Search Results - (( data optimization based algorithm ) OR ( defect classification based algorithm ))

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  1. 1

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

    Published 2015
    “…The proposed framework and models that are are considered to be the specific research contributions of this thesis are: 1) a comparison framework of classification models for software defect prediction known as CF-SDP, 2) a hybrid genetic algorithm based feature selection and bagging technique for software defect prediction known as GAFS+B, 3) a hybrid particle swarm optimization based feature selection and bagging technique for software defect prediction known as PSOFS+B, and 4) a hybrid genetic algorithm based neural network parameter optimization and bagging technique for software defect prediction, known as NN-GAPO+B. …”
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    Thesis
  2. 2

    Using the bees algorithm to optimise a support vector machine for wood defect classification by Pham, D.T, Muhammad, Zaidi, Mahmuddin, Massudi, Ghanbarzadeh, Afshin, Koc, Ebubekir, Otri, Sameh

    Published 2007
    “…This paper describes a new application of the Bees Algorithm to the optimization of a Support Vector Machine (SVM) for the problem of classifying defects in plywood. …”
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    Enhanced Image Classification for Defect Detection on Solar Photovoltaic Modules by Wiliani, Ninuk

    Published 2023
    “…The second algorithm uses K Nearest Neighbour using a ratio of training data and testing data of 95:05 resulting in an accuracy value of 62%. …”
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  5. 5

    Training feedforward neural networks for fault diagnosis of ball bearing by Tuan Abdul Rahman, Tuan Ahmad Zahidi, As'arry, Azizan, Abdul Jalil, Nawal Aswan, Raja Ahmad, Raja Mohd Kamil

    Published 2018
    “…The results show that the proposed approach produces comparable classification accuracy as parameters of the FNNs were optimized systematically using CFS algorithm.…”
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  6. 6

    Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

    Published 2022
    “…All the algorithms were pretrained from ImageNet data-base before training with the wafer defect images. …”
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  7. 7

    Neural network paradigm for classification of defects on PCB by Heriansyah, Rudi, Syed Al-Attas, Syed Abdul Rahman, Zabidi, Muhammad Mun'im Ahmad

    Published 2003
    “…The algorithms to segment the image into basic primitive patterns, enclosing the primitive patterns, patterns assignment, patterns normalization, and classification have been developed based on binary morphological image processing and Learning Vector Quantization (LVQ) neural network. …”
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  8. 8

    A cascading fuzzy logic with image processing algorithm-based defect detection for automatic visual inspection of industrial cylindrical object’s surface by Ali, Mohammed A. H., Au, Kai Lun

    Published 2018
    “…This paper proposes a cascading fuzzy logic algorithm with image processing technique for defect detection and classification on the lateral surface of industrial cylindrical object using a camera and multiple flat mirrors. …”
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    Internal defect detection and reconstruction framework for laminated glass fibre reinforced polymer composite materials by Ng, Sok Choo

    Published 2013
    “…Therefore, by removmg the low frequency signals, the intemal defect detectability can be improved. Moreover, the classification of an input pattem based on the closest neighbours of the point of interest provides more accurate defect detection in comparison with the classification based on experience data as the defect pattems vary on circumstances in ultrasonic NDE problems.…”
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  13. 13

    Detection of tube defect using the autoregressive algorithm by Abd Halim, Zakiah, Jamaludin, Nordin, Junaidi, Syarif, Syed Yusainee, Syed Yahya

    Published 2015
    “…This study is aimed to automate defect detection using the pattern recognition approach based on the classification of high frequency stress wave signals. …”
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  14. 14

    Intelligent Thermal Condition Monitoring Of Electrical Equipment Using Infrared Thermography by Huda, A. S. Nazmul

    Published 2013
    “…In this thesis, an automatic features extraction system from thermal image of defects and the intelligent classification of thermal condition based on neural network are proposed. …”
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  15. 15

    Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin by Shamsuddin, Noraishah

    Published 2011
    “…This thesis presents a research work on a diagnosis system for heart sound based on nonlinear ARX (NARX) model. The system uses neural network for model estimation and classification of several heart diseases. …”
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  16. 16

    Identification of weld defect through the application of denoising method to the sound signal acquired during pulse mode laser welding by Yusof, M. F.M., Quazi, M. M., Aleem, S.A.A., Ishak, M., Ghazali, M. F.

    Published 2023
    “…This paper describes the improvement of weld defect identification achieved by incorporating Z-score-based thresholding into the wavelet denoising algorithm for the pre-processing of sound signals. …”
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    Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network by Vincent Chung, Norah Tuah, Kit Guan Lim, Min Keng Tan, Ismail Saad, Kenneth Tze Kin Teo

    Published 2020
    “…Based on the performance evaluation, GACS outperforms both Genetic Algorithm (GA)-based cluster optimization algorithm and Cuckoo Search (CS)-based multi-hop optimization algorithm.…”
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    An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning by Islam, Md Kamrul

    Published 2019
    “…BOCEDS clusters the data stream in a single stage. The algorithm summarizes the data from data stream in micro-clusters. …”
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    Clustering chemical data set using particle swarm optimization based algorithm by Triyono, Triyono

    Published 2008
    “…In this study, Particle Swarm Optimization (PSO) based clustering algorithm is exploited to optimize the results of other clustering algorithm such as K-means. …”
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