Search Results - (( model evaluation from algorithm ) OR ( identification _ learning algorithm ))

A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

“…The proposed algorithm is able to improve the weaknesses in PQF model in updating and learning the important attributes for software quality assessment. …”
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System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

“…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman by Abdul Rahman, Muhammad Nur Azri Irfan

“…Finally, the rigor of evaluation phase is carried out to evaluate the model utilizing precision, recall, F1 score, and the overall accuracy metrics which ascertained robustness and reliability for the model.…”
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Opposition- based simulated kalman filters and their application in system identification by Kamil Zakwan, Mohd Azmi

“…However, the exploration capability of SKF could be further improved. From literature, Opposition-based Learning (OBL) has been employed to increase the diversity (exploration) of search algorithm by allowing current population to be compared with an opposite population. …”
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Landslide susceptibility mapping: machine and ensemble learning based on remote sensing big data by Kalantar, Bahareh, Ueda, Naonori, Saeidi, Vahideh, Ahmadi, Kourosh, Abdul Halin, Alfian, Shabani, Farzin

“…In this research, the potential of supervised machine learning and ensemble learning is investigated. Firstly, the Flexible Discriminant Analysis (FDA) supervised learning algorithm is trained for LSM and compared against other algorithms that have been widely used for the same purpose, namely Generalized Logistic Models (GLM), Boosted Regression Trees (BRT or GBM), and Random Forest (RF). …”
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An artificial immune system model as talent performance predictor / Siti ‘Aisyah Sa’dan, Hamidah Jantan and Mohd Hanapi Abdul Latif by Sa’dan, Siti ‘Aisyah, Jantan, Hamidah, Abdul Latif, Mohd Hanapi

“…To achieve this objective, the research was divided into three phases, which consist of talent data identification and data preparation phase, algorithm development for prototype phase and testing and evaluation phase to identify the most suitable prediction model for talent prediction. …”
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Keylogger detection analysis using machine learning algorithm / Muhammad Faiz Hazim Abdul Rahman by Abdul Rahman, Muhammad Faiz Hazim

“…Besides, to test the accuracy of detection models on keylogger dataset comparing two machine learning algorithms. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

“…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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Dyslexia handwriting detection using Convolutional Neural Network (CNN) algorithm / Sofea Najihah Mohd Zaki by Mohd Zaki, Sofea Najihah

“…Further enhancements might involve including machine learning algorithms to improve the prototype's accuracy by learning from a larger dataset, which would eventually improve the prototype's ability to offer deep understanding into handwriting patterns related to dyslexia.…”
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Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga by Mwenge , Mulenga

“…While the complex relations that exist between the microbiome and host phenotypes make machine learning algorithms suitable for analysing the microbiome data, deep learning methods are becoming more popular due to their outstanding performance in related fields. …”
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A Hybrid Artificial Intelligence Model for Detecting Keratoconus by Alyasseri Z.A.A., Al-Timemy A.H., Abasi A.K., Lavric A., Mohammed H.J., Takahashi H., Milhomens Filho J.A., Campos M., Hazarbassanov R.M., Yousefi S.

“…This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. …”

A comparative study of vibrational response based impact force localization and quantification using different types of neural networks / Wang Yanru by Wang, Yanru

“…ANNs is one of the methods, which has drawn attention by researchers in recent years due to its unique advantages compared with other indirect identification techniques. It can analyze complex relationship of nonlinear input-output by learning from datasets without any mathematical model. …”
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Handgrip strength evaluation using neuro fuzzy approach by Seng, W.C., Chitsaz, M.

“…The neurofuzzy analysis provides system identification and interpretability of fuzzy models and learning capability of neural networks. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh by Kuldeep Kaur , Ragbir Singh

“…To evaluate the efficacy of the models, publicly available financial and credit card data sets are evaluated. …”
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A machine learning approach of predicting high potential archers by means of physical fitness indicators by Musa, Rabiu Muazu, Anwar, P. P. Abdul Majeed, Zahari, Taha

“…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. …”
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Malaysian license plate recognition system using Convolutional Neural Network (CNN) on web application / Nur Farahana Mahmud by Mahmud, Nur Farahana

“…Nowadays, there are numerous license plate recognition systems that have been developed and analysed effectively by previous researchers using different machine learning algorithms. However, according to a recent study, ANN algorithms require a huge amount of training data while BPFFNN algorithms only have an average success rate of 70% in recognizing all the characters. …”
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Feature extraction and supervised learning for volatile organic compounds gas recognition by Mohd Tombel, Nor Syahira, Mohd Zaki, Hasan Firdaus, Mohd Fadglullah, Hanna Farihin

“…The performance of each model was evaluated and compared using k-Fold cross-validation (k=10) and metrics derived from the confusion matrix. …”
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A machine learning approach of predicting high potential archers by means of physical fitness indicators by Muazu Musa, Rabiu, Abdul Majeed, Anwar P.P., Taha, Zahari, Chang, Siow Wee, Ab. Nasir, Ahmad Fakhri, Abdullah, Mohamad Razali

“…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. …”
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3D face recognition using triplet point cloud network for the identification of a person with a face mask / Muhammad Azhad Zuraimi by Zuraimi, Muhammad Azhad

“…To address these problems, this study proposed a pipeline of works such as collected 3D masked face dataset and combined with the existing 3D dataset for train and evaluating networks, designed a triplet 3D face masked point clouds-aware deep network using triplet loss function, and evaluated the performance of 3D face recognition using Deep Learning model for identification of a person with a face mask. …”
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