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  1. 1
    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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  2. 2
    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification

    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

    Published 2020
    “…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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  3. 3
    Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar

    Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar by Anuar, Norhasnelly

    Published 2015
    “…To overcome these problems this project proposes a methodology for determining consumers’ TLPs by using fuzzy C-means (FCM) clustering method and probability neural networks (PNN) classification techniques. …”
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  4. 4
    Local gray level S-curve transformation – A generalized contrast enhancement technique for medical images

    Local gray level S-curve transformation – A generalized contrast enhancement technique for medical images by Gandhamal, A., Talbar, S., Gajre, S., Hani, A.F.M., Kumar, D.

    Published 2017
    “…The proposed technique can be used as a preprocessing tool for effective segmentation and classification of tissue structures in medical images. © 2017 Elsevier Ltd…”
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  5. 5
    Development of compound clustering techniques using hybrid soft-computing algorithms

    Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

    Published 2006
    “…The hierarchical fuzzy clustering method developed here is far better than a similar implementation of the hard k-means method. When used for overlapping structures, its performance improves significantly. …”
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    Monograph
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  6. 6
    Application of artificial neural network in discriminating the agarwood oil quality using significant chemical compounds / Mohd Hezri Fazalul Rahiman … [et al.]

    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

    Published 2014
    “…Back-propagation training algorithm and sigmoid transfer function were used to optimise the parameters in the training network. …”
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    Book Section
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  7. 7
    Incremental continuous ant colony optimization for tuning support vector machine’s parameters

    Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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  8. 8
    Detection of sweetness level for fruits (watermelon) with machine learning

    Detection of sweetness level for fruits (watermelon) with machine learning by Wan Nazulan, Wan Nurul Suraya, Asnawi, Ani Liza, Mohd Ramli, Huda Adibah, Jusoh, Ahmad Zamani, Ibrahim, Siti Noorjannah, Mohamed Azmin, Nor Fadhillah

    Published 2020
    “…The objective of this work is to investigate the sweetness parameter for the fruit’s detection and classification algorithm in machine learnings. …”
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    Proceeding Paper
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  9. 9
    Hybrid ACO and SVM algorithm for pattern classification

    Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

    Published 2013
    “…Hybridization algorithms between ACO and SVM techniques were proposed. …”
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  10. 10
    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak

    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…The third stage is to classify individual jammers according to the specific pattern and characteristics design as defined in jamming identification and classification parameters. It involves development of Max-Min Rule-Based Classification Algorithm. …”
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  11. 11
    Optimizing support vector machine parameters using continuous ant colony optimization

    Optimizing support vector machine parameters using continuous ant colony optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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  12. 12
    Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor

    Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor by Intan Noradybah Md Rodi

    Published 2019
    “…Remote sensing technologies are used globally to derive some of crucial spatial variable parameter such as vegetation cover. Three different classification algorithm, minimum distance classifier, Mahalanobis distance classifier and maximum likelihood algorithm was applied to classify the forest area in Gunung Basor. …”
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    Undergraduate Final Project Report
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  13. 13
    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani

    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

    Published 2015
    “…The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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  14. 14
    Aco-based feature selection algorithm for classification

    Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

    Published 2022
    “…The proposed EGCACO algorithm can be utilised for FS in DNA microarray classification tasks that involve large dataset size in various application domains.…”
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  15. 15
    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm

    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

    Published 2023
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  16. 16
    Development of an intelligent prediction tool for rice yield based on machine learning techniques

    Development of an intelligent prediction tool for rice yield based on machine learning techniques by Md. Sap, Mohd. Noor, Awan, A. M.

    Published 2006
    “…Support vector machine algorithm is developed for classification of rice plantation data. …”
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  17. 17
    Integrated ACOR/IACOMV-R-SVM Algorithm

    Integrated ACOR/IACOMV-R-SVM Algorithm by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2017
    “…The first algorithm, ACOR-SVM, will tune SVM parameters, while the second IACOMV-R-SVM algorithm will simultaneously tune SVM parameters and select the feature subset. …”
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  18. 18
    First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms

    First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms by Azwa, Abdul Aziz, Fadhilah, Ahmad

    Published 2014
    “…The comparative analysis is also conducted to discover the best classification model for prediction. From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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  19. 19
    Soft Set Decision/Forecasting System Based on Hybrid Parameter Reduction Algorithm

    Soft Set Decision/Forecasting System Based on Hybrid Parameter Reduction Algorithm by Mohammed, Mohammed Adam Taheir, Sadiq, Ali Safa, Ruzaini, Abdullah Arshah, Ernawan, Ferda, Mirjalili, Seyedali

    Published 2017
    “…The results show that the decision partition order technique performs better in parameter reduction up to 50%, while other algorithms could not obtain any reduction in some scenarios. …”
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  20. 20
    Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network

    Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network by Hairuddin, Nurul Liyana, Yusuf, Lizawati Mi, Othman, Mohd Shahizan

    Published 2020
    “…This was to obtain a good combination of parameters in order to produce a better gender classification. …”
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