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Neural Computing and Applications

Neural Computing and Applications OnlineFirst articles

15.12.2018 | Original Article

Nuclear Fission–Nuclear Fusion algorithm for global optimization: a modified Big Bang–Big Crunch algorithm

This study introduces a derivative of the well-known optimization algorithm, Big Bang–Big Crunch (BB–BC), named Nuclear Fission–Nuclear Fusion-based BB–BC, simply referred to as N2F. Broadly preferred in the engineering optimization community …

15.12.2018 | Intelligent Biomedical Data Analysis and Processing

A-COA: an adaptive cuckoo optimization algorithm for continuous and combinatorial optimization

Cuckoo optimization algorithm (COA) is inspired from the special and exotic lifestyle of a bird family called the cuckoo and her amazing and unique behavior in egg laying and breeding. Just like any other population-based swarm intelligence …

13.12.2018 | Review Article

Neural network applications in fault diagnosis and detection: an overview of implementations in engineering-related systems

The use of artificial neural networks (ANN) in fault detection analysis is widespread. This paper aims to provide an overview on its application in the field of fault identification and diagnosis (FID), as well as the guiding elements behind their …

13.12.2018 | Deep learning for music and audio

Singing voice separation using a deep convolutional neural network trained by ideal binary mask and cross entropy

Separating a singing voice from its music accompaniment remains an important challenge in the field of music information retrieval. We present a unique neural network approach inspired by a technique that has revolutionized the field of vision: …

12.12.2018 | Original Article

Large-margin Distribution Machine-based regression

This paper presents an efficient and robust Large-margin Distribution Machine formulation for regression. The proposed model is termed as ‘Large-margin Distribution Machine-based Regression’ (LDMR) model, and it is in the spirit of Large-margin …

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Über diese Zeitschrift

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 contributions in the area of applicable neural networks theory, supervised and unsupervised learning methods, algorithms, architectures, performance measures, applied statistics, software simulations, hardware implementations, benchmarks, system engineering and integration and case histories of innovative applications.

Featured contributions fall into several categories: Original Articles, Review Articles, Forum Presentations, Book Reviews, Announcements and NCAF News.

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. The Forum Presentations will be summaries of oral presentations made at quarterly meetings of the Natural Computing Applications Forum which will generally be reviewed by one referee.

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