Bio-inspired Computation - Inderscience - Impact Factor

International Journal of Bio-inspired Computation - Inderscience | 2024 Impact Factor:2 | Cite Score:3.7 | Q3

Impact Factor and Journal Rank of International Journal of Bio-inspired Computation

About: The International Journal of Bio-inspired Computation (IJBIC) focuses on the latest research and developments in the field of bio-inspired computation. This journal covers a broad spectrum of topics related to the innovative methodologies and applications inspired by natural biological systems.
Publication Types:
IJBIC publishes various types of articles, including:
Research Articles: Original research contributions that advance the theory and application of bio-inspired computation.
Review Papers: Comprehensive reviews of the current state-of-the-art in bio-inspired computation.
Application Papers: Practical applications of bio-inspired algorithms in real-world scenarios.
Technical Notes: Shorter papers presenting novel methodologies or significant improvements to existing techniques.
Impact and Contribution:
The International Journal of Bio-inspired Computation plays a crucial role in advancing the field by providing a platform for researchers to publish high-quality, peer-reviewed research. The journal facilitates the exchange of ideas and promotes collaboration among researchers and practitioners worldwide, influencing both theoretical advancements and practical applications of bio-inspired algorithms.

Journal Home: Journal Homepage

Editor-in-Chief: Prof. Zhihua Cui

Scope: The International Journal of Bio-inspired Computation (IJBIC) focuses on publishing high-quality research articles that explore and apply bio-inspired computation methods across various domains. Bio-inspired computation refers to computational techniques and algorithms inspired by biological systems and processes.
Key topics covered in the journal include:
Evolutionary Computation: Algorithms and models inspired by the process of natural selection and genetic evolution, including genetic algorithms, genetic programming, and evolutionary strategies.
Swarm Intelligence: Techniques inspired by the collective behavior of decentralized, self-organized systems, such as ant colonies, bird flocking, and fish schooling, including particle swarm optimization and ant colony optimization.
Artificial Immune Systems: Computational systems inspired by the principles and processes of the biological immune system, used for tasks like anomaly detection, pattern recognition, and optimization.
Neural Networks: Computational models inspired by the structure and functioning of the human brain, including artificial neural networks, deep learning, and neuromorphic computing.
Artificial Life: Studies and simulations of life-like behaviors in artificial systems, encompassing areas such as self-replication, artificial chemistry, and autonomous agents.
Biologically Inspired Robotics: Design and control of robots inspired by biological organisms, including soft robotics, biomimetic actuators, and sensors.