Foundations of Computing and Decision Sciences Walter de Gruyter Journal Impact Factor

Foundations of Computing and Decision Sciences - Walter de Gruyter GmbH | 2024 Impact Factor:1.3 | Cite Score:3.2 | Q3

Foundations of Computing and Decision Sciences Journal With Cite Score

Cite Score and Journal Rank of Foundations of Computing and Decision Sciences

About: The Foundations of Computing and Decision Sciences is a peer-reviewed academic journal dedicated to advancing the theoretical and practical aspects of computing and decision sciences. It focuses on fundamental research that addresses foundational issues in computing, decision-making processes, and their applications across various domains.
Objective
The journal aims to provide a platform for disseminating significant research findings that contribute to the understanding and development of fundamental principles in computing and decision sciences. It seeks to foster the advancement of theoretical foundations, methodologies, and applications that impact both academic research and practical implementations.
Topics Covered
The Foundations of Computing and Decision Sciences covers a wide range of topics, including but not limited to: Theoretical foundations of computing Decision theory and decision-making processes Algorithms and computational complexity Optimization methods and techniques Mathematical modeling and analysis Information systems and management Computational intelligence and machine learning Applications in various domains such as economics, engineering, and social sciences
Interdisciplinary Approach
The journal embraces an interdisciplinary approach by integrating insights from various fields related to computing and decision sciences. It encourages research that explores connections between theoretical foundations and practical applications, fostering a comprehensive understanding of complex problems and solutions.
Impact and Significance
The Foundations of Computing and Decision Sciences has a significant impact on the field by advancing the theoretical understanding of computing and decision processes. Its publications contribute to the development of new methodologies, models, and applications that influence both academic research and practical implementations. The journal serves as a valuable resource for researchers, practitioners, and policymakers interested in foundational issues in these areas.
Submission and Review Process
The journal follows a rigorous peer-review process to ensure the quality and relevance of submitted articles. Researchers are invited to submit original research papers, reviews, and case studies that align with the journals focus. The open-access model ensures that all published content is freely accessible to the global research community, enhancing the dissemination and impact of the research.

Journal Home: Journal Homepage

Editor-in-Chief: Jerzy Stefanowski

Scope: The Foundations of Computing and Decision Sciences journal addresses foundational aspects of computing and decision-making methodologies. It encompasses a broad spectrum of topics related to the theoretical underpinnings, algorithmic developments, and practical applications in computing and decision sciences.
Scope and Areas of Interest:
Computational Foundations:
Theoretical Computer Science: Research on the theoretical aspects of computer science, including computational complexity, algorithms, and data structures.
Formal Methods: Studies on formal methods for software and hardware verification, including model checking, theorem proving, and formal specification.
Computational Models: Exploration of various computational models, including deterministic and probabilistic models, and their applications.
Algorithm Design and Analysis: Research on the design, analysis, and optimization of algorithms, including exact and approximate algorithms.
Decision Sciences:
Decision Theory: Studies on decision-making models and methodologies, including classical and modern decision theory, multi-criteria decision analysis, and decision support systems.
Optimization: Research on optimization techniques and algorithms, including linear programming, integer programming, and heuristic methods.
Stochastic Processes: Exploration of stochastic processes and their applications in decision-making, including Markov chains, queuing theory, and probabilistic models.
Game Theory: Studies on game theory and its applications in strategic decision-making, including non-cooperative and cooperative game theory.
Computing and Decision Support Systems:
Decision Support Systems (DSS): Research on the development and application of decision support systems, including data mining, knowledge management, and business intelligence.
Computational Intelligence: Exploration of computational intelligence techniques, including neural networks, fuzzy systems, and evolutionary algorithms.
Information Retrieval: Studies on information retrieval systems, including search algorithms, indexing, and query processing.
Human-Computer Interaction (HCI): Research on HCI principles and practices, including user interface design, usability studies, and interaction techniques.
Applications and Case Studies:
Business and Industry: Application of computing and decision sciences methodologies in business contexts, including supply chain management, financial modeling, and operations research.
Healthcare: Studies on the application of computing and decision-making techniques in healthcare, including medical imaging, diagnostic systems, and health informatics.
Engineering and Manufacturing: Exploration of computational and decision sciences applications in engineering and manufacturing, including process optimization, quality control, and system design.
Social Sciences: Research on the application of computational and decision-making methods in social sciences, including sociological studies, behavioral analysis, and policy-making.
Emerging Trends and Research Directions:
Big Data and Analytics: Research on big data technologies and analytics methodologies, including data processing, data visualization, and predictive analytics.
Artificial Intelligence and Machine Learning: Exploration of AI and machine learning techniques, including supervised and unsupervised learning, reinforcement learning, and AI applications.
Quantum Computing: Studies on quantum computing principles and their implications for decision sciences, including quantum algorithms and quantum information theory.
Smart Systems: Research on smart systems and applications, including smart grids, smart cities, and autonomous systems.