in recent decades, the developments of artificial intelligence to predict hydrologic models have been widely used. in this study, the ability of artificial neural network(ann) models for modeling and predict the biological oxygen demand (bod) is located on the karun river in west iran were evaluated. to improve the simulation results, wavelet analysis was used as a hybrid model. bod index month...

Anomalous propagation echo belongs to representative non-precipitation echoes which have very similar characteristics of precipitation echoes. It occurs due to superrefraction or ducting phenomenon of radar beam by temperature or humidity. There are a lot of ongoing researches about detecting and removing the anomalous propagation echo in radar data in order to improve accuracy of data analysis...

Voice Recognition using Distributed Artificial Neural Network for Multiresolution Wavelet Transform Decomposition

there are a variety of electrocardiogram (ecg) based methods to detect myocardial infarction (mi) patients. this study used the signal averaged electrocardiogram (saecg) and its wavelet coefficient as an index to detect mi. orthogonal leads signals from 50 acute myocardial infarction (ami) and 50 healthy subjects were selected from the national metrology institute of germany (ptb diagnostic dat...

Prediction of traffic is very crucial for its management. Because of human involvement in the generation of this phenomenon, traffic signal is normally accompanied by noise and high levels of non-stationarity. Therefore, traffic signal prediction as one of the important subjects of study has attracted researchers’ interests. In this study, a combinatorial approach is proposed for traffic signal...

An appropriate method for fault identification and classification on extra high voltage transmission line using discrete wavelet transform is proposed in this paper. The sharp variations of the generated short circuit transient signals which are recorded at the sending end of the transmission line are adopted to identify the fault. The threshold values involve fault classification and these are...

Automatic identification and localization of cartographic objects in aerial and satellite images have gained increasing attention in recent years in digital photogrammetry and remote sensing. Although the automatic extraction of man made objects in essence is still an unresolved issue, the man made objects can be extracted from aerial photos and satellite images. Recently, the high-resolution s...

Received Nov 07, 2016 Revised Jan 13, 2017 Accepted Jan 23, 2017 An appropriate fault detection and classification of power system transmission line using discrete wavelet transform and artificial neural networks is performed in this paper. The analysis is carried out by applying discrete wavelet transform for obtained fault phase currents. The work represented in this paper are mainly concentr...