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  1. 1
    Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification

    Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification by Abusnaina, Ahmed A., Abdullah, Rosni

    Published 2013
    “…Traditional training algorithms have some drawbacks such as local minima and its slowness.Therefore, evolutionary algorithms are utilized to train neural networks to overcome these issues.This research tackles the ANN training by adapting Mussels Wandering Optimization (MWO) algorithm.The proposed method tested and verified by training an ANN with well-known benchmarking problems.Two criteria used to evaluate the proposed method were overall training time and classification accuracy.The obtained results indicate that MWO algorithm is on par or better in terms of classification accuracy and convergence training time.…”
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  2. 2
    BRAIN ACTIVITIES FOR MOTOR MOVEMENT

    BRAIN ACTIVITIES FOR MOTOR MOVEMENT by ., WAFAA ELSAYED ELBASTY

    Published 2012
    “…Multivariate adaptive auto regressive (MVAAR) method is used in the feature extraction part because it is suitable for motor imaginary. …”
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  3. 3
    Performance evaluation of direction of arrival (DOA) for linear array antenna design using multiple signal classification (MUSIC) algorithm in variation of displacement vectors and noise / Norhayati Hamzah

    Performance evaluation of direction of arrival (DOA) for linear array antenna design using multiple signal classification (MUSIC) algorithm in variation of displacement vectors and... by Hamzah, Norhayati

    Published 2007
    “…The use of adaptive antenna arrays is one area that gives promise for improving capacity of wireless communication systems and provides improved safety through location capabilities. …”
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  4. 4
    Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength

    Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength by Hussain Talpur, Kashif

    Published 2015
    “…Many researchers have trained ANFIS parameters using metaheuristic algorithms but very few have considered optimizing the ANFIS rule-base. …”
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  5. 5
    Condition diagnosis of bearing system using multiple classifiers of ANNs and adaptive probabilities in genetic algorithms

    Condition diagnosis of bearing system using multiple classifiers of ANNs and adaptive probabilities in genetic algorithms by Wulandhari, Lili A., Wibowo, Antoni, Desa, Mohammad I.

    Published 2014
    “…Therefore, finding the best weights in learning process is an important task for obtaining good performance of ANNs.Previous researchers have proposed some methods to get the best weights such as simple average and majority voting.However, these methods have some limitations in providing the best weights especially in condition diagnosis of bearing systems.In this paper, we propose a hybrid technique of multiple classifier-ANNs (mANNs) and adaptive probabilities in genetic algorithms (APGAs) to obtain the best weights of ANNs in order to increase the classification performance of ANNs in condition diagnosis of bearing systems. …”
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  6. 6
    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh

    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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  7. 7
    An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons

    An efficient intrusion detection model based on hybridization of artificial bee colony and dragonfly algorithms for training multilayer perceptrons by Ghanem, Waheed Ali H. M., Aman, Jantan, Ahmed Ghaleb, Sanaa Abduljabbar, Naseer, Abdullah B.

    Published 2020
    “…Ten other metaheuristic algorithms were adapted to train the neural network and their performances were compared with that of the proposed model. …”
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  8. 8
    Modified anfis architecture with less computational complexities for classification problems

    Modified anfis architecture with less computational complexities for classification problems by Talpur, Noureen

    Published 2018
    “…Furthermore, researchers have mainly used metaheuristic algorithms to avoid the problem of local minima in standard learning method. …”
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  9. 9
    Ensemble based categorization and adaptive model for malware detection

    Ensemble based categorization and adaptive model for malware detection by Ahmad Zabidi, Muhammad Najmi, Maarof, Mohd Aizaini, Zainal, Anazida

    Published 2011
    “…This may include the use of signature based method. In this paper, we propose an ensemble categorization by using ensemble classification and clustering together with adaptive learning model. …”
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  10. 10
    Neuro fuzzy classification and detection technique for bioinformatics problems

    Neuro fuzzy classification and detection technique for bioinformatics problems by Othman, Mohd. Fauzi, Moh, Thomas Shan Yau

    Published 2007
    “…It is very important to identify new integration of classification or clustering algorithm especially in neuro fuzzy domain as compared to conventional or traditional method. …”
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  11. 11
    Computational intelligence approach for classification and risk quantification of metabolic syndrome / Habeebah Adamu Kakudi

    Computational intelligence approach for classification and risk quantification of metabolic syndrome / Habeebah Adamu Kakudi by Habeebah Adamu , Kakudi

    Published 2019
    “…Therefore, the aim of this study is to propose and develop a novel non-clinical technique for the early risk quantification and classification of MetS refered to as genetically optimized Bayesian adaptive resonance theory mapping (GOBAM). Genetic Algorithm(GA) is used to optimize the order of sequence of the input sample and the parameters of the Bayesian ARTMAP (BAM). …”
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  12. 12
    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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  13. 13
    Radiomics analysis and supervised machine learning model for classification of cervical cancer images using diffusion weighted imaging-MRI

    Radiomics analysis and supervised machine learning model for classification of cervical cancer images using diffusion weighted imaging-MRI by Ramli, Zarina

    Published 2024
    “…This study investigates the efficacy of staging classification using diffusion-weighted imaging magnetic resonance imaging (DWIMRI) through radiomic analysis and machine learning. …”
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  14. 14
    Enhanced Adaptive Neuro-Fuzzy Inference System Classification Method for Intrusion Detection

    Enhanced Adaptive Neuro-Fuzzy Inference System Classification Method for Intrusion Detection by Jia, Liu

    Published 2024
    “…Additionally, standard deviation and proposed adaptive K-means algorithms have been employed to minimize the generated rules by ANFIS from the proposed hybrid models. …”
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  15. 15
    Classification of transient disturbance using Wavelet based support vector machine / Fahteem Hamamy Anuwar

    Classification of transient disturbance using Wavelet based support vector machine / Fahteem Hamamy Anuwar by Anuwar, Fahteem Hamamy

    Published 2012
    “…The simulations will be done using the PSCAD/EMTDC software. Switching of capacitors was simulated to generate oscillatory transients in a power distribution system. …”
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  16. 16
    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa

    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

    Published 2018
    “…These findings suggest the potential use of this software as aided tool for radiologist in detecting WMH, especially to predict patients with higher risk of several chronic diseases.…”
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  17. 17
    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa

    An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

    Published 2018
    “…These findings suggest the potential use of this software as aided tool for radiologist in detecting WMH, especially to predict patients with higher risk of several chronic diseases.…”
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  18. 18
    Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi

    Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi by Rahimi, Ahmad Faris

    Published 2017
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  19. 19
    Software Classification Using Structure-Based Descriptors

    Software Classification Using Structure-Based Descriptors by Ramadan, Qusai Hussein

    Published 2009
    “…Based on the undertaken experiment, the IBK algorithm is noted to generate the highest classification accuracy (74.8%) compared to several other algorithms provided in the Weka tool. …”
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  20. 20
    Software defect prediction framework based on hybrid metaheuristic optimization methods

    Software defect prediction framework based on hybrid metaheuristic optimization methods by Wahono, Romi Satria

    Published 2015
    “…For the purpose of this study, ten classification algorithms have been selected. The selection aims at achieving a balance between established classification algorithms used in software defect prediction. …”
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