Abstract: This paper presents a dual neural network based technique for detecting and classifying the power quality disturbances. In the proposed method, Adaptive Linear Neural Network is used to extract the rms voltage for harmonics and Interharmonics estimations. With the help of these indices, PQ disturbances such as Sag, Swell, Outages are detected and classified, Harmonics and Interharmoni...

Work had always been under process to design efficient algorithms for image compression based on various conventional and soft computing methodologies. This paper aims at exploring the application of multi layered perceptron (MLP) feed forward neural networks (FFNN), wavelet transforms and their combination architectures for image compression. Initially two neural network architectures for imag...

Rainfall prediction is very complex hydrologic process and is important as it holds the key to any countries’ economy. Proposed model presents a new approach for yearly rainfall prediction of 30 Indian subdivisions. Yearly rainfall data of the Indian subdivision is available from IITM, Pune. The combination of Fast Fourier Transform (FFT) and Feed Forward Neural Network (FFNN) is applied for ne...

The differential diagnosis of erythemato-squamous diseases is a difficult problem in dermatology. Artificial Neural Network (ANN) classifies the given samples when trained and nearly 98 % classification accuracy is achieved. Generalized Feed Forward Neural Network (FFNN) can solve the multivariable classification problem of determination of skin disease. ANN approach is studied to determine the...

Sentence boundary identification is an important step for text processing tasks, e.g., machine translation, POS tagging, text summarization etc., in this paper, we present an approach comprising of Feed Forward Neural Network (FFNN) along with part of speech information of the words in a corpus. Proposed adaptive system has been tested after training it with varying sizes of data and threshold ...

s – Mini Symposia 34 MS 6 (Monday 22, 15:45 – 17:15) Room C Indonesian PhD Students Minisymposium 1: Statistics and Neural Network Organizer: W.M. Kusumawinahyu (Dept. of Math., ITB, Indonesia) Brodjol Sutijo, Subanar, Suryo Guritno 1) Mathematics Department, Gadjah Mada University, Indonesia 2) Statistics Department, Sepuluh Nopember Institut of Technology, Indonesia Title: Construction and Tr...

CONTEXT is vital in formulating intelligent classifications and responses, especially under uncertainty. In a standard feed-forward neural network (FFNN), context comes in the form of information encoded in the input vector and trained in weight parameters. However, useful information can also be present in the temporal nature of the input vectors, or from past internal states of a network. Fut...

Priyanka Agrawal student, electrical, mits, rgpv, gwalior, mp 474005, india† Dr. A. K. Wadhwani professor, electrical ,mits, rgpv gwalior, mp 474005, india Abstract : This paper deals with the designing of feed forward neural network (FFNN) with the effect of ANN parameters for feature extraction of ECG signal by employing wavelet decomposition. Extraction of ECG features has a significance rol...

This study proposes a novel approach based on multi-objective artificial bee colony (ABC) for feature selection, particularly for intrusion-detection systems. The approach is divided into two stages: generating the feature subsets of the Pareto front of non-dominated solutions in the first stage and using the hybrid ABC and particle swarm optimization (PSO) with a feed-forward neural network (F...