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Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

“…Thus, it can be concluded that the developed algorithm is capable to improve the classification efficiency by improving the generality of the classifier in classifying test data with unpredictable variations under various working conditions.…”
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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

“…In this study, an Artificial Neural Network (ANN) was designed, optimized and deployed to model the dielectric phenomena of microwave interacting with oil palm fruitlets within the frequency range of 2-4GHz. The ANN training data were obtained from Open-ended Coaxial Probe (OCP) microwave measurements and the quasi-static admittance model, the ANN was trained with four different training algorithms: Levenberg Marquardt (LM) algorithm, Gradient Descent with Momentum (GDM) algorithm, Resilient Backpropagation (RP) algorithm and Gradient Descent with Adaptive learning rate (GDA) algorithm. …”
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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.

ARTIFICIAL NEURAL NETWORK FOR WATER LEVEL PREDICTION IN A RIVER UNDER TIDAL INFLUENCE by Maliana, Sa'ad

“…This model generated the highest R Testing of 0.9425 when trained with the scaled conjugate gradient algorithm (trainscg). …”
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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 Artificial Neural Network (ANN) for lightning prediction under Malaysia environment / Jeremy AK Stewart Bedimbap by Stewart Bedimbap, Jeremy

“…The purpose of this project is to present the development of Artificial Neural Network (ANN) for lightning prediction under Malaysia environment. …”
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Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari by Sha’ari, Nor Silawati

“…In this paper, by using the database available in the internet and using Neural Network (NN) as training algorithm, plant recognition based on leaves image would be developed. …”
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Nonlinear modeling and control of a spark ignition engine idle speed / Hazem Mohamed by Hazem, Mohamed

“…The fuzzy controller is formulated as a radial basis function network trained by the orthogqnalleast squares algorithm to estimate the controller parameters. …”
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Development of Artificial Neural Network for lightning prediction under Malaysia environment: article / Jeremy AK Stewart Bedimbap by Stewart Bedimbap, Jeremy

“…This paper presents the development of Artificial Neural Network (ANN) for lightning prediction under Malaysia environment. …”
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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.

Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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Hourly water level prediction of sungai bedup catchement using pre-developed ANNs model from Siniawan catchment by Hong,, Calvin Chiao Chun

“…The back propagation algorithm was adopted for this study. The models used in this study is the network trained with scaled conjugate gradient algorithm (trainscg) with two hours of antecedent data, learning rate and the number of neurons in the hidden layer of 0.8 and 40 respectively. …”
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Artificial neural network and inverse solution method for assisted history matching of a reservoir model by Negash, B.M., Vel, A., Elraies, K.A.

“…This allows to directly simulate the trained neural network and avoid the use of objective function and optimization algorithm. …”
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The development of extra axial brain tumor detection prototype using back propagation based neural network / Suriyanti Panagen by Panagen, Suriyanti

“…Knowledge appearance is compulsory for neural network in which it comes under the training phase before it recognize or detecting any pattern.A study about the artificial neural network has been done and back propagation training algorithm is suitable for this system development. …”
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Face recognition and identification system (FaceRec) / Khew Jye Huei by Khew , Jye Huei

“…It describes the implementation and functions of a working system that performs the recognition and identification of human faces using the implement algorithms. Java is use as programming language to develop the Face Rec system and Microsoft Access as the database to store and access the fa e images for the training set. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

“…Transfer Learning is one of the common methods. Various algorithms under Transfer Learning had been developed for different applications. …”
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Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition by Yew W.H., Fat Chau C., Mahmood Zuhdi A.W., Syakirah Wan Abdullah W., Yew W.K., Amin N.

“…Despite the limitations of training the DRL, it shows a promising method for addressing MPPT issues under PSC. � 2023 IEEE.…”

Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman by Abdul Rahman, Muhammad Nur Azri Irfan

“…The methodology followed a structured three-phase process: The first stage was the collection of a dataset of 5,099 images of 30 different musical instruments of Kaggle, providing variable lighting, angles, or backgrounds, along with preprocessing to standardize the inputs. In the development phase, Convolutional Neural Network model was designed and trained using sophisticated techniques of data augmentation, dropping out and hyperparameter tuning under the supervised learning methodology to increase the performance of the system. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush