Search Results - (( using factorization learning algorithm ) OR ( parameter classifications using algorithm ))

Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

“…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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Three-term backpropagation algorithm for classification problem by Saman, Fadhlina Izzah

“…This algorithm utilizes two term parameters which are Learning Rate, α and Momentum Factor,β. …”
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Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram by Faris Francis Singaram, Fareena

“…Therefore, this study aimed to used OBIA method with selected machine learning algorithm to estimate the mangrove age by using Sentinel 2A image. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

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Cluster identification and separation in the growing self-organizing map: Application in protein sequence classification by Ahmad, N.

“…We used simple k-means algorithm as a method to identify clusters in the GSOM. …”
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Backpropagation algorithm for classification problem: academic performance prediction model for UiTM Melaka Mengubah Destini Anak Bangsa (MDAB) program. / Fadhlina Izzah Saman, Nur... by Saman, Fadhlina Izzah, Zainuddin, Nurulhuda, Md Shahid, Khairiyah

“…Multilayer perceptrons (MLPs) is one of the topology used for processing ANN, while backpropagation algorithm is one of the most popular methods in training MLPs. …”
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On equivalence of FIS and ELM for interpretable rule-based knowledge representation by Wong S.Y., Yap K.S., Yap H.J., Tan S.C., Chang S.W.

Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

“…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

“…Most existing approaches modify the learning model in order to add a random factor to the model which can help to overcome the tendency to sink into local minima. …”
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Predicting noise-induced hearing loss (NIHL) in TNB workers using GDAM algorithm by Rehman Gillani, Syed Muhammad Zubair

“…Despite providing useful information on hearing loss, these studies have neglected some important factors. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

“…The framework addresses a gap in predictive analytics by combining computational techniques, consumer behavior theories, and demographic data to better understand and forecast purchasing trends. The framework uses machine learning methods, including classification, clustering, feature selection, and parameter tuning, to improve accuracy and reliability. …”
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Modeling of road geometry and traffic accidents by hierarchical object-based and deep learning methods using laser scanning data by Sameen, Maher Ibrahim

“…There was a need for efficient segmentation algorithm, optimization strategy, feature extraction and classification, and robust statistical and computational intelligence models to accomplish the set aims. …”
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Application of artificial neural network in discriminating the agarwood oil quality using significant chemical compounds / Mohd Hezri Fazalul Rahiman … [et al.] by Rahiman, Mohd Hezri Fazalul, Ismail, Nurlaila, Taib, Mohd Nasir, Mohd Ali, Nor Azah, Tajuddin, Saiful Nizam

“…Back-propagation training algorithm and sigmoid transfer function were used to optimise the parameters in the training network. …”
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A Bayesian Approach to Explore Risk Factors for Respiratory Dysfunction in Intensive Care Unit Patient by Shah N.B.N.H., Razak N.N.B.A., Samah A.B.A., Razak N.A.B.A., Ramasamy A., Suhaimi F.M., Chase J.G.

Image Splicing Detection With Constrained Convolutional Neural Network by Lee, Yang Yang

“…It is shown that CNN with constrained convolution algorithm can be used as a general image splicing detection task.…”
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Enhancement Of Static Code Analysis Malware Detection Framework For Android Category-Based Application by Aminordin, Azmi

“…In increasing the reliability, the results obtained are then validated by using statistical analysis procedure which each machine learning classification algorithm are iterate 50 times. …”
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Neurons to heartbeats: spiking neural networks for electrocardiogram pattern recognition by Wong, Yan Chiew, Mohamad Noor, Nor Amalia Dayana, Mohd Noh, Zarina, Sarban Singh, Ranjit Singh

“…Establishing functioning spiking neural networks (SNN) involves figuring out the neuron’s state through its activity level, challenging due to its resemblance to the human brain’s data processing, yet appealing due to factors like improved unsupervised learning methods, with ten parameters chosen for the learning algorithm of SNN. …”
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Digital economy tax compliance model in Malaysia using machine learning approach by Raja Azhan Syah Raja Wahab, Azuraliza Abu Bakar

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Artificial intelligence to predict pre-clinical dental student academic performance based on pre-university results: a preliminary study by Lestari, Widya, Abdullah, Adilah Syahirah, Ahmad Amin, Afifah Munirah, faridah, Nur, Sukotjo, Cortino, Ismail, Azlini, mohamad ibrahim, mohamad shafiq, Insani, Nashuha, Utomo, Chandra Prasetyo

“…However, it was limited by several factors. Each algorithm has unique performance qualities, and trade-offs between different performance metrics may be necessary. …”
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