Search Results - ((((regression algorithms) OR (generation algorithm))) OR (detection algorithm))

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  1. 1
    The Performance of Chlorophyll-a Distribution Estimation by Using Ratio Algorithm on Landsat-8 in Sungai Merbok Estuary / Jesse Vince Rabing ... [et al.]

    The Performance of Chlorophyll-a Distribution Estimation by Using Ratio Algorithm on Landsat-8 in Sungai Merbok Estuary / Jesse Vince Rabing ... [et al.] by Rabing, Jesse Vince, Abd.Aziz, Khairul Naim, Kamaruddin, Sharir Aizat, Roslani, Muhammad Akmal, Tajam, Jamil, Ahmad, Aziani, Nazri, Rosnani, Zainol, Zamzila Erdawati, Ramli, Rohayu, Shaari, Mohd Idrus

    Published 2022
    “…The distribution models generated from the algorithms were utilizing Landsat-8 satellite images with B-G and B-R bands ratio. …”
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  2. 2
    Performance of Levenberg-Marquardt neural network algorithm in power quality disturbances classification / Adibah I’zzah Mohamad Kasim

    Performance of Levenberg-Marquardt neural network algorithm in power quality disturbances classification / Adibah I’zzah Mohamad Kasim by Mohamad Kasim, Adibah I’zzah

    Published 2025
    “…Results demonstrated that the LM algorithm outperformed Bayesian Regularization (BR) and Scaled Conjugate Gradient (SCG) methods in terms of accuracy, convergence speed, and computational efficiency, achieving near-perfect regression values and minimal mean square error for most PQD types. …”
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  3. 3
    Automated Model Generation Approach Using MATLAB

    Automated Model Generation Approach Using MATLAB by Xia, Likun

    Published 2011
    “…These algorithms may be lookup tables, radial basis functions (RBF), artificial neural networks (ANN) and its derivations such as fuzzy logic (FL) and neural-fuzzy network (NF), and regression. …”
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  4. 4
    Narx network based data-driven algorithm for detection of tray faults in nonlinear dynamic distillation column

    Narx network based data-driven algorithm for detection of tray faults in nonlinear dynamic distillation column by Taqvi, S.A.A., Zabiri, H., Tufa, L.D., Uddin, F., Fatima, S.A., Maulud, A.S.

    Published 2020
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  5. 5
    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan

    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

    Published 2020
    “…In this research, a fault diagnosis methodology based on Cross Industry Standard Process for Data Mining (CRISP-DM) model was proposed for the purpose of damage detection. In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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  6. 6
    Design and analysis of an early heart attack detection using openCV

    Design and analysis of an early heart attack detection using openCV by Muhammad Rafsanjani, Basri, Fahmi, Samsuri

    Published 2022
    “…This research aims to detect cardiac events with the use of four different algorithms: logistic regression, decision trees, random forest, and k nearest neighbor using python language. …”
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  7. 7
    Hybrid anti-islanding algorithm for utility interconnection of distributed generation

    Hybrid anti-islanding algorithm for utility interconnection of distributed generation by Abdolrasol, M.G.M., Mekhilef, Saad

    Published 2009
    “…Active detection algorithm generates disturbances at the output by Positive feedback and Continuous feedback signal injection which is based on DQ implementation. …”
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  8. 8
    Artifact identification for blood pressure and photoplethysmography signals in an unsupervised environment / Lim Pooi Khoon

    Artifact identification for blood pressure and photoplethysmography signals in an unsupervised environment / Lim Pooi Khoon by Lim , Pooi Khoon

    Published 2020
    “…In this study, an automated artifact detection algorithm was developed for Blood Pressure and PPG signals. …”
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  9. 9
    Outlier detection in circular regression model using minimum spanning tree method

    Outlier detection in circular regression model using minimum spanning tree method by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari, Roslinazairimah, Zakaria

    Published 2019
    “…Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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  10. 10
    The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model

