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...

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...

Agricultural sector area plays major role in Indian economy. This paper shows research comparison in between MLP Feed Forward Neural Network, Generalized Regression Neural Network and Radial-Basis Function Neural Network in the field of Wheat yield prediction using Z-score Normalization method. The outcome represents that GRNN present better prediction results as compared to FFNN and RBNN. Eigh...

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...

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 ...

The use of Artificial Intelligence methods is becoming increasingly common in the modeling and forecasting of hydrological and water resource processes. In this study, applicability of Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) methods, Generalized Regression Neural Networks (GRNN) and Feed 5 Forward Neural Networks (FFNN), for forecasting of daily river f...

this paper proposes a method for the prediction of pore size values in hydrocarbon reservoirs using 3d seismic data. to this end, an actual carbonate oil field in the south-western part ofiranwas selected. taking real geological conditions into account, different models of reservoir were constructed for a range of viable pore size values.  seismic surveying was performed next on these models. f...

Alpha-galactosidase production in submerged fermentation by Acinetobacter sp. was optimized using feed forward neural networks and genetic algorithm (FFNN-GA). Six different parameters, pH, temperature, agitation speed, carbon source (raffinose), nitrogen source (tryptone), and K2HPO4, were chosen and used to construct 6-10-1 topology of feed forward neural network to study interactions between...

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...