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  1. 1
    Identification of debris flow initiation zones using topographic model and airborne laser scanning data

    Identification of debris flow initiation zones using topographic model and airborne laser scanning data by Lay, Usman Salihu, Pradhan, Biswajeet

    Published 2017
    “…Conditioning parameters were numerically optimized to identify the arbitrarily maximum model basis function for eleven variables, using MARSplines analysis (algorithm). …”
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  2. 2
    Enhancing obfuscation technique for protecting source code against software reverse engineering

    Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

    Published 2019
    “…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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  3. 3
    LED based NIR spectroscopy for detection of lard adulteration in palm oil via chemometrics / Katrul Nadia Basri

    LED based NIR spectroscopy for detection of lard adulteration in palm oil via chemometrics / Katrul Nadia Basri by Basri, Katrul Nadia

    Published 2017
    “…Pure and adulterated palm oil sample were classified using soft independent modeling class analogy (SIMCA) algorithm with model accuracy more than 0.95 reported for both transflectance and transmission modes. …”
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  4. 4
    Classification and quantification of palm oil adulteration via portable NIR spectroscopy

    Classification and quantification of palm oil adulteration via portable NIR spectroscopy by Basri, Katrul Nadia, Hussain, Mutia Nurulhusna, Bakar, Jamilah, Sharif, Zaiton, Abdul Khir, Mohd Fared, Zoolfakar, Ahmad Sabirin

    Published 2017
    “…Pure and adulterated palm oil sample were classified using soft independent modeling class analogy (SIMCA) algorithm with model accuracy more than 0.95 reported for both transflectance and transmission modes. …”
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  5. 5
    Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN)

    Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN) by Khan T., Manan T.S.B., Isa M.H., Ghanim A.A.J., Beddu S., Jusoh H., Iqbal M.S., Ayele G.T., Jami M.S.

    Published 2023
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  6. 6
    Classification and quantification of palm oil adulteration via portable NIR spectroscopy

    Classification and quantification of palm oil adulteration via portable NIR spectroscopy by Basri, Katrul Nadia, Hussain, Mutia Nurulhusna, Bakar, Jamilah, Sharif, Zaiton and, Zoolfakar, Ahmad Sabirin, Mohd Fared Abdul Khir

    Published 2024
    “…Pure and adulterated palm oil sample were classified using soft independent modeling class analogy (SIMCA) algorithm with model accuracy more than 0.95 reported for both transflectance and transmission modes. …”
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  7. 7
    Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN)

    Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN) by Khan, T., Manan, T.S.B., Isa, M.H., Ghanim, A.A.J., Beddu, S., Jusoh, H., Iqbal, M.S., Ayele, G.T., Jami, M.S.

    Published 2020
    “…The Fletcher-Reeves conjugate gradient backpropagation (BP) algorithm was the best fit among all of the tested algorithms (mean squared error (MSE) of 3.84 and R2 of 0.989). …”
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  8. 8
    Automated detection and evaluation of ischemic stroke on ct brain imaging using machine learning techniques

    Automated detection and evaluation of ischemic stroke on ct brain imaging using machine learning techniques by Sharuddin, Nur Amirah Atikah

    Published 2025
    “…The Random Forest model achieved the highest accuracy at 92.76%, with an AUC of 0.973, outperforming both the KNN and SVM models. …”
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  9. 9
    Modeling of cu(ii) adsorption from an aqueous solution using an artificial neural network (ann)

    Modeling of cu(ii) adsorption from an aqueous solution using an artificial neural network (ann) by Khan, Taimur, Abd Manan, Teh Sabariah, Hasnain Isa, Mohamed, A. J. Ghanim, Abdulnoor, Beddu, Salmia, Jusoh, Hisyam, Iqbal, Muhammad Shahid, Ayele, Gebiaw T, Jami, Mohammed Saedi

    Published 2020
    “…The Fletcher–Reeves conjugate gradient backpropagation (BP) algorithm was the best fit among all of the tested algorithms (mean squared error (MSE) of 3.84 and R2 of 0.989). …”
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  10. 10
    Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail

    Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail by Sh. Ismail, Faridah

    Published 2015
    “…Back-propagation algorithm is a training method widely used in a multilayer perceptron Neural Network model. …”
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  11. 11
    Design & Development of a Robotic System Using LEGO Mindstorm

    Design & Development of a Robotic System Using LEGO Mindstorm by Abd Manap, Nurulfajar, Md Salim, Sani Irwan, Haron, Nor Zaidi

    Published 2006
    “…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. …”
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  12. 12
    Zero distortion-based steganography for handwritten signature

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

    Published 2018
    “…In this thesis, the human handwritten signature is introduced as a novel cover media (c) in conjunction with