Search Results - (( simulation classification using algorithm ) OR ( data classification modified algorithm ))

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  1. 1
    Electroencephalography Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation

    Electroencephalography Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation by Mohamed, Shakir, Qidwai, Uvais, Malik, Aamir Saeed, Kamel , Nidal

    Published 2015
    “…With controlled data types, healthy/normal, seizure and pre-seizure classes, tuning of algorithms for detection and classification applications can be attained. …”
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  2. 2
    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data

    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

    Published 2022
    “…The performance of the proposed method is illustrated using simulation study and on glass vessel data with 1920 variables, cardiomyopathy microarray data with 6319 variables, and octane data with 226 dimensions. …”
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  3. 3
    EEG Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation

    EEG Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation by Shakir, Mohamed, Qidwai, Uvais, Malik, Aamir Saeed, Kamel, Nidal

    Published 2015
    “…With controlled data types, healthy/normal, seizure and pre-seizure classes, tuning of algorithms for detection and classification applications can be attained. …”
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  4. 4
    RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm

    RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm by Basri, S.M.M., Nawi, N.M., Mamat, M., Hamid, N.A.

    Published 2018
    “…The efficiency of the proposed method is verified by means of simulation on four classification problems. The results show that the computational efficiency of the proposed method was better than the conventional BP algorithm.…”
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  5. 5
    The effect of pre-processing techniques and optimal parameters on BPNN for data classification

    The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

    Published 2015
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  6. 6
    A modified reweighted fast consistent and high-breakdown estimator for high-dimensional datasets

    A modified reweighted fast consistent and high-breakdown estimator for high-dimensional datasets by A. Baba, Ishaq, Midi, Habshah, June, Leong W., Ibragimov, Gafurjan

    Published 2024
    “…Outlier detection and classification algorithms play a critical role in statistical analysis. …”
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  7. 7
    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control

    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control by Mohd Hanafi, Muhammad Sidik

    Published 2020
    “…Total of ten control methods determined from population and individual data were tested against another 10 healthy persons to evaluate the algorithm performance. …”
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  8. 8
    New modified controlled bat algorithm for numerical optimization problem

    New modified controlled bat algorithm for numerical optimization problem by Waqas Haider Bangyal, Abdul Hameed, Jamil Ahmad, Kashif Nisar, Muhammad Reazul Haque, Ag. Asri Ag. Ibrahim, Joel J. P. C. Rodrigues, M. Adil Khan, Danda B. Rawat, Richard Etengu

    Published 2022
    “…The MCBA-NN algorithm may be used effectively for data classification and statistical problems in the future.…”
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  9. 9
    Forward scattering radar for real-time detection of human activities and fall classification

    Forward scattering radar for real-time detection of human activities and fall classification by Abdulhameed, Ali Ahmed

    Published 2019
    “…The frequency spectrum signatures extracted from the experimentally collected data were used as input features to the classification unit. …”
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  10. 10
    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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  11. 11
    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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  12. 12
    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
    “…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
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  13. 13
    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
    “…Nowadays, the use of SVM is very perspective for the big data classification. SVM provides a global solution for data classification but SVM is highly sensitive to noise data and may not be effective when the level of noise data is high. …”
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  14. 14
    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
    “…Nowadays, the use of SVM is very perspective for the big data classification. SVM provides a global solution for data classification but SVM is highly sensitive to noise data and may not be effective when the level of noise data is high. …”
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  15. 15
    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
    “…Thus, this study aims to adopt and modify the BFOA into Instance Selection (IS) classifier by manipulating its global search capability and high convergence rate for data classification problem. …”
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  16. 16
    A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules

    A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

    Published 2013
    “…Thus, this thesis proposed two variants of hybrid ACO with simulated annealing (SA) algorithm for solving problem of classification rule induction. …”
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  17. 17
    Feature Selection using Binary Simulated Kalman Filter for Peak Classification of EEG Signals

    Feature Selection using Binary Simulated Kalman Filter for Peak Classification of EEG Signals by Badaruddin, Muhammad, Mohd Falfazli, Mat Jusof, Mohd Ibrahim, Shapiai, Asrul, Adam, Zulkifli, Md. Yusof, Kamil Zakwan, Mohd Azmi, Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Norrima, Mokhtar

    Published 2018
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  18. 18
    Mutable composite firefly algorithm for gene selection in microarray based cancer classification

    Mutable composite firefly algorithm for gene selection in microarray based cancer classification by Fajila, Mohamed Nisper Fathima

    Published 2022
    “…A computational approach for gene selection based on microarray data analysis has been applied in many cancer classification problems. …”
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  19. 19
    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network

    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

    Published 2016
    “…Two modified algorithms are proposed in this research, which are mixture of the momentum algorithm with different learning rate algorithms. …”
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  20. 20
    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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