We present a comprehensive review of the evolutionary design of neural network
architectures. This work is motivated by the fact that the success of an Artificial Neural …

Artificial neural networks (ANN) provide a range of powerful new techniques for solving
problems in sensor data analysis, fault detection, process identification, and control and …

Abstract The Multi-Layer Perceptron (MLP), as one of the most-widely used Neural Networks
(NNs), has been applied to many practical problems. The MLP requires training on specific …

The most pressing issue in network security is the establishment of an approach that is
capable of detecting violations in computer systems and networks. There have been several …

In the field of medical informatics, the accuracy of medical data classification plays a vital
role. Multi-layer Perceptron (MLP), as one of the most widely used neural networks, has …

Arguably the most recurring issue concerning network security is building an approach that
is capable of detecting intrusions into network systems. This issue has been addressed in …

This paper introduces a parallel meta-heuristic algorithm called Cuckoo Flower Search
(CFS). This algorithm combines the Flower Pollination Algorithm (FPA) and Cuckoo Search …

Medical data classification is an important factor in improving diagnosis and treatment and
can assist physicians in making decisions about serious diseases by collecting symptoms …

Artificial neural networks are widely used in data analysis and to control dynamic processes.
These tools are powerful and versatile, but the way in which they are constructed, in …

Training multi-layer perceptron (MLP) is non-trivial due to its non-linear nature and the
presence of large number of local optima. Meta-heuristic algorithms may solve this problem …