Journal Information
Neural Computing & Applications (NCA)
https://link.springer.com/journal/521
Impact Factor:
4.500
Publisher:
Springer
ISSN:
0941-0643
Viewed:
22115
Tracked:
29
Call For Papers
Neural Computing & Applications is an international journal which publishes original research and other information in the field of practical applications of neural computing and related techniques such as genetic algorithms, fuzzy logic and neuro-fuzzy systems.  

All items relevant to building practical systems are within its scope, including but not limited to:

    adaptive computing
    algorithms
    applicable neural networks theory
    applied statistics
    architectures
    artificial intelligence
    benchmarks
    case histories of innovative applications
    fuzzy logic
    genetic algorithms
    hardware implementations
    hybrid intelligent systems
    intelligent agents
    intelligent control systems
    intelligent diagnostics
    intelligent forecasting
    machine learning
    neural networks
    neuro-fuzzy systems
    pattern recognition
    performance measures
    self-learning systems
    software simulations
    supervised and unsupervised learning methods
    system engineering and integration

Featured contributions fall into several categories: Original Articles, Review Articles, Book Reviews and Announcements.
The Original Articles will be high-quality contributions, representing new and significant research, developments or applications of practical use and value.  They will be reviewed by at least two referees. 

FOUNDING EDITOR
Howard James

JOURNAL ADMINISTRATOR
Tanya Daly, United Kingdom

For all queries relating to papers after submission, please contact the Journal Editorial Office via “contact us” at Editorial Manager.
Last updated by Dou Sun in 2024-07-17
Special Issues
Special Issue on AI for Space: Theories, Models and Applications
Submission Date: 2024-11-30

Aims, Scope and Objective Artificial Intelligence (AI) is becoming increasingly important in the space sector. Indeed, AI-based systems are contributing to several space operations including mission planning, big space data collection and processing, autonomous navigation, spacecraft monitoring and so on. The International Workshop on “The use of Artificial Intelligence for Space Applications” has been co-organized by the University Mediterranea of Reggio Calabria (Italy), the University of Arizona Space Systems Engineering Laboratory (SSEL) (USA), the Italian Space Agency (ASI) (Italy), the European Space Agency - ESA’s Φ-lab (Italy) and Thales Alenia Space (Italy) and was held in Reggio Calabria, Italy, in September 1-3, 2022. This Topical Collection intends to examine the “dialogue” between AI and space and aims to report new theories, models and applications in this field, by including expanded versions of selected workshop and also newly innovative papers. The topics of interest include, but are not limited to: AI for space and aerospace applications AI for fault detection and diagnosis in space applications AI for studying astronautics’ neurodegeneration AI and learning systems for satellite communications AI and learning systems for space robotics AI for earth observation Meta-learning for space applications IoT for space applications Space informatics Human-machine interaction systems in space applications Intelligent and optimal control for aerospace systems Intelligent search and optimization methods in aerospace applications Bio-inspired solutions for automatic navigation in space applications Sensors for space applications Space data processing for ground-based and onboard analysis Guest Editors Dr. Cosimo Ieracitano (Lead Guest Editor), University Mediterranea of Reggio Calabria, Italy, cosimo.ieracitano@unirc.it Prof. Nadia Mammone, University Mediterranea of Reggio Calabria, Italy, nadia.mammone@unirc.it Dr. Piergiorgio Lanza, Thales Alenia Space, Italy, Piergiorgio.Lanza@thalesaleniaspace.com Prof. Fei Gao, Beihang University, China, youfeigao@buaa.edu.cn Dr. Bertrand Le Saux, European Space Agency, Φ-lab, Italy, Bertrand.Le.Saux@esa.int Prof. Roberto Furfaro, University of Arizona, USA, robertof@arizona.edu Prof. Francesco Carlo Morabito, University Mediterranea of Reggio Calabria, Italy, morabito@unirc.it Manuscript submission deadline: 30th November 2024
Last updated by Dou Sun in 2024-07-17
Special Issue on Neural Computing in the Advancement of Automated Connected & Electrical (ACE) Vehicles
Submission Date: 2024-11-30

Aims and Scope: Automated Connected & Electrical (ACE) vehicle technologies are rapidly transforming the transportation sector and are a cornerstone in the development of future smart cities. The journey from research labs to real-world application, however, is fraught with challenges, including extensive time and financial investments, and stringent regulatory environments. Crucially, the evolution of ACE technologies is increasingly reliant on advanced computational methods, including neural networks, fuzzy logic, and deep learning, to enhance predictive analytics, system modeling, pattern identification, and more. This Special Issue seeks to explore how neural computing and related approaches can optimize the development, testing, and implementation of ACE vehicle technologies. We invite contributions that not only focus on ACE vehicles but also highlight the application of neural computing, machine learning, and intelligent systems in this domain. Topics of Interest include, but are not limited to: Integration of Neural Networks and Deep Learning in ACE Vehicle Development Cooperative Driving Automation (CDA) Enhanced by AI Techniques AI-Driven Edge-Computing for CAV Operations Neural Computing in CAV-Infrastructure Integration Intelligent Vehicle Control Strategies Using Machine Learning Advanced Diagnostics and Forecasting in ACE Vehicles V2X Communications Optimized through Intelligent Algorithms 5G Technologies in ACE Vehicles Enhanced by Neural Computing Simulation and Validation of Automated Driving Parameters Using AI Neural Network-Based Methodologies for Test Scenario Generation Hardware/Vehicle in the Loop Simulation with Intelligent Systems Practical Systems Modeling in ACE Technologies Real-World Case Studies Demonstrating the Application of Neural Computing in ACE Vehicles Guest Editors: Yang Liu, Chalmers University of Technology, Sweden, liuy@chalmers.se Tom Shi, University of Wisconsin-Milwaukee, USA, tomshi@uwm.edu Xiaopeng (Shaw) Li, University of Wisconsin-Madison, USA, xli2485@wisc.edu Xiaobo Qu, Tsinghua University, China, xiaobo@tsinghua.edu.cn Manuscript submission deadline: 30th November 2024 This topical collection is connected to SDG 11: Sustainable cities & communities
Last updated by Dou Sun in 2024-07-17
Special Issue on Explainable Sequential Decision-Making
Submission Date: 2025-01-01

