Search Results - (( _ evaluation step algorithm ) OR ( shape identification learning algorithm ))*

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    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

    Published 2020
    “…After evaluating the results of these algorithms, a hybrid Artificial Neural Network-based Imperial Competitive Algorithm (ANN-ICA) was presented in the deployment step of the proposed methodology to identify the structural damage of illustrative structures. …”
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    Thesis
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    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    Published 2016
    “…Most of the existing plant identification methods are based on both the global shape features and the intact plant leaves. …”
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    Thesis
  3. 3

    Zero distortion-based steganography for handwritten signature by Iranmanesh, Vahab

    Published 2018
    “…In addition, the imperceptibility rates of 3.5% and 4.7% were obtained for machine learning and human perception evaluation approaches, respectively, when identifying the stego signatures (s). …”
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    Thesis
  4. 4

    Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei by Chen , Shilei

    Published 2021
    “…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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    Thesis
  5. 5

    Identification of tajwid using artificial neural networks / Zunnajah Kamaruddin by Kamaruddin, Zunnajah

    Published 2005
    “…In order to have a system which has an ability to learn, back-propagation learning algorithm is used. …”
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    Thesis
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    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

    Published 2012
    “…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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    Thesis
  7. 7

    Classification of Citrus (Rutaceae) by Using Image Processing by Najwa Bari'ah Mohd Tabri

    Published 2019
    “…A machine learning algorithms, SVM have been used to build species identification models. …”
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    Undergraduate Final Project Report
  8. 8

    Bacteria identification via Artificial Neural Network based-on Bergey’s manual by Ruhaimi, Amirul Hafiiz

    Published 2017
    “…Levenberg Marquardt algorithm based Feed-forward backpropagation with Multilayer perceptron type of ANN was used in the training and learning sessions of the ANN development in order to obtain high accuracy simulation results within short period of time.…”
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    Student Project
  9. 9

    Application of artificial neural network in bacteria identification based on Bergey’s manual: Hydrogenophilaceae family: article by Ruhaimi, Amirul Hafiiz, Ahmad, Normadyzah, Husin, Hazlina, Mohamad Pauzi, Syazana

    Published 2017
    “…Levenberg Marquardt algorithm based Feedforward backpropagation with Multilayer perceptrons type of ANN was used in the training and learning sessions of the ANN development in order to obtain high accuracy simulation results. within short period time.…”
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    Article
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    Classification of metal screw defect detection using FOMO on edge impulse / Muhammad Imran Daing by Daing, Muhammad Imran

    Published 2025
    “…The introduction of deep learning, particularly in visual detection, offers a significant improvement in the effectiveness and precision of defect identification. …”
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    Student Project
  14. 14

    Multistep forecasting for highly volatile data using new algorithm of Box-Jenkins and GARCH by Siti Roslindar, Yaziz, Roslinazairimah, Zakaria

    Published 2018
    “…In evaluating the performance of the multistep ahead forecast, the proposed algorithm is employed to daily world gold price series of 5-year data. …”
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    Conference or Workshop Item
  15. 15

    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. This study applies image processing techniques to detect the color and shape of watermelon’s skin for grading based on the sweetness level using K-means clustering method via the Python platform. 13 samples of watermelon images are used to test the functionality of the proposed detection system in this study. …”
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    Proceeding Paper
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    Novel Adaptive Bacterial Foraging Algorithms for Global Optimisation with Application to Modelling of a TRS by Ahmad Nor Kasruddin, Nasir, Nor Maniha, Abd Ghani, Tokhi, M. O.

    Published 2015
    “…The constant step size in the original bacterial foraging algorithm causes oscillation in the convergence graph where bacteria are not able to reach the optimum location with large step size, hence reducing the accuracy of the final solution. …”
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    Article
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    Iterative And Single-Step Solutions Of Two Dimensional Time-Domain Inverse Scattering Problem Featuring Ultra Wide Band Sensors by Binajjaj, Saeed Ali Saeed

    Published 2010
    “…First, the algorithms‘ performances were evaluated using numerical simulation employing two different scanning geometries: limited and full view scanning geometries, where the applicability of these algorithms was accessed by comparing the reconstructed images with actual model. …”
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    Thesis
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    Algorithmic approaches in model selection of the air passengers flows data by Ismail, Suzilah, Yusof, Norhayati, Tuan Muda, Tuan Zalizam

    Published 2015
    “…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
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    Conference or Workshop Item
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