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Performance of various training algorithms on scene illumination classification by Hesamian, Mohammad Hesam, Mashohor, Syamsiah, Saripan, M. Iqbal, Wan Adnan, Wan Azizun, Hesamian, B., Hooshyari, M. M.

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Extending the decomposition algorithm for support vector machines training by Zaki, N,M., Deris, S., Chin, K.K.

“…The decomposition algorithm developed by Osuna et al. (1997a) reduces the training cost to an acceptable level. …”
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Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Ramarao, Taj, Mohammed Baloch

“…The developed algorithm is effectively trained, verified and validated with a set of training, dedicated testing and validation data respectively.…”
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Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Rama Rao

“…The developed algorithm is effectively trained, verified and validated with a set of training, dedicated testing and validation data respectively.…”
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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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Autoreclosure in extra high voltage lines using taguchi's method and optimized neural networks by K.S.R, Rao, F. D., Zahlay

“…The developed algorithm is effectively trained, verified and validated with a set of training, dedicated testing and validation data respectively. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…Methods for improving supervised and unsupervised classification of remotely sensed data were developed in this study. …”
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Sentiment classification for malay newspaper using clonal selection algorithm / Nur Fitri Nabila Mohamad Nasir by Mohamad Nasir, Nur Fitri Nabila

“…The experimental results show that our method can achieve better performance in clonal selection algorithm sentiment classification and the data collected cannot be used at once in this model because training data is very time-consuming if using all the data. …”
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A new approach for forecasting OPEC petroleum consumption based on neural network train by using flower pollination algorithm by Haruna, Chiroma, Khan, Abdullah, Abubakar, Adamu, Saudi, Younes, Hamza, Mukhtar Fatihu, Shuiba, Liyana, Gital, Abdulsalam, Herawan, Tutut

“…The proposed approach is compared with established meta-heuristic algorithms. The results show that the new proposed method out performs existing algorithms by advancing OPEC petroleum consumption forecast accuracy and convergence speed. …”
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Adapting and enhancing mussels wandering optimization algorithm for supervised training of neural networks by Abusnaina, Ahmed A. A.

“…The major objective of this thesis is to achieve better performance in terms of convergence training time and classification accuracy for pattern classification by proposing new supervised training methods for Artificial Neural Networks (ANN) based on the MWO algorithm. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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REDUCING LATENCY IN A VIRTUAL REALITY-BASED TRAINING APPLICATION by P ISKANDAR, YULITA HANUM

“…Findings indicated that heuristic-based algorithm is an accurate prediction method to compensate latency in virtual training. …”
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Water Quality Parameter Prediction Using Machine Learning Method by Muhammad Shaiful Bin Abdul Halim

Improved prediction accuracy of biomass heating value using proximate analysis with various ANN training algorithms by Veza, I., Irianto, Panchal, H., Paristiawan, P.A., Idris, M., Fattah, I.M.R., Putra, N.R., Silambarasan, R.

“…The specific objective of this study is to predict the HHV of 350 samples of biomass from the proximate analysis by developing an ANN model which was trained with 11 different algorithms. …”
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Accelerated mine blast algorithm for ANFIS training for solving classification problems by Mohd Salleh, Mohd Najib, Hussain, Kashif

“…ANFIS accuracy depends on the parameters it is trained with. Keeping in view the drawbacks of gradients based learning of ANFIS using gradient descent and least square methods in two-pass learning algorithm, many have trained ANFIS using metaheuristic algorithms. …”
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Enhanced conjugate gradient methods for training MLP-networks by Izzeldin, H., Asirvadam , Vijanth Sagayan, Saad , Nordin

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

“…This research focuses on the use of binaryencoded genetic algorithm (GA) to implement efficient search strategies for the optimal architecture and training parameters of a multilayer feed-forward ANN. …”
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Performance comparison of feedforward neural network training algorithms in modeling for synthesis of polycaprolactone via biopolymerization by Wong, Yong Jie, Arumugasamy, Senthil Kumar, Jewaratnam, Jegalakshimi

“…A multilayer feedforward neural network (FFNN) model with 11 different training algorithms is developed for the multivariable nonlinear biopolymerization of polycaprolactone (PCL). …”
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Advances of metaheuristic algorithms in training neural networks for industrial applications by Chong H.Y., Yap H.J., Tan S.C., Yap K.S., Wong S.Y.

Development of a detection and classification method for induction motor faults using Motor Current Signature Analysis and Feedforward Neural Network / Felicity Bulan Leo Uchat by Leo Uchat, Felicity Bulan

“…As it is important to choose proper training algorithm for training the FNN, therefore three different FNN training algorithms are compared in terms of their accuracy, number of iterations and training time.…”
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