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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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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…In cluster labelling process, a cluster labelling algorithm based on calculation of minimum-distance (MD) between cluster mean and class mean was developed to label the clusters. …”
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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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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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A Comparative Performance Analysis of ANN Algorithms for MPPT Energy Harvesting in Solar PV System by Roy R.B., Rokonuzzaman M., Amin N., Mishu M.K., Alahakoon S., Rahman S., Mithulananthan N., Rahman K.S., Shakeri M., Pasupuleti J.

Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector by Wang G., Mukhtar A., Moayedi H., Khalilpoor N., Tt Q.

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Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia by Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.

“…Post-optimization ANN model was trained using eleven different leaning algorithms. …”

Weather prediction system using ANN algorithm / Nur Afiqah Ahmad Sukri by Ahmad Sukri, Nur Afiqah

“…The ANN model consists of three layers with ReLU and softmax activations and is trained using the backpropagation algorithm. The performance of the model is evaluated using metrics such as mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), precision, recall, F1-score, and accuracy. …”
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Development of real-time embedded system with speech recognition for smart house by Yahya, Zuraimi, Sheikh Salleh, Sheikh Hussain, Syed Abu Bakar, Syed Abdul Rahman

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Logic Programming In Radial Basis Function Neural Networks by Hamadneh, Nawaf

“…The analysis revealed that performance of particle swarm optimization algorithm and Prey predator algorithm are better to use in training the networks. …”
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Water Quality Parameter Prediction Using Machine Learning Method by Muhammad Shaiful Bin Abdul Halim

Neural network algorithm-based fall detection modelling by Mohd Yusoff, Ainul Husna, Koh, Cheng Zhi, Ngadimon, Khairulnizam, Md Salleh, Salihatun

“…This article presents results of modelling for fall detection system by using nonlinear autoregression neural network NARnet algorithm. The algorithm is trained by network training function; LM, SCG and RP by collocation with threshold-based setting value. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

“…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. …”
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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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Development of vision autonomous guided vehicle behaviour using neural network by Husnul ‘Asyiyyah, Mohamad @ Awang

“…The line recognition algorithm involved the pre-processing images of the guideline captured by a camera and extracts the feature of the images by using first order statistics to calculate the values of mean, variance, skewness and kurtosis and train the image recognition by using neural networks. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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Comparative study of artificial neural network and mathematical model on marine diesel engine performance prediction by Noor C.W.M., Mamat R., Ahmed A.N.

Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…The statistical error estimation exhibits a mean absolute error of 11.5, and root mean squared error of 0.87. …”
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Development Of Automatic Liver Segmentation Method For Three- Dimensional Computed Tomography Dataset by Chew, Chin Boon

“…The segmentation results from the algorithm developed are competitive. However, improvements still can be made.…”
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Analyzing CT images for detecting lung cancer by applying the computational intelligence-based optimization techniques by Pethuraj, Mohamed Shakeel, Mohd Aboobaider, Burhanuddin, Salahuddin, Lizawati

“…The gathered image noise is removed by applying the mean filter, and the affected regions are segmented with the help of the Butterfly Optimization Algorithm-based K-Means Clustering (BOAKMC)algorithm. …”
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