
AI in Education: Examination of the role of AI in educational settings, including personalized learning, educational technology, and intelligent tutoring systems.
Emerging Trends and Technologies: Review of emerging trends and technologies in the field of advanced intelligence, including new methodologies, tools, and research directions.