The Official Journal of the Asia-Pacific Neural Network Society, the International Neural Network Society & the Japanese Neural Network Society Neural Networks provides a forum for developing and nurturing an international community of scholars and practitioners who are interested in all aspects of neural networks, including deep learning and related approaches to artificial intelligence and machine learning. Neural Networks welcomes submissions that contribute to the full range of neural networks research, from cognitive modeling and computational neuroscience, through deep neural networks and mathematical analyses, to engineering and technological applications of systems that significantly use neural network concepts and learning techniques. This uniquely broad range facilitates the cross-fertilization of ideas between biological and technological studies and helps to foster the development of the interdisciplinary community that is interested in biologically-inspired artificial intelligence. Accordingly, the Neural Networks editorial board represents experts in fields including psychology, neurobiology, computer science, engineering, mathematics, and physics. The journal publishes articles, letters, and reviews, as well as letters to the editor, editorials, current events, and software surveys. Articles are published in one of four sections: learning systems, cognitive and neural science, mathematical and computational analysis, engineering and applications. Neural Networks is the archival journal of the world's three oldest neural modeling societies: the International Neural Network Society (INNS), the European Neural Network Society (ENNS), and the Japanese Neural Network Society (JNNS). A subscription to the journal is included with membership in each of these societies. Members of the societies listed as affiliated to the journal receive a 25% discount on Article Processing Charges when they publish an article in Neural Networks as an author - this will be detailed through the submission and production processes.

Neural Networks (NN) is :

International, Peer-Reviewed, Open Access, Refereed, Neuroscience, Control, Optimization, Artificial Intelligence, Engineering, Computer Science , Online or Print, Monthly Journal

UGC Approved, ISSN Approved: P-ISSN - 0893-6080, E-ISSN - 1879-2782, Established in - 1988, Impact Factor - 7.9

Not Provide Crossref DOI

Indexed in Scopus, WoS

Not indexed in DOAJ, PubMed, UGC CARE

Long Tang

September, 2023

A simple and reliable instance selection for fast training support vector machine: Valid Border Recognition

Support vector machines (SVMs) are powerful statistical learning tools, but their application to large datasets can cause time-consuming training complexity. To address this issue, various i...

Pietro Liò

May, 2023

HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN

Deep learning-based models have achieved significant success in detecting cardiac arrhythmia by analyzing ECG signals to categorize patient heartbeats. To improve the performance of such mod...

Mohammad Ali Moni

May, 2023

HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN

Deep learning-based models have achieved significant success in detecting cardiac arrhythmia by analyzing ECG signals to categorize patient heartbeats. To improve the performance of such mod...

Neural Networks (NN)

Journal Descriptions

Neural Networks (NN) is :

International, Peer-Reviewed, Open Access, Refereed, Neuroscience, Control, Optimization, Artificial Intelligence, Engineering, Computer Science , Online or Print, Monthly Journal

UGC Approved, ISSN Approved: P-ISSN - 0893-6080, E-ISSN - 1879-2782, Established in - 1988, Impact Factor - 7.9

Not Provide Crossref DOI

Indexed in Scopus, WoS

Not indexed in DOAJ, PubMed, UGC CARE

Indexing

Scopus

WoS

ABCD

Elsevier

Science Direct

SJR

ISSN Portal

Peeref

Publications of NN

A simple and reliable instance selection for fast training support vector machine: Valid Border Recognition

HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN

HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN

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Neural Networks (NN)

Journal Descriptions

Neural Networks (NN) is :

International, Peer-Reviewed, Open Access, Refereed, Neuroscience, Control, Optimization, Artificial Intelligence, Engineering, Computer Science , Online or Print, Monthly Journal

UGC Approved, ISSN Approved: P-ISSN - 0893-6080, E-ISSN - 1879-2782, Established in - 1988, Impact Factor - 7.9

Not Provide Crossref DOI

Indexed in Scopus, WoS

Not indexed in DOAJ, PubMed, UGC CARE

Indexing

Scopus

WoS

ABCD

Elsevier

Science Direct

SJR

ISSN Portal

Peeref

Publications of NN

A simple and reliable instance selection for fast training support vector machine: Valid Border Recognition

HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN

HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN

Establish Your Own Journal Without the Expense!

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