Backpropagation
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Recent papers in Backpropagation
In this paper, a new algorithm for Automatic License Plate Localisation and Recognition (ALPR) is proposed on the basis of isotropic dilation that can be achieved using the binary image Euclidean distance transform. In a blob analysis... more
Levenberg-Marquardt back-propagation training method has some limitations associated with over fitting and local optimum problems. Here, we proposed a new algorithm to increase the convergence speed of Backpropagation learning to design... more
With the rise of web-based education systems and the increased use of information systems in education institutions, the amount of data recorded on student performance and behavior has increased exponentially. Thus, bringing about a large... more
7.2 Phoneme Recognition Using Time-Delay Neural Networks 395 Fig. 1. A Time-Delay Neural Network (TDNN) unit. BOG Output layer integration Hidden Layer 2 Hidden layer 1 I Input layer 15 frames 10 msec frame rate Fig. 2. The architecture... more
In response to the growing concern over the use of fossil fuels, renewable energy industries have been significant economic drivers in many parts of the United States. In the recent years there is a strong growth in solar power generation... more
ANN Backpropagation adalah metode dengan algoritma pembelajaran untuk memperkecil tingkat error dengan cara menyesuaikan bobotnya berdasarkan perbedaan output dan target yang diinginkan. Pada percobaan kali ini fungsi aktivasi yang... more
Technological intelligence is a highly sought after commodity even in traffic-based systems. These intelligent systems do not only help in traffic monitoring but also in commuter safety, law enforcement and commercial applications. In... more
The authors propose a general fuzzy classification scheme with learning ability using an adaptive network. System parameters, such as the membership functions defined for each feature and the parameterized t-norms used to combine... more
... Olatoyosi Olude Department of Systems Science & Industrial Engineering ... In order to improve the stock market performance, Quah & Srinivasan [31] proposed a stock selection system using ANN to select stocks that are... more
The objective of this paper is to develop the hybrid neural network models for bankruptcy prediction. The proposed hybrid neural network models are (1) a MDA-assisted neural network, (2) an ID3-assisted neural network, and (3) a SOFM(self... more
Cuenca 2 Programa para el manejo del agua y el suelo (PROMAS), Universidad de Cuenca Resumen La aplicación de modelos matemáticos en el manejo de cuencas hidrográficas tiene requerimientos exigentes de información y en su mayoría no han... more
In the dynamic global economy, the accuracy in forecasting the foreign currency exchange (Forex) rates or at least predicting the trend correctly is of crucial importance for any future investment. The use of computational intelligence... more
This study and research aimed is to classify and predict the credit card default customers payment by means of contemporary approach of artificial neural network (ANN) known as deep neural network. This paper explains the dataset which... more
An approach using a convolutional neural network (CNN) is proposed for real-time gender classification based on facial images. The proposed CNN architecture exhibits a much reduced design complexity when compared with other CNN solutions... more