Advanced Artificial Neural Networks II

Dear Colleague,

Artificial neural networks (ANNs) have been extensively applied to a wide range of disciplines, such as system identification and control, decision-making, pattern recognition, medical diagnosis, finance, data mining, visualization, and others. With advances in computing and networking technologies, more complicated forms of ANNs are expected to emerge, requiring the design of advanced learning algorithms. This Special Issue is intended to provide technical details for the construction and training of advanced ANNs. These details will hold great interest for researchers in computer science, artificial intelligence, soft computing, and information management, as well as for practicing engineers. This Special Issue will feature a balance between state-of-the-art research and practical applications. It will also provide a forum for researchers and practitioners to review and disseminate quality research work on advanced ANNs and identify critical issues for ANNs’ further development.

Prof. Dr. Tin-Chih Toly Chen
Dr. Cheng-Li Liu
Dr. Hong-Dar Lin
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• artificial neural network
• algorithm
• learning