Search Results - (( basic classification modelling algorithm ) OR ( a classification using algorithm ))

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  1. 1

    Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak by Rajogoval, Illayakantthan

    Published 2022
    “…The COVID-19 Basic Reproduction Number, R0 a predictive model is developed using a linear regression classification algorithm to predict the COVID-19 Basic Reproduction Number, Robased on the actual COVID-19 Basic Reproduction Number, R0. …”
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    Monograph
  2. 2

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…These rules consist of conditions over attribute value pairs called the descriptions, and decision attributes. Therefore generating a good decision model or classification model is a major component in many data mining researches. …”
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    Thesis
  3. 3

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…This reserarch adapted a methodology of computer vision and algorithms that exploit image segmentation, feature extraction and fuzzy classification to guide the research activities. …”
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    Thesis
  4. 4
  5. 5

    A Novel Method for Fashion Clothing Image Classification Based on Deep Learning by Yoon Shin, Seong, Jo, Gwanghyun, Wang, Guangxing

    Published 2023
    “…This paper suggested a deep learning-based image classification technique based on a CNN model and improved convolutional and pooling layers. …”
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    Article
  6. 6

    Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza by Ghulam , Murtaza

    Published 2021
    “…Several studies developed BrC detection and classification models using Hp images. However, the existing models required high computational resources, long training time, and their performance is compromised due to a higher misclassification rate. …”
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    Thesis
  7. 7

    EMG motion pattern classification through design and optimization of neural network by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

    Published 2012
    “…Different types of ANN models are basically structured with many interconnected network elements which can develop pattern classification strategies based on a set of input/training data. …”
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    Proceeding Paper
  8. 8
  9. 9

    Modelling of clinical risk groups (CRGs) classification using FAM by Mohd. Asi, Salina, Saad, Puteh

    Published 2006
    “…Fuzzy ARTMAP (FAM) is an incremental supervised learning of recognition neural networks in response to input and target pattern [4, 5]. FAM is a fast learning algorithm and used less epoch training [4]. …”
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    Conference or Workshop Item
  10. 10

    Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome by Salari, Nader

    Published 2014
    “…The classification performance of K1-K2-NN model was benchmarked against 13 commonly used classification models using repeated random sub-sampling crossvalidation on ACSEKI data set. …”
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    Thesis
  11. 11

    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

    Published 2019
    “…The derived model was rigorously compared to four models, including basic ELM, basic FLN, Reduce Kernel ELM (RK-ELM), and RK-FLN. …”
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    Conference or Workshop Item
  12. 12

    Al-Hams and Al-Jahr Sifaat evaluation using classification approach by Altalmas, Tareq, M., Ahmad, Salmiah, Sediono, Wahju, Nik Hashim, Nik Nur Wahidah, Embong, Abd Halim, Hassan, Surul Shahbudin

    Published 2021
    “…As a part of the automated system’s developed, therefore, in this paper, a classification approach is introduced to develop a classification model that can classify the Quranic letters to its first pair of Sifaat with opposites (Al-Hams and Al-Jahr). …”
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    Proceeding Paper
  13. 13

    Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance by Nor Azlan, Nor Asmaa Alyaa

    Published 2021
    “…The LP’s application is need to be further computed with a technique and Simplex algorithm is the one that commonly used. …”
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    Thesis
  14. 14

    Image Splicing Detection With Constrained Convolutional Neural Network by Lee, Yang Yang

    Published 2019
    “…With the trained and tuned CNN model, a cross-database classification evaluation is carried out. …”
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    Thesis
  15. 15

    Disposable Biomimetic Array Sensor Strip Coupled With Chemometric Algorithm For Quality Assessment Of Orthosiphon Stamineus Benth Samples by Yap, Maxsim Mee Sim

    Published 2006
    “…A disposable screen printed array sensor strip based on self-plasticized methacrylate acrylate PVC blend lipid membranes combined with chemometric algorithm has been developed and applied for qualitative and quantitative analysis of O.stamineus samples. …”
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    Thesis
  16. 16

    Identification model for hearing loss symptoms using machine learning techniques by Nasiru Garba Noma

    Published 2014
    “…The model is implemented using both unsupervised and supervised machine learning techniques in the form of Frequent Pattern Growth (FP-Growth) algorithm as feature transformation method and multivariate Bernoulli naïve Bayes classification model as the classifier. …”
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    Thesis
  17. 17

    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

    Published 2004
    “…The network stages are a feature extraction network, and a classification network. …”
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    Thesis
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    Malay continuous speech recognition using continuous density hidden Markov model by Ting, Chee Ming

    Published 2007
    “…Hidden Markov Model (HMM) based statistical modeling is used in Malay speech recognition. …”
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    Thesis
  20. 20

    Fault diagnosis in unbalanced radial distribution networks using generalised regression neural network by Mirzaei, Maryam

    Published 2011
    “…To achieve this goal, the initial or pre-fault condition of the system has to be computed. Using the proposed method, less learning time of PNN is required for classification. …”
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    Thesis