Neural Network World

Scope & Guideline

Advancing Knowledge in Neural Networks and Beyond

Introduction

Delve into the academic richness of Neural Network World with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly 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

Journal of Membrane Computing

Pioneering Research at the Intersection of Theory and Application
Publisher: SPRINGERNATUREISSN: 2523-8906Frequency: 4 issues/year

Journal of Membrane Computing is an esteemed academic journal published by SpringerNature, focused on the innovative intersection of applied mathematics and computational theory. With an ISSN of 2523-8906 and an E-ISSN of 2523-8914, this journal plays a pivotal role in advancing the field, currently holding a commendable Q2 category rank in both applied mathematics and computational theory as of 2023. Its prestigious positioning—ranked #80 out of 635 in Applied Mathematics and #37 out of 176 in Computational Theory—places it in the top percentiles, reflecting its significant contributions to the discourse within these domains. Operating from Germany, the journal serves as a vital resource for researchers, professionals, and students, seeking to explore new theoretical frameworks and applications in membrane computing. With a focus on open access, it ensures that groundbreaking research is accessible to a broad audience, enhancing collaboration and innovation across disciplines. Founded in 2019, the journal continues to thrive until 2024, solidifying its position as a preeminent platform for the exchange of ideas and advancements in its field.

IEEE Computational Intelligence Magazine

Pioneering Research for a Smarter Tomorrow
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.

Journal of Electrical and Computer Engineering

Unleashing Potential in Electrical and Computer Engineering
Publisher: HINDAWI LTDISSN: 2090-0147Frequency: 1 issue/year

Journal of Electrical and Computer Engineering is a premier open-access journal published by HINDAWI LTD, dedicated to advancing the fields of electrical and computer engineering. With an ISSN of 2090-0147 and an E-ISSN of 2090-0155, this journal has been providing a platform for cutting-edge research since its inception in 2007. Based in the United States, it operates from its address at ADAM HOUSE, 3RD FLR, 1 FITZROY SQ, LONDON W1T 5HF, ENGLAND. The journal has established itself with a healthy impact factor, classified in the 2023 Q2 quartile for both Computer Science (Miscellaneous) and Electrical and Electronic Engineering, demonstrating its growing influence in the academic community. Additionally, its ranking positions it within the 67th percentile in General Computer Science and the 61st percentile in Electrical and Electronic Engineering on Scopus, indicating its significant contribution to these fields. Covering an extensive scope from 2010 to 2024, the journal seeks to publish innovative research articles, reviews, and case studies that explore new techniques and applications in electrical and computer engineering, benefiting a wide audience of researchers, professionals, and students focused on these rapidly-evolving areas.

SOFT COMPUTING

Elevating Research in Interdisciplinary Computing
Publisher: SPRINGERISSN: 1432-7643Frequency: 12 issues/year

SOFT COMPUTING is a premier international journal published by Springer, focusing on the interdisciplinary field of soft computing, which includes areas such as fuzzy logic, neural networks, genetic algorithms, and their applications. With an ISSN of 1432-7643 and E-ISSN 1433-7479, the journal is based in Germany and contributes significantly to the advancement of knowledge in its fields, boasting an impressive Scopus ranking that places it in the top echelons of Geometry and Topology, Theoretical Computer Science, and Software categories. In the 2023 category quartiles, it has achieved Q2 rankings in multiple disciplines, reflecting its high-quality research contributions. Though not Open Access, the journal's rigor and relevance to contemporary issues make it a favored resource for researchers, professionals, and students alike. From its inception in 2000 and spanning across the years until 2024, SOFT COMPUTING continues to serve as a robust platform for innovative research and theoretical advancements, making it an essential read for anyone engaged in the rapidly evolving landscape of computational intelligence.

NETWORK-COMPUTATION IN NEURAL SYSTEMS

Exploring the Fusion of Networks and Neural Dynamics
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.

Computational Management Science

Shaping Tomorrow's Management with Innovative Computational Techniques
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.

NEURAL PROCESSING LETTERS

Innovating Insights at the Intersection of Mind and Machine.
Publisher: SPRINGERISSN: 1370-4621Frequency: 6 issues/year

NEURAL PROCESSING LETTERS, published by Springer, is a prestigious journal dedicated to the interdisciplinary fields of Artificial Intelligence, Computer Networks and Communications, Software Engineering, and Neuroscience. Established in 1994, the journal has built a solid reputation over the past decades, showcasing innovative research and developments that significantly contribute to the advancement of these dynamic areas. With a 2023 Scopus quartile ranking of Q2 in Artificial Intelligence and Computer Networks and Communications, and a Q3 ranking in Neuroscience, this journal occupies an important niche for professionals and researchers alike. The journal’s impact is further evidenced by its competitive Scopus ranks, positioning it within the top 60th percentile across its categories. Researchers looking for a platform to disseminate their findings in the intersection of technology and neuroscience will find NEURAL PROCESSING LETTERS an invaluable resource. For additional engagement and visibility, the journal supports various access options; however, it's important to note that it does not currently operate under an open access model. For submissions or queries, the journal can be reached at its headquarters in Dordrecht, Netherlands.

Foundations of Data Science

Advancing the Frontiers of Data Science Knowledge
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.

OPTICAL MEMORY AND NEURAL NETWORKS

Bridging Disciplines for Tomorrow's Technological Breakthroughs
Publisher: SPRINGERNATUREISSN: 1060-992XFrequency: 4 issues/year

OPTICAL MEMORY AND NEURAL NETWORKS is a premier academic journal dedicated to advancing the fields of optical memory technologies and neural network applications. Published by SpringerNature in the United States, this interdisciplinary journal serves as an essential platform for researchers and professionals to disseminate findings and insights that bridge the gap between computer science, electrical engineering, and materials science. With an ISSN of 1060-992X and an E-ISSN of 1934-7898, it encompasses a wide range of innovative topics across its scope, which includes but is not limited to optical storage methods, neural network modelling, and the interaction of light with electronic materials. Though currently categorized in the Q4 tier across multiple relevant disciplines—such as computer science and electrical engineering—its commitment to quality research aims to enhance its standing in the academic community by 2024. Through rigorous peer review and an emphasis on novel contributions, this journal not only encourages exploration and development in emerging areas of technology but also seeks to support the educational needs of students and practitioners alike, fostering a collaborative environment for scientific advancement.

Open Computer Science

Fostering global collaboration in computer science.
Publisher: DE GRUYTER POLAND SP Z O OISSN: 2299-1093Frequency: 1 issue/year

Open Computer Science is a premier scholarly journal published by DE GRUYTER POLAND SP Z O O, dedicated to fostering innovative research and discussions in the rapidly evolving field of computer science. With an impact factor that places it in Q2 of the computer science (miscellaneous) category, as well as a commendable Scopus ranking of #80 out of 232 and a 65th percentile standing, this journal serves as a critical resource for researchers, professionals, and students alike. Since its inception in 2011 and having embraced the open access model, Open Computer Science promotes the dissemination of knowledge across a global audience, ensuring that cutting-edge research is accessible to all. By covering a broad range of topics within the realm of computer science, this journal is committed to advancing the discipline’s theoretical and practical boundaries. The journal is published in Germany and features robust editorial standards, ensuring the inclusion of high-quality, peer-reviewed articles that contribute significantly to the field.