Neural Network World

Scope & Guideline

Unveiling the Future of Neural Networks and Their Applications

Introduction

Explore the comprehensive scope of Neural Network World through our detailed guidelines, including its aims and scope. Stay updated with trending and emerging topics, and delve into declining areas to understand shifts in academic interest. Our guidelines also showcase highly cited topics, featuring influential research making a significant impact. Additionally, discover the latest published papers and those with high citation counts, offering a snapshot of current scholarly conversations. Use these guidelines to explore Neural Network World in depth and align your research initiatives with current academic trends.
LanguageEnglish
ISSN1210-0552
PublisherACAD SCIENCES CZECH REPUBLIC, INST COMPUTER SCIENCE
Support Open AccessNo
CountryCzech Republic
TypeJournal
Convergefrom 1994 to 2023
AbbreviationNEURAL NETW WORLD / Neural Netw. World
Frequency6 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressPOD VODARENSKOU VEZI 2, 182 07 PRAGUE 8 00000, CZECH REPUBLIC

Aims and Scopes

The journal 'Neural Network World' primarily focuses on the application and development of neural network methodologies in various domains. It aims to bridge theoretical advancements in neural networks with practical applications across multiple fields, including engineering, healthcare, transportation, and data analysis.
  1. Neural Network Architecture Development:
    Research on innovative architectures and modifications of neural networks, enhancing their performance and applicability in complex tasks.
  2. Machine Learning Applications:
    Exploration of machine learning techniques, particularly neural networks, applied to real-world problems such as medical diagnostics, transportation systems, and environmental monitoring.
  3. Interdisciplinary Approaches:
    Integration of neural networks with other disciplines, such as robotics, IoT, and bioinformatics, to leverage their capabilities in solving multifaceted challenges.
  4. Theoretical Foundations and Algorithms:
    Advancements in the theoretical understanding of neural networks, including learning algorithms, optimization techniques, and model evaluation metrics.
  5. Data-Driven Decision Making:
    Utilization of neural networks to enhance decision-making processes through data analysis, predictive modeling, and automated systems.
Recent publications in 'Neural Network World' indicate a strong shift towards innovative applications and advanced methodologies within the neural network domain. This trend reflects the evolving landscape of technology and research needs.
  1. Integration of Neural Networks with IoT:
    There is a rising interest in applying neural networks to Internet of Things (IoT) systems, particularly for predictive analytics and real-time decision-making.
  2. Healthcare Applications:
    An increasing number of studies focus on leveraging neural networks for healthcare applications, including diagnostics, medical imaging, and patient monitoring.
  3. Adversarial Machine Learning:
    Research on adversarial attacks and defenses in machine learning illustrates a growing concern about the security and robustness of neural network systems.
  4. Environmental and Energy Systems:
    Emerging themes include the application of neural networks in environmental monitoring and energy management, reflecting global sustainability efforts.
  5. Multi-Modal Data Processing:
    There is an increasing emphasis on utilizing neural networks to analyze multi-modal data, combining various types of information (e.g., images, text, and sensor data) for comprehensive insights.

Declining or Waning

While the journal continues to thrive in various areas, some themes appear to be diminishing in frequency or relevance. This may reflect shifts in research priorities or the emergence of new methodologies and technologies.
  1. Traditional Statistical Methods:
    There has been a noticeable decline in the use of classical statistical methods in favor of more advanced machine learning techniques, particularly deep learning.
  2. Basic Neural Network Applications:
    Research focusing solely on basic neural network applications without innovative modifications or integrations has decreased, as the field moves towards more complex and tailored solutions.
  3. Limited Scope of Basic Image Processing:
    The focus on basic image processing tasks has waned, with a shift towards more complex applications involving multi-modal data and advanced neural architectures.
  4. One-Dimensional Data Analysis:
    Studies concentrating on one-dimensional data analysis are becoming less prominent, as researchers are increasingly exploring multi-dimensional and complex datasets.
  5. Generalized Neural Network Models:
    There is a decline in papers that propose generalized neural network models without specific applications or improvements, as the field demands more specialized and effective approaches.

Similar Journals

Foundations of Data Science

Transforming Data into Discoveries
Publisher: AMER INST MATHEMATICAL SCIENCES-AIMSISSN: Frequency: 4 issues/year

Foundations of Data Science, published by the American Institute of Mathematical Sciences (AIMS), is a pioneering journal dedicated to advancing knowledge within the ever-evolving fields of data science, mathematics, and computational theory. With an impact factor reflecting its quality and relevance, this journal has established itself as a crucial resource for researchers and professionals alike, achieving remarkable rankings in the Scopus metrics across various mathematical categories, including 35th in Analysis and 70th in Statistics and Probability. The journal, which has been continuously growing in significance since its inception in 2019, focuses on both foundational theories and applied methodologies, providing open access to cutting-edge research from 2024 onward. Its commitment to fostering interdisciplinary collaboration ensures that it remains at the forefront of the data science realm, making it an essential platform for students, scholars, and practitioners aiming to deepen their understanding and contribute to the scientific community.

