Search Results - feed-forward ((propagation algorithm) OR (((prediction algorithm) OR (selection algorithm))))

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. …”
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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. …”
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Wind power prediction using Artificial Neural Network: article by Edik, Septony

“…In order to get an accurate wind power prediction, several network structures, training algorithms and transfer functions have been developed and tested with different sets of data. …”
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Wind power prediction using Artificial Neural Network by Edik, Septony

“…In order to get an accurate wind power prediction, several network structures, training algorithms and transfer functions have been developed and tested with different sets of data. …”
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A Hybrid Neural Network-Based Improved PSO Algorithm for Gas Turbine Emissions Prediction by Yousif S.T., Ismail F.B., Al-Bazi A.

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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). …”
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Power system security assessment using artificial neural network: article / Mohd Fathi Zakaria by Zakaria, Mohd Fathi

“…This paper presented an application of Artificial Neural Network (ANN) in steady state stability classifications. A multi layer feed forward ANN with Back Propagation Network algorithm is proposed in determining the steady state stability classifications. …”
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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%. …”
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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. …”
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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

“…In this study, artificial neural network (ANN) analysis of Candida antarctica lipase (Novozym 435) -catalyzed esterification of betulinic acid with phthalic anhydride was carried out. A multilayer feed-forward neural network trained with an error back-propagation algorithm was incorporated for developing a predictive model. …”
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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. …”
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Applications of IoT and Artificial Intelligence in Water Quality Monitoring and Prediction: A Review by Mustafa H.M., Mustapha A., Hayder G., Salisu A.

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

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An intelligent optical fibre pH sensor based on sol-gel advanced material and artificial neural network / Mohd Nasir Taib, Faiz Bukhari Mohd Suah and Musa Ahmad by Taib, Mohd Nasir, Mohd Suah, Faiz Bukhari, Ahmad, Musa

“…The pH sensor is developed based on the use of bromophenol blue indicator immobilized in a sol-gel thin film as a sensing material. A three layer feed-forward network was used and the network training was performed using the back-propagation algorithm. …”
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Nonlinear response prediction of spar platform using artificial neural network / Md. Alhaz Uddin by Md. Alhaz , Uddin

“…Environmental forces and structural parameters are used as inputs and FEM-based time history of spar platform responses are used as targets. Feed-forward neural networks with back-propagation algorithm are used to train the network. …”
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Prediction of material removal rate and tool wear rate in electrical discharge machining using feedforward neural network / Zaid Mohd Hanapiah by Mohd Hanapiah, Zaid

“…The NN architecture that had been used in this project is multilayer feed forward with back propagation learning algorithm. …”
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Application of artificial neural network in share price forecasting / Zakiah Mustafa by Mustafa, Zakiah

“…Abstract This thesis present the applications of artificial neural network (ANN) to predict the share price of Telekom Malaysia Bhd. The back-propagation algorithm used to train the ANN. …”
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Development of an artificial neural network algorithm for predicting the surface roughness in end milling of inconel 718 alloy by Hossain, Mohammad Ishtiyaq, Amin, A. K. M. Nurul, Patwari, Anayet Ullah

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Optimisation of laser cutting parameters of oil palm wood / Harizam Mohd Zin by Harizam, Mohd Zin

“…In some cases, the prediction errors of Taguchi ANN model was found larger than 10% even using a Levenberg Marquardt training algorithm. …”
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Intelligent technique for grading tropical fruit using magnetic resonance imaging by A. Balogun, Wasiu, Salami, Momoh Jimoh Emiyoka, J. McCarthy, Michael, Mohd Mustafah, Yasir, Aibinu, Abiodun Musa

“…The features extracted from Magnetic Resonance Imaging (MRI), using any of the two proposed methods, were applied as an input to train artificial neural network (ANN) in order to predict the orange fruit status. Different structures of multi-layer perceptron neural networks with feed-forward and back-propagation learning algorithms were developed using MATLAB. …”
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