Aims and Scope As we work with AI and rely on AI for more and more decisions that influence our lives, the research area of explainable AI (XAI) has rapidly developed, with goals such as increasing trust, enhancing collaboration, and enabling transparency in AI. The focus of this topical collection is on explainable sequential decision-making – XAI for systems that are required to make a sequence of decisions to achieve their goals or objectives. This stands in contrast to the substantial existing work on interpretable machine learning, which generally focuses on the single input-output mappings of "black box" models such as neural networks. While such ML models are an important tool, intelligent behavior extends over time and needs to be explained and understood as such. We may have superhuman chess agents, but can they teach us how to play? We may have search & rescue robots, but can we effectively and efficiently communicate with them in the field? This topical collection targets high-quality original papers covering all aspects of explainable sequential decision-making. Manuscripts that extend a previous conference or workshop publication are welcome, provided that there is a significant amount (at least 30%) of new material in the submission. Relevant topics include, but are not limited to, the following: Explainable/interpretable/intelligible reinforcement learning Explainable planning and search Explainability in Multi-Agent Systems Explainability for and through negotiations or argumentation Extended explanatory dialogue with users Modeling users over extended interactions Explanation-aware sequential decision-making Foundational frameworks for formalizing and evaluating explainable agency in sequential decision-making settings Integration of explainable agents and explainable deep learning, e.g. when DL models are guiding agent behaviors User interfaces/visualizations for explaining agent behavior, learning or planning Evaluation methods for explainable sequential decision-making systems Explainability for embodied systems/robotics Other practical applications for explainability in sequential or goal-oriented tasks, e.g. in planning/scheduling, in pathfinding, etc. Policy/plan summarization Cognitive theories Empirical studies in explainable sequential decision making Guest Editors Hendrik Baier (Lead Guest Editor), Eindhoven University of Technology, The Netherlands, h.j.s.baier@tue.nl Sarath Sreedharan, Colorado State University, USA, ssreedh3@colostate.edu Manuscript submission deadline: 1st January 2025
Last updated by Dou Sun in 2024-07-17
Special Issue on Multi-Objective Decision Making 2024 (MODeM 2024)
Submission Date: 2025-02-17

Building on two previous successful topical collections (TCs), we are delighted to invite submissions to a new topical collection of Neural Computing and Applications (NC&A, impact factor 6.0) on Multi-Objective Decision Making 2024 (MODeM 2024). Previous topical collections in this series were hosted in: Neural Computing and Applications - TC on MODeM 2023 (in progress) Journal of Autonomous Agents and Multi-Agent Systems - TC on MODeM (completed in 2023) Explicitly modelling multiple objectives can be essential for decision support, explainability, and human-AI alignment. As such, there has been a growing awareness of the need for automated and assistive decision making systems to move beyond single-objective formulations when dealing with complex real-world issues, which invariably involve multiple competing objectives. In this topical collection, we aim to provide a platform for original research in multi-objective decision making using AI. This topical collection targets high-quality original papers covering all aspects of multi-objective decision making, including, but not limited to, the list of topics below. Manuscripts that extend a previous conference or workshop publication are welcome, provided that there is a significant amount of new material in the submission (i.e., the manuscript should contain at least 50% new material). Please note that manuscripts submitted to this TC should have a clear link to artificial intelligence and/or agent-based systems - manuscripts without a clear link to these areas will be desk rejected without being sent for review. Topics The following is a non-exhaustive list of topics that we would like to cover in the topical collection: Multi-objective/multi-criteria/multi-attribute decision making Multi-objective reinforcement learning Multi-objective planning and scheduling Multi-objective multi-agent decision making Multi-objective game theory Multi-objective/multi-criteria/multi-attribute utility theory Preference elicitation for MODeM Social choice and MODeM Multi-objective decision support systems Multi-objective metaheuristic optimisation (e.g., evolutionary algorithms) for autonomous agents and multi-agent systems Multi-objectivisation Human-AI alignment through multi-objective modelling Ethical AI through multi-objective modelling Explainable AI through multi-objective modelling Interactive systems for MODeM Applications of MODeM Interdisciplinary work (MODeM research that relates to other fields) New benchmark problems for MODeM Guest Editors Roxana Rădulescu (Lead Guest Editor), Utrecht University & Vrije Universiteit Brussel, r.t.radulescu@uu.nl Patrick Mannion, University of Galway Pieter Libin, Vrije Universiteit Brussel Please direct queries about the NC&A MODeM 2024 TC to the Lead Guest Editor at r.t.radulescu@uu.nl Timeline Submission deadline: 17th February 2025 Manuscript submissions will be considered for publication in the NC&A MODeM 2024 TC on a continuous basis until the submission deadline. Submissions accepted for publication before the completion of the TC will be available on the journal website shortly after acceptance.
Last updated by Dou Sun in 2024-07-17
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