Search Results - feed-forward optimization algorithm*

PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

“…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
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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. …”
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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. …”
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Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO) by Ahmed, Ehab Ali

“…This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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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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Development of generalized feed forward network for predicting annual flood (depth) of a tropical river by Salarpour, Mohsen, Zulkifli Yusop, Jajarmizadeh, Milad, Fadhilah Yusof

“…This study aimed at developing a Generalized Feed Forward (GFF) network model for predicting annual flood (depth) of Johor River in Peninsular Malaysia. …”
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Artificial neural network technique for modeling of groundwater level in Langat Basin, Malaysia by Mahmoud Khaki, Ismail Yusoff, Nur Islami, Nur Hayati Hussin

“…Based on the observation, the feed-forward neural network model optimized with the Levenberg-Marquardt algorithms showed the most beneficial results with the minimum MSE value of (0.048) and maximum R value of (0.839), obtained for simulation of groundwater levels. …”
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Comparison of feed forward neural network training algorithms for intelligent modeling of dielectric properties of oil palm fruitlets by Adedayo, Ojo O., Mohd Isa, Maryam, Che Soh, Azura, Abbas, Zulkifly

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PV boost converter conditioning using neural network by Abd Aziz, Aizat

“…This master report presents a voltage control system for DC-DC boost converter integrated with Photovoltaic (PV) array using optimized feed-forward neural network controller. …”
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Optimization of neural network through genetic algorithm searches for the prediction of international crude oil price based on energy products prices by Chiroma, Haruna, Ya’u Gital, Abdulsalam, Abubakar, Adamu, Usman, Mohammed Joda, Waziri, Usman

“…The propose GANN was able to improve the performance accuracy of the comparison algorithms. Our approach can easily be modified for the prediction of similar commodities.…”
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Training functional link neural network with ant lion optimizer by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

“…The Ant Lion Optimizer (ALO) is the metaheuristic optimization algorithm that mimics the hunting mechanism of antlions in nature. …”
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Introducing new statistical shape based and texture feature extraction methods in the plant species recognition system by Seyed Mohammad Hussein, Ahmad, Siti Anom, Hassan, Mohd Khair, Ishak, Asnor Juraiza

“…As the classification result, radial basis neural networks (RBFNN), feed forward neural networks (FFNN), neural networks using genetic algorithm (NNUGA) shows 100%, 93%, 97.3% of accuracy respectively . …”
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Improved pole-placement control with feedforward dead zone compensation for position tracking of electro-pneumatic actuator system by Sunar, Noorhazirah, Rahmat, Mohd Fua’ad, Mohd Fauzi, Ahmad ‘Athif, Ismail, Zool Hilmi, Osman, Siti Marhanis, Sulaiman, Siti Fatimah

“…In order to cater this issue, the EPA system transfer function and the dead-zone model is identified by MATLAB SI toolbox and the Particle Swarm Optimization (PSO) algorithm respectively. Then a parametric control is designed based on pole-placement approach and combine with feed-forward inverse dead-zone compensation. …”
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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

“…In this paper, the particle swan optimization algorithm (PSO) was used to obtain an optimal set of initial parameters for Reduce Kernel FLN (RK-FLN), thus, creating an optimal RKFLN classifier named PSO-RKELM. …”
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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.

“…The potential of genetic algorithm in optimization was utilized in the proposed hybrid model to minimize the error prediction for regions of cutting conditions away from the Taguchi based factor level points. …”
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Evolutionary Multiobjective optimization for automatic generation Of Neural game controller by Chin, Kim On, Yong, Yung Nan

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Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots by Hanafi Ahmad Hijazi, Patricia Anthony

“…A simulated Khepera robot is evolved by a Pareto-frontier Differential Evolution (POE) algorithm, and learned through a 3-layer feed-forward artificial neural network, attempting to simultaneously fulfill two conflicting objectives of maximizing robot phototaxis behavior while minimizing the neural network's hidden neurons by generating a Pareto optimal set of controllers. …”
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Self-evaluation of RTS Troop's performance by Chin Kim On, Chang Kee Tong, Jason Teo, Rayner Alfred, Wang Cheng, Tan Tse Guan

“…Experimental results demonstrate success with all aims: both EP and hybrid DE could be implemented into the Warcraft III platform, and both algorithms used able to generate optimal solutions.…”
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Evolution of RF-signal cognition for wheeled mobile robots using pareto multi-objective optimization by Chin, Kim On, Teo, Jason Tze Wi

“…The elitist Pareto-frontier Differential Evolution (PDE) algorithm is used to generate the Pareto optimal set of ANNs that could optimize two objectives in a single run; (1) maximize the mobile robot homing behavior whilst (2) minimize the hidden neurons involved in the feed-forward ANN. …”
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Optimization of robot plasma coating efficiency using genetic algorithm and neural networks / S.Prabhu and B.K.Vinayagam by S., Prabhu, B.K., Vinayagam

“…This work describes the Taguchi analysis coupled with Artificial Neural network and Genetic algorithm to optimize the robot deposition parameters used for plasma coating on titanium aluminum alloy material. …”
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