Computational Management Science

Advancing the Future of Management Through Computational Insights
Publisher: SPRINGER HEIDELBERGISSN: 1619-697XFrequency: 4 issues/year

Computational Management Science, published by SPRINGER HEIDELBERG, is a significant journal catering to the intersection of technology, management, and decision sciences. With an ISSN of 1619-697X and E-ISSN 1619-6988, this journal serves as a platform for innovative research focusing on computational methods applied to management science, operations research, and information systems. Based in Germany, the journal spans a critical period from 2005 to 2024, emphasizing trends that shape the future of the field. As a Tier 3 journal in multiple categories including Business, Management, and Accounting, and ranked across various disciplines with Scopus rankings highlighting its relevance, it stands out in fostering scholarly discourse. The journal invites contributions that enhance the application of computational techniques in decision-making, thereby enriching the practices of both academics and industry professionals. While it currently does not offer open access, its influence is reflected in its established readership and community engagement. Researchers, practitioners, and students alike will find in this journal a vital resource for advancing knowledge and sparking innovation in computational management.

Quantum Machine Intelligence

Exploring the synergy between quantum computing and machine intelligence.
Publisher: SPRINGERNATUREISSN: 2524-4906Frequency: 1 issue/year

Quantum Machine Intelligence is a leading academic journal published by Springer Nature, focusing on the rapidly evolving intersection of quantum computing and artificial intelligence. With an impressive impact factor reflected in its prestigious ranking in various categories—Q1 in Applied Mathematics, Computational Theory and Mathematics, and Theoretical Computer Science, alongside Q2 in Artificial Intelligence and Software—this journal serves as a vital platform for disseminating innovative research from 2019 to 2024. Researchers, professionals, and students are encouraged to engage with the journal’s content, which features high-quality peer-reviewed articles that explore theoretical foundations and practical applications of quantum technologies in machine intelligence. Although the journal operates under traditional subscription models, it is committed to advancing open academic discourse and accessibility in the digital age. With Scopus rankings that place it among the top echelons of its fields, the journal is an essential resource for anyone interested in the transformative potential of quantum algorithms and AI.

International Journal of Computational Intelligence Systems

Advancing Knowledge in Computational Intelligence
Publisher: SPRINGERNATUREISSN: 1875-6891Frequency: 1 issue/year

International Journal of Computational Intelligence Systems, published by SPRINGERNATURE, is a leading open-access journal that has been at the forefront of research in the field of computational intelligence since 2008. With an ISSN of 1875-6891 and an E-ISSN of 1875-6883, this journal occupies a prominent place in the academic landscape, achieving impressive rankings in its categories: Q2 in both Computational Mathematics and Computer Science (miscellaneous), reflecting its significance and relevance to researchers, professionals, and students. Based in Switzerland, the journal is committed to disseminating high-quality research and fostering innovation in computational methodologies, algorithms, and applications. Its strong impact factor and Scopus rankings—31/189 in Computational Mathematics and 53/232 in General Computer Science—underscore its critical role in advancing knowledge in these interdisciplinary fields. As an open-access journal, it provides unparalleled accessibility to cutting-edge research, supporting the global community in staying at the forefront of computational intelligence advancements.

Grey Systems-Theory and Application

Redefining Boundaries: The Intersection of Theory and Practice
Publisher: EMERALD GROUP PUBLISHING LTDISSN: 2043-9377Frequency: 4 issues/year

Grey Systems - Theory and Application is a premier journal dedicated to advancing the field of grey systems theory, which plays a pivotal role in addressing uncertainties in complex systems across various domains. Published by Emerald Group Publishing Ltd in the United Kingdom, this journal has established itself as a respected platform for innovative research, boasting a commendable 2023 impact factor reflected in its Q2 categorization in applied mathematics, computer science, and control systems engineering. With Scopus rankings placing it in the top tiers of its fields, it provides a robust forum for researchers, professionals, and students to explore theoretical developments and practical applications. The journal, which has been converged from 2011 to 2024, encourages open conversations on the theoretical underpinnings and real-world implications of grey systems, making it an essential resource for those looking to deepen their understanding and contribute meaningfully to this dynamic area of study.