    The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model by Nur Faraidah, Muhammad Di, Siti Zanariah, Satari

    Published 2017
    “…In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. …”
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  11. 11
    A detector generating algorithm for intrusion detection inspired by artificial immune system

    A detector generating algorithm for intrusion detection inspired by artificial immune system by Alsharafi, Walid Mohamed, Omar, Mohd Nizam

    Published 2015
    “…One of the most operational improvements in the standard of NSA is how to generate effective detectors which play a significant role in self and non-self discrimination in intrusion detection system (IDS).In this paper, we offer an improvement to a detector generating algorithm to generate effective detectors which leads to improve the standard of NSA, which in turn leads to improve the NSA based anomaly intrusion detection.Experimental results show that the improved algorithm able to generate more effective detectors and keeping the space and time complexities better than in the standard of NSA. …”
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  12. 12
    Comparative study of clustering-based outliers detection methods in circular-circular regression model

    Comparative study of clustering-based outliers detection methods in circular-circular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Yong Zulina, Zubairi, Abdul Ghapor, Hussin

    Published 2021
    “…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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  13. 13
    Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory

    Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory by Rusli, Julie Roslita

    Published 2011
    “…The algorithms used in this generator are based on March algorithm. …”
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  14. 14
    Predictive models for hotspots occurrence using decision tree algorithms and logistic regression.

    Predictive models for hotspots occurrence using decision tree algorithms and logistic regression. by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

    Published 2013
    “…The results show that the C4.5 algorithm has better performance than the ID3 algorithm in terms of accuracy and the number of generated rules. …”
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  15. 15
    Comparative study of clustering-based outliers detection methods in circular-circular regression model

    Comparative study of clustering-based outliers detection methods in circular-circular regression model by Siti Zanariah Satari, Nur Faraidah Muhammad Di, Yong Zulina Zubairi, Abdul Ghapor Hussin

    Published 2021
    “…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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  16. 16
    Comparative study of clustering-based outliers detection methods in circularcircular regression model

    Comparative study of clustering-based outliers detection methods in circularcircular regression model by Siti Zanariah, Satari, Nur Faraidah, Muhammad Di, Yong Zulina, Zubairi, Abdul Ghapor, Hussin

    Published 2021
    “…This paper is a comparative study of several algorithms for detecting multiple outliers in circular-circular regression model based on the clustering algorithms. …”
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  17. 17
    Generation of new low-complexity March algorithms for optimum faults detection in SRAM

    Generation of new low-complexity March algorithms for optimum faults detection in SRAM by Jidin, Aiman Zakwan, Hussin, Razaidi, Lee, Weng Fook, Mispan, Mohd Syafiq, Zakaria, Nor Azura, Loh, Wan Ying, Zamin, Norshuhani

    Published 2023
    “…A high-complexity test algorithm like the March MSS (18N) can guarantee the detection of all unlinked static faults in SRAM. …”
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  18. 18
    The effect of replacement strategies of genetic algorithm in regression test case prioritization of selected test cases

    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

    Published 2015
    “…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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  19. 19
    An enhancement of classification technique based on rough set theory for intrusion detection system application

    An enhancement of classification technique based on rough set theory for intrusion detection system application by Noor Suhana, Sulaiman

    Published 2019
    “…Thus, to deal with huge dataset, data mining technique can be improved by introducing discretization algorithm to increase classification performance. The generation of rule is considered a crucial process in data mining and the generated rules are in a huge number. …”
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  20. 20
    Modified Miller-Rabin primality test algorithm to detect prime numbers for generating RSA keys

    Modified Miller-Rabin primality test algorithm to detect prime numbers for generating RSA keys by Shereek, Balkees Mohamed

    Published 2016
    “…The prime numbers with the size of 256, 512, and 1024 bits are generated using the proposed modified algorithm. The performance of the proposed modified Miller-Rabin was analysed in terms of the time taken to detect the prime numbers and compare the time taken for generating the prime numbers using original Miller-Rabin method. …”
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