Search Results - (( based constructive based algorithm ) OR ( data validation learning algorithm ))

Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system by Maseer, Ziadoon Kamil

“…The optimized DBN algorithm, known as the HW-DBN algorithm, integrated through feature learning based on a Gaussian–Bernoulli Restricted Boltzmann Machine as well as classification task through a weight neuron network. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…Iris data set has been taken from UCO machine learning to assist in testing phase. …”
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Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat by Chia , Yu Huat

“…This is due to the data generated from the numerical model possess the pattern for the ML algorithm ease of prediction. …”
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Sentiment Analysis of Sexual Harassment in Malaysia on Twitter Using Machine Learning Algorithms by Nurellezia, Suleiman

“…The transformed data is then modelled using machine learning algorithms such as Naïve Bayes classifier and Support Vector Machine to predict the overall sentiment of tweets, in which the finding depicted an overall positive sentiment surrounding the issue. …”
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A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction by Hammid, Ali Thaeer, M. H., Sulaiman, Awad, Omar I.

“…The objective of this study, first, a firefly algorithm (FA) based on the k-fold cross-validation of BPNN has been suggested to predict data for keeping rapid learning and prevents the exponential increase in operating parts. …”
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Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

“…This study developed an algorithm for statistical classification that enable ones to classify a future data to one of predetermined groups based on the measured data which facing two major threats; (i) multicollinearity among the measured variables and (ii) imbalanced groups. …”
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Machine Learning based Predictive Modelling of Cybersecurity Threats Utilising Behavioural Data by Ting, Tin Tin, Khiew, Jie Xin, Ali Aitizaz, Lee, Kuok Tiung, Teoh, Chong Keat, Hasan Sarwar

“…The algorithms are used to construct, test, and validate three categories of cybercrime threat (Malware, Social Engineering, and Password Attack) predictive models. …”
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Artificial Neural Network Algorithms to Predict the Compressive Strength of Fly Ash-Based Geopolymers by Siaw Hui, Teo

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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization by Nanyonga Aziida, Sorayya Malek, Firdaus Aziz, Khairul Shafiq Ibrahim, Sazzli Kasim

“…Feature selection methods such as Boruta, Random Forest (RF), Elastic Net (EN), Recursive Feature Elimination (RFE), learning vector quantization (LVQ), Genetic Algorithm (GA), Cluster Dendrogram (CD), Support Vector Machine (SVM) and Logistic Regression (LR) were combined with RF, SVM, LR, and EN classifiers for 30-day mortality prediction. …”
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Time series modeling of water level at Sulaiman Station, Klang River, Malaysia by Galavi, Hadi

“…The estimation of parameters of the model is accomplished using the hybrid learning algorithm consisting of standard neural network backpropagation algorithm and least squares method. …”
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Development of machine learning sentiment analyzer and quality classifier (MLSAQC) and its application in analysing hospital patient satisfaction from Facebook reviews in Malaysia by A Rahim, Afiq Izzudin

“…By manually annotating many batches of randomly chosen reviews, we constructed a machine learning quality classifier (MLQC) based on the SERVQUAL model and a machine learning sentiment analyzer (MLSA). …”
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Artificial intelligence-driven anticancer peptide discovery by Wu, Junrui, Ji, Shuaiqi, Sahibzada, Kashif Iqbal, Lou, Mengxue, An, Feiyu, Li, Wenqian, Guo, Jiawei, Zhang, Taowei, Zhang, Xinyi, Chou, Yilin, Zhang, Henan, Jin, Hao, Ma, Teng, Liu, Weichi, Alikulov, Begali, Golovneva, Natalia Alekseevna, Foo, Hooi Ling, Kuralay, Issayeva, Sun, Zhihong, Wei, Dongqing, Wu, Rina

“…Therefore, we presented a comprehensive ACP screening framework based on AI models. The presented framework includes data collection and organization, feature extraction, model construction, model interpretability analysis, and experimental validation. …”
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EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique by Liew, Siaw Hong

“…The IncFRNN algorithm is able to control the size of training pool using predefined window size threshold. …”
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A comparative study on aviation arrival delay prediction using machine learning methods by Chew, Pui Ting

“…This research aims to identify the most important features for flight delay prediction, build supervised machine learning algorithms (i.e., logistic regression (LR), random forest (RF) and artificial neural network (ANN)) for predicting flight arrival delay and compare the performances of the methods. …”
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Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis by Abujayyab, Sohaib K. M.

“…Hybrid neural network was utilized as an evaluation method to select the optimal selection method and optimal training algorithm. The employment of automated toolbox is a straightforward process constructed from eight sub-tools to prepare, train, and processes the data. …”
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A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation by Mohd Ali, Nursabillilah, Besar, Rosli, Ab Aziz, Nor Azlina

“…Annually, almost half a million women do not survive the disease and die from breast cancer. Machine learning is a subfield of artificial intelligence (AI) and computer science that uses data and algorithms to mimic how humans learn, and gradually improving its accuracy. …”
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Prediction of Machine Failure by Using Machine Learning Algorithm by Fakhrurazi, Nur Amalina

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Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan by Hamdan, Ezaryf

“…Text preprocessing ensures consistent data representation and facilitates validation. The Machine Learning algorithm, comprising Random Forest, Linear Regression, XGBoost, SVM, and Stacking Ensemble, is embedded in the system for job position predictions based on the analysed data. …”
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Investigation of machine learning models in predicting compressive strength for ultra-high-performance geopolymer concrete: A comparative study by Abdellatief M., Hassan Y.M., Elnabwy M.T., Wong L.S., Chin R.J., Mo K.H.

“…Overall, the dataset of 128 CS results was used to develop the machine learning (ML) models. The findings validate the effectiveness of the RF, SVR, and XGB models in accurately predicting the strength of the UHPGC, as constructed by their excellent predictive accuracy (R2 > 0.84). …”

Suicide and self-harm prediction based on social media data using machine learning algorithms by Abdulrazak Yahya, Saleh, Fadzlyn Nasrini, Mostapa

“…In combined with robust machine learning algorithms, social networking data may provide a potential path ahead. …”
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