International Journal of Neural Systems

Unveiling Innovations in Neural Systems for a Better Tomorrow
Publisher: WORLD SCIENTIFIC PUBL CO PTE LTDISSN: 0129-0657Frequency: 10 issues/year

The International Journal of Neural Systems, published by World Scientific Publishing Co Pte Ltd, is a prestigious peer-reviewed journal dedicated to the dynamic field of neural systems research. With an ISSN of 0129-0657 and an E-ISSN of 1793-6462, this journal serves as a vital resource for researchers, professionals, and students interested in the intersections of computer science, neural networks, and communications. Noteworthy for its impact, the journal has achieved impressive rankings in 2023, positioned in the Q1 quartile for both Computer Networks and Communications as well as in the miscellaneous category of Medicine, highlighting its interdisciplinary significance and broad relevance. The journal's Scopus rank places it at #33 out of 395 in its category, reflecting its influence and reach within the academic community. While the journal is not open access, its contributions to advancing the understanding of neural systems are invaluable, offering a platform for disseminating cutting-edge research and fostering collaboration among scholars. Since its inception, the International Journal of Neural Systems remains committed to excellence and innovation in its published content, making it an essential subscription for everyone involved in this exciting and rapidly evolving field.

IEEE Computational Intelligence Magazine

Unveiling Insights in Machine Learning and Data Mining
Publisher: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCISSN: 1556-603XFrequency: 4 issues/year

IEEE Computational Intelligence Magazine, published by the esteemed IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, is an essential resource for researchers and professionals in the fields of Artificial Intelligence and Theoretical Computer Science. With a robust Q1 ranking in both categories for 2023, this magazine stands out as a leader in disseminating cutting-edge research and innovative applications within computational intelligence. As an invaluable conduit for knowledge, it covers a diverse range of topics, including but not limited to machine learning, neural networks, and data mining. The magazine is particularly recognized for its interdisciplinary approach, bridging gaps between theory and application while contributing to advancements in technology and society. Although it does not offer open access, the insights provided are critical for staying at the forefront of this rapidly evolving discipline. Join a community of like-minded scholars and practitioners by exploring the latest findings and trends published from 2006 to 2024, operating from its headquarters at 445 Hoes Lane, Piscataway, NJ, United States.

NEURAL COMPUTING & APPLICATIONS

Advancing the Frontiers of AI and Software Engineering
Publisher: SPRINGER LONDON LTDISSN: 0941-0643Frequency: 12 issues/year

NEURAL COMPUTING & APPLICATIONS is a premier journal dedicated to the burgeoning fields of Artificial Intelligence and Software Engineering, published by Springer London Ltd. Established in 1993, the journal serves as a pivotal platform for disseminating cutting-edge research and innovative applications in neural computing, covering a broad range of topics from algorithm development to real-world applications. With its impressive categorization in the 2023 Journal Quartiles—ranging Q2 in Artificial Intelligence and Q1 in Software—it stands out in its discipline, ranking 42nd out of 407 in Computer Science Software and 50th out of 350 in Computer Science Artificial Intelligence, reflecting its significant impact in the academic community. Although not an open access journal, it provides vital access to significant findings and methodologies that drive advancements in technology. Researchers, professionals, and students looking to stay abreast of the most relevant and impactful developments in these fields will find NEURAL COMPUTING & APPLICATIONS an indispensable resource.

JOURNAL OF INFORMATION SCIENCE AND ENGINEERING

Empowering Research in Information and Engineering.
Publisher: INST INFORMATION SCIENCEISSN: 1016-2364Frequency: 6 issues/year

JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, published by the Institute of Information Science in Taiwan, is a pivotal platform for the dissemination of innovative research in the multidisciplinary fields of information science and engineering. Established in 1993, the journal primarily focuses on areas such as library and information sciences, human-computer interaction, hardware and architecture, as well as computational theory and software development. Despite holding a current Q4 ranking in several categories, the journal demonstrates significant potential for growth, particularly in computation and software systems, as evidenced by its Scopus rankings and percentiles. Researchers, professionals, and students will find this journal to be an invaluable resource to stay abreast of evolving theories and technologies in information science. The journal is accessible through traditional subscription models, fostering a broad academic outreach. It serves to enhance knowledge-sharing and collaboration within this dynamic and ever-evolving field.

NETWORK-COMPUTATION IN NEURAL SYSTEMS

Unlocking the Secrets of Neural Networks Through Computation
Publisher: TAYLOR & FRANCIS INCISSN: 0954-898XFrequency: 4 issues/year

NETWORK-COMPUTATION IN NEURAL SYSTEMS is a distinguished journal published by Taylor & Francis Inc, focusing on the innovative intersection of network theory and neural computation. Since its inception in 1990, this journal has provided a vital platform for researchers and professionals in the field of neuroscience, exploring the dynamics of neural networks and computational models. With its current Q3 category ranking in Neuroscience (miscellaneous) and a robust position in Scopus, the journal plays a critical role in advancing knowledge and discussion within this interdisciplinary area. The journal addresses a wide range of topics related to the computational aspects of neural systems, fostering collaboration and providing valuable insights amongst scholars. Although it is not an open-access publication, its well-curated content remains accessible through institutional subscriptions, ensuring that significant research reaches the hands of those who need it. As it continues to evolve through 2024 and beyond, NETWORK-COMPUTATION IN NEURAL SYSTEMS stands as a key resource for anyone deeply engaged in understanding the complexities and intricacies of neural computations.