Search Results - (( using optimization based algorithm ) OR ( parameter training learning algorithm ))

A review of training methods of ANFIS for applications in business and economic by Mohd Salleh, Mohd Najib, Hussain, Kashif

“…Therefore many researchers have trained ANFIS parameters using metaheuristic algorithms however very few have considered optimizing the ANFIS rule-base. …”
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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.

A review of training methods of ANFIS for applications in business and economics by Mohd Salleh, Mohd Najib, Hussain, Kashif

“…Therefore many researchers have trained ANFIS parameters using metaheuristic algorithms however very few have considered optimizing the ANFIS rule-base. …”
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Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates by Yeong, Lin Koay, Hong, Seng Sim, Yong, Kheng Goh, Sing, Yee Chua, Wah, June Leong

“…The process of training neural networks heavily involves solving optimization problems. Most optimization algorithms use a !…”
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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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Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…Optimization algorithms are widely used for the identification of intrusion. …”
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Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

“…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

“…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO) by Ahmed, Ehab Ali

“…Due to that, many algorithms employ different training algorithms to guide the network for providing an accurate result with less training and testing error. …”
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A speech recognition system based on structure equivalent fuzzy neural network trained by firefly algorithm by Tahereh Hassanzadeh, Karim Faez, Golnaz Seyfi

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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

“…The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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Deep Learning Based Face Attributes Recognition by Saidi, Mohamad Hazim

“…Combined-algorithm based optimizers plays an important role in optimizing the training algorithm. …”
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Artificial neural networks based optimization techniques: A review by Abdolrasol M.G.M., Suhail Hussain S.M., Ustun T.S., Sarker M.R., Hannan M.A., Mohamed R., Ali J.A., Mekhilef S., Milad A.

“…In the last few years, intensive research has been done to enhance artificial intelligence (AI) using optimization techniques. In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), and backtracking search algorithm (BSA) and some modern developed techniques, e.g., the lightning search algorithm (LSA) and whale optimization algorithm (WOA), and many more. …”

Rao-SVM machine learning algorithm for intrusion detection system by Abd, Shamis N., Alsajri, Mohammad, Ibraheem, Hind Raad

“…Most of the intrusion detection systems are developed based on optimization algorithms as a result of the increase in audit data features; optimization algorithms are also considered for IDS due to the decline in the performance of the human-based methods in terms of their training time and classification accuracy. …”
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New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification by Balakrishnan, Malarvili, Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain

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Firefly algorithm-based neural network for GCPV system output prediction: article / Nor Syakila Mohd Zainol Abidin by Mohd Zainol Abidin, Nor Syakila

“…In the proposed MLFNN, Firefly Algorithm (FA) was employed as the optimizer and search tools of the MLFNN training parameters. …”
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Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…These algorithms have widely been used to optimize the learning mechanism of classifiers, particularly on Artificial Neural Network (ANN) Classifier. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

“…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”