Artificial Neural Network (ANN) is a widely used algorithm in pattern recognition,
classification, and prediction fields. Among a number of neural networks, backpropagation …

Artificial neural networks (ANNs) have been proved to be successfully used in a variety of
pattern recognition and data mining applications. However, training ANNs on large scale …

Large scale mobile data are generated continuously by multiple mobile devices in daily
communications. Classification on such data possesses high significance for analyzing the …

Resonant frequency is a vital parameter in designing Microstrip Antenna (MSA). Artificial
Neural Network (ANN) based on Particle Swarm Optimization (PSO) algorithm (PSO-ANN) …

Faced with continuously increasing scale of data, original back-propagation neural network
based machine learning algorithm presents two non-trivial challenges: huge amount of data …

In the big data era, the need for fast robust machine learning techniques is rapidly
increasing. Deep network architectures such as cortical algorithms are challenged by big …

Artificial Neural Networks (ANN) are able to simplify recognition tasks and have been
steadily improving both in accuracy and efficiency. Classical ANN, as a universal …

Proses pembelajaran neural network merupakan hal yang penting, bertujuan untuk
mengenali lingkungan. Proses pembelajaran neural network membutuhkan waktu untuk …

Resonant frequency is an important parameter in the design process of microstrip antenna
(MSA). Artificial neural network (ANN) trained by particle swarm optimisation (PSO) …

Owing to its scalability and high fault-tolerance even on a distributed environment built up
with personal computers, MapReduce has been introduced to parallelise the training of …