Search Results - ((((regression algorithm) OR (selection algorithm))) OR (detection algorithm))

Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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The effect of replacement strategies of genetic algorithm in regression test case prioritization of selected test cases by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

“…This study presents an optimized regression test case prioritization of selected test cases for object-oriented software using Genetic algorithm with different replacement strategies. …”
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Rao-SVM machine learning algorithm for intrusion detection system by Abd, Shamis N., Alsajri, Mohammad, Ibraheem, Hind Raad

“…This article presents the development of an improved intrusion detection method for binary classification. In the proposed IDS, Rao Optimization Algorithm, Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) were combined with NTLBO algorithm with supervised ML techniques (for feature subset selection (FSS). …”
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Software regression test case prioritization for object-oriented programs using genetic algorithm with reduced-fitness severity by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

“…This paper propose an optimized regression test case selection and prioritization for object-oriented software based on dependence graph model analysis of the source code and optimized the selected test case using Genetic Algorithm. …”
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A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

“…This paper presents an evolutionary regression test case prioritization for object-oriented software based on dependence graph model analysis of the affected program using Genetic Algorithm. …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

“…A deterministic mutation-based algorithm is introduced to overcome this problem. Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
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Regression test case selection & prioritization using dependence graph and genetic algorithm by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

“…Unfortunately, it is costly and time consuming to allow for the re-execution of all test cases during regression testing. The challenge in regression testing is the selection of best test cases from the existing test suite.This paper presents an evolutionary regression test case prioritization for object-oriented software based on extended system dependence graph model of the affected program using genetic algorithm. …”
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Neural network algorithm-based fall detection modelling by Mohd Yusoff, Ainul Husna, Koh, Cheng Zhi, Ngadimon, Khairulnizam, Md Salleh, Salihatun

“…Related algorithm for the fall detection has been discussed in depth by researcher from the previous research. …”
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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

“…In a semiconductor industry, wafer defect detection has becoming ubiquitous. Various machine learning algorithms had been adopted to be the “brain” behind the machine for reliable, fast defect detection. …”
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Polymorphic malware detection based on dynamic analysis and supervised machine learning / Nur Syuhada Selamat by Selamat, Nur Syuhada

“…The benefit of this work indicated that the implementation of a feature selection technique plays an important role in machine learning algorithms to increase the performance of detection.…”
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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network by Mohammad Azmi Ridwan, Dr.

“…This thesis proposes a hybrid ML-based intrusion detection system (ML-IDS) and ML-based intelligent routing algorithm (ML-RA) for MPLS network. …”

Multi-sensor fusion based on multiple classifier systems for human activity identification by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Alo, Uzoma Rita, Al-garadi, Mohammed Ali

“…To this end, computationally efficient classification algorithms such as decision tree, logistic regression and k-Nearest Neighbors were used to implement diverse, flexible and dynamic human activity detection systems. …”
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Classification of herbs plant diseases via hierachical dynamic artificial neural network after image removal using kernel regression framework by Abdullah, Lili Nurliyana, Khalid, Fatimah, Borhan, N.M.

“…This paper is to propose an unsupervised diseases pattern recognition and classification algorithm that is based on a modified Hierarchical Dynamic Artificial Neural Network which provides an adjustable sensitivity-specificity herbs diseases detection and classification from the analysis of noise-free colored herbs images. …”
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Breast Cancer Prediction Model Using Machine Learning by Muhammad Amin, Bakri, Inna, Ekawati

“…Modelling with machine learning is done by selecting three candidate algorithms, namely Random Forest, Support Vector Machine, and Logistic Regression. …”
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Analysis Of Feature Reduction Algorithms To Estimate Human Stress Conditions by Arasu, Darshan Babu

“…Therefore, this study aimed to present analyse of the performance of feature classify when combining with feature selection algorithm to estimate human stress based on the facial feature of thermal imaging. …”
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Detecting Malware with Classification Machine Learning Techniques by Mohd Yusof, Mohd Azahari, Abdullah, Zubaile, Hamid Ali, Firkhan Ali, Mohamad Sukri, Khairul Amin, Shaker Hussain, Hanizan

“…The study assesses the effectiveness of several algorithms, including Naïve Bayes, Support Vector Machine (SVM), KNearest Neighbor (KNN), Decision Tree, Random Forest, and Logistic Regression, through an examination of a publicly accessible dataset featuring both benign files and malware. …”
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Detecting Malware with Classification Machine Learning Techniques by Mohd Yusof, Mohd Azahari, Abdullah, Zubaile, Hamid Ali, Firkhan Ali, Mohamad Sukri, Khairul Amin, Shaker Hussain, Hanizan

“…The study assesses the effectiveness of several algorithms, including Naïve Bayes, Support Vector Machine (SVM), KNearest Neighbor (KNN), Decision Tree, Random Forest, and Logistic Regression, through an examination of a publicly accessible dataset featuring both benign files and malware. …”
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Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri by Basri, Katrul Nadia

“…The best performance obtained using Savitzky-Golay smoothing and LDA algorithms after the wavelength selection with the accuracy reported of 0.90. …”
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Outlier detection in circular regression model using minimum spanning tree method by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari, Roslinazairimah, Zakaria

“…Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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Air quality measurement using remote sensing and digital images processing techniques / Lim, H. S. … [et al.] by Lim, H. S., Jafri, Mat, Abdullah, M. Z., Ahmad, A.N.

“…The relationship between the reflectance and the corresponding air quality data was determined using regression analysis. A new algorithm was developed for detecting air pollution from the digital camera images chosen based on the highest correlation coefficient, R and lowest root mean square error, RMS for PM10. …”
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