Search Results - Feed-forward propagation algorithm

Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network by Azian Azamimi, Uwate, Yoko, Nishio, Yoshifumi

Get full text

Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding by Mahmoud, Omer, Anwar, Farhat, Salami, Momoh Jimoh Emiyoka

“…One of the essential factors that affect the performance of Artificial Neural Networks is the learning algorithm. The performance of Multilayer Feed Forward Artificial Neural Network performance in image compression using different learning algorithms is examined in this paper. …”
Get full text
Get full text
Get full text

Early tube leak detection system for steam boiler at KEV power plant by Ismail F.B., Singh D., Maisurah N., Musa A.B.B.

“…Backpropagation; Coal; Coal fired boilers; Engineering research; Engines; Fault detection; Fossil fuel power plants; Leak detection; Neural networks; Plant shutdowns; Steam power plants; Artificial neural network models; Coal-fired power plant; Feed-forward back propagation networks; Hidden layers; Neural network (nn); Training algorithms; Training function; Working properties; Boilers…”

Training method for a feed forward neural network based on meta-heuristics by Melo, H., Zhang, H., Vasant, P., Watada, J.

“…This paper proposes a Gaussian-Cauchy Particle Swarm Optimization (PSO) algorithm to provide the optimized parameters for a Feed Forward Neural Network. …”
Get full text
Get full text

Training method for a feed forward neural network based on meta-heuristics by Melo, H., Zhang, H., Vasant, P., Watada, J.

“…This paper proposes a Gaussian-Cauchy Particle Swarm Optimization (PSO) algorithm to provide the optimized parameters for a Feed Forward Neural Network. …”
Get full text
Get full text

Neural Networks based fault diagnosis of ac motors by K.S., Rama Rao, Muhammad, Aariff Yahya

“…The proposed ANN-based fault detector is developed using the Resilient Error Back Propagation (RPROP) training algorithm. The fast and reliable method for multilayer neural networks converges much faster than the conventional back propagation algorithm. …”
Get full text
Get full text

Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh by Seef Saadi , Fiyadh

“…The best result achieved for Pb2+ removal using ANFIS algorithm is with RE 7.078%. For As3+ removal using different adsorbents, two algorithms were applied for the modelling, the feed-forward back-propagation maximum RE achieved is 5.97% while, the NARX algorithm achieved better accuracy with maximum RE of 5.79%. …”
Get full text
Get full text
Get full text

Neural networks applied for fault diagnosis of AC motors by K.S., Rama Rao, Yahya , M.A.

“…The proposed ANN-based fault detector is developed using the Resilient Error Back Propagation (RPROP) training algorithm. The fast and reliable method for multilayer neural networks converges much faster than the conventional back propagation algorithm. …”
Get full text
Get full text
Get full text

Development of generalized feed forward network for predicting annual flood (depth) of a tropical river by Salarpour, Mohsen, Zulkifli Yusop, Jajarmizadeh, Milad, Fadhilah Yusof

“…The governing training algorithm was back propagation with momentum term and tangent hyperbolic types was used as transfer function for hidden and output layers. …”
Get full text
Get full text
Get full text

Using an Enhanced Feed-Forward BP Network for Predictive Model Building From Students’ Data by Ajiboye, Adeleke Raheem, Ruzaini, Abdullah Arshah, Qin, Hongwu

“…Feed-forward, Back Propagation (BP) Network is a network structure capable of modeling the class prediction as a nonlinear combination of the inputs. …”
Get full text
Get full text
Get full text

Design of artificial intelligence based speed estimator for DC drives / Pauziah Saleh by Saleh, Pauziah

“…For this purpose, the Lavenberg-Marquardt back propagation algorithm was used. A standard three layer feed-forward neural network with tan-sigmoid (tansig) activation functions in the hidden layer and purelin at the output layer is used for this test. …”
Get full text
Get full text

E-Handrawn Calculator by Mohamad, Syamimi

“…The purpose of this project is to demonstrate an application of back-propagation network (comparison of training their algorithms and transfer function) in order to developing e-Hand-Drawn Calculator. …”
Get full text
Get full text

Increasing the speed of convergence of an artificial neural network based ARMA coefficients determination technique by Aibinu, Abiodun Musa, Salami, Momoh Jimoh Emiyoka, Shafie, Amir Akramin, Najeeb, Athaur Rahman

“…In this paper, novel techniques in increasing the accuracy and speed of convergence of a Feed forward Back propagation Artificial Neural Network (FFBPNN) with polynomial activation function reported in literature is presented. …”
Get full text
Get full text

Image Improvement Technique Using Feed Forward Neural Network by Abu Saeeda, Omar Abdulmola

“…A nonlinear digital filter has been introduced as a promising solution for improving the image quality.The filter, which is named unsharp mask filter based neural network,significantly enhances the sharpness of image while highlights its details(edges and lines).In this thesis sharpening of image details has been obtained.Multi-layer Feed forward neural network with back propagation algorithm known as Multilayer Perceptron (MLP) is used to control the level of contrast enhancement.Grayscale blurred images were also used in this study.The results have been evaluated using mean square error as well as grayscale histogram distribution for sharpening of image details.Comparison among 3x3, 5x5 and 7x7 mask sizes has shown that least mean square error has been achieved by using the 3x3 mask size. …”
Get full text
Get full text

Optimization of Prediction Error in CO2 Laser Cutting process by Taguchi Artificial Neural Network Hybrid with Genetic algorithm by Nukman, Y., Hassan, M.A., Harizam, M.Z.

“…Simulation and prediction of CO2 laser cutting of Perspex glass has been done by feed forward back propagation Artificial Neural Network (ANN). …”
Get full text

Artificial neural network modeling studies to predict the yield of enzymatic synthesis of betulinic acid ester by Moghaddam, Mansour Ghaffari, Ahmad @ Amat, Faujan, Basri, Mahiran, Abdul Rahman, Mohd Basyaruddin

“…The paper makes a robust comparison of the performances of the above four algorithms employing standard statistical indices. The results showed that the quick propagation algorithm (QP) with 4-9-1 arrangement gave the best performances. …”
Get full text
Get full text
Get full text

Prediction the effect of heat treatment in tensile properties of TI-6AL-4V alloys using artificial neural network by Yan P., Detak, Syarif Junaidi, S Djalil, Rizauddin, Ramli

Get full text

Early detection of dengue disease using extreme learning machine by Suhaeri, Suhaeri, Mohd Nawi, Nazri, Fathurahman, Muhamad

“…Therefore, this research proposed an improved algorithm known as ELM which is an extension of Feed Forward Neural Network that utilize the Moore Penrose Pseudoinver matrix that gain the optimal weights of neural network architecture. …”
Get full text
Get full text

A new fuzzy back-propagation learning method based on derivation of min-max function tuned with genetic algorithms by Mashinchi, Mohammad Hadi

Get full text
Get full text
Get full text

CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

“…ANN based STLF models commonly use back-propagation algorithm, which generally exhibits a slow and improper convergence that affects the forecast accuracy. …”
Get full text
Get full text