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  1. 1
    The use of SOM for fingerprint classification

    The use of SOM for fingerprint classification by Turky A.M., Ahmad M.S.

    Published 2023
    “…This paper introduces an approach to fingerprint classification by using Self-Organizing Maps (SOM). In order to be able to deal with fingerprint images having distorted regions, the SOM learning and classification algorithms are modified. …”
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  2. 2
    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network

    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

    Published 2014
    “…Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. …”
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  3. 3
    Modified word representation vector based scalar weight for contextual text classification

    Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

    Published 2024
    “…In addition, a contextual text classification experiment is conducted using benchmarked datasets to assess the performance of the modified word vectors in the targeted classification task. …”
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  4. 4
    A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification

    A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification by Quteishat, A., Lim, C.P., Tan, K.S.

    Published 2010
    “…The first stage consists of a modified fuzzy min-max (FMM) neural-network-based pattern classifier, while the second stage consists of a genetic-algorithm (GA)-based rule extractor. …”
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  5. 5
    A hybrid-based modified adaptive fuzzy inference engine for pattern classification

    A hybrid-based modified adaptive fuzzy inference engine for pattern classification by Sayeed, Md. Shohel, Ramli, Abdul Rahman, Hossen, Md. Jakir, Samsudin, Khairulmizam, Rokhani, Fakhrul Zaman

    Published 2011
    “…A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data set. …”
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  6. 6
    Functional link neural network with modified bee-firefly learning algorithm for classification task

    Functional link neural network with modified bee-firefly learning algorithm for classification task by Mohmad Hassim, Yana Mazwin

    Published 2016
    “…The aim is to introduce an improved learning algorithm that can provide a better solution for training the FLNN network for the task of classification…”
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  7. 7
    Improved swarm intelligence algorithms with time-varying modified Sigmoid transfer function for Amphetamine-type stimulants drug classification

    Improved swarm intelligence algorithms with time-varying modified Sigmoid transfer function for Amphetamine-type stimulants drug classification by Muda, Azah Kamilah, Mohd Yusof, Norfadzlia, Pratama, Satrya Fajri, Carbo-Dorca, Ramon, Abraham, Ajith

    Published 2022
    “…In this article, a new time-varying modified Sigmoid transfer function with two time-varying updating schemes is proposed as the binarization method for particle swarm optimization (PSO), grey wolf optimization algorithm (GWO), whale optimization algorithm (WOA), harris hawk optimization (HHO), and manta-ray foraging optimization (MRFO). …”
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  8. 8
    An approach to improve functional link neural network training using modified artificial bee colony for classification task

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Yana Mazwin Mohmad Hassim, Rozaida Ghazali

    Published 2013
    “…In this paper, a modified Artificial Bee Colony (mABC) is used to recover the BP drawbacks. …”
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  9. 9
    An approach to improve functional link neural network training using modified artificial bee colony for classification task

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2012
    “…In this paper, a modified Artificial Bee Colony (mABC) is used to recover the BP drawbacks. …”
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  10. 10
    An approach to improve functional link neural network training using modified artificial bee colony for classification task

    An approach to improve functional link neural network training using modified artificial bee colony for classification task by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2012
    “…In this paper, a modified Artificial Bee Colony (mABC) is used to recover the BP drawbacks. …”
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  11. 11
    An Improved Wavelet Neural Network For Classification And Function Approximation

    An Improved Wavelet Neural Network For Classification And Function Approximation by Ong , Pauline

    Published 2011
    “…The modified WNN was then applied in the areas of classification and function approximation.…”
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  12. 12
    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
    “…The results show that the proposed modified ANFIS architecture with gaussian membership function and Artificial Bee Colony (ABC) optimization algorithm, on average has achieved classification accuracy of 99.5% with 83% less computational complexity.…”
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  13. 13
    MODIFIED AIS-BASED CLASSIFIER FOR MUSIC GENRE CLASSIFICATION

    MODIFIED AIS-BASED CLASSIFIER FOR MUSIC GENRE CLASSIFICATION by Muda, N. A.

    Published 2010
    “…The objective of this paper is to introduce a possible new technique in the Artificial Immune System (AIS) domain called a modified immune classifier (MIC) for music genre classification. …”
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  14. 14
    The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification

    The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification by Faizol, Bin Mohd Suria

    Published 2020
    “…However, none of the available works had proposed BFOA as a classification algorithm despite of its good performance. …”
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  15. 15
    Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering

    Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering by Rashed, Alwatben Batoul

    Published 2022
    “…The present study proposed a modified selection mechanism for archive updates in MOPSO (MOPSO-CD). …”
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  16. 16
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…Classification refers to a predictive modeling problem where a class label is predicted for a given example of input data. …”
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  17. 17
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…Classification refers to a predictive modeling problem where a class label is predicted for a given example of input data. …”
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  18. 18
    Reliable multiclass cancer classification of microarray gene expression profiles using an improved wavelet neural network

    Reliable multiclass cancer classification of microarray gene expression profiles using an improved wavelet neural network by Zainuddin, Zarita, Pauline, Ong

    Published 2011
    “…The modified WNN was then applied to heterogeneous cancer classification using four different microarray benchmark datasets. …”
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  19. 19
    Automated classification of blasts in acute leukemia blood samples using HMLP network

    Automated classification of blasts in acute leukemia blood samples using HMLP network by Harun, N. H., Mashor, M.Y., Abdul Nasir, A.S., Rosline, H.

    Published 2011
    “…This paper presents a study on classification of blasts in acute leukemia blood samples using artificial neural network.In acute leukemia there are two major forms that are acute myelogenous leukemia (AML) and acute lymphocytic leukemia (ALL).Six morphological features have been extracted from acute leukemia blood images and used as neural network inputs for the classification.Hybrid Multilayer Perceptron (HMLP) neural network was used to perform the classification task.The Hybrid Multilayer Perceptron(HMLP) neural network is trained using modified RPE(MRPE) training algorithm for 1474 data samples.The Hybrid Multilayer Perceptron (HMLP) neural network produces 97.04% performance accuracy.The result indicates the promising capabilities and abilities of the Hybrid Multilayer Perceptron (HMLP) neural network using modified RPE (MRPE) training algorithm for classifying and distinguishing the blasts from acute leukemia blood samples.…”
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  20. 20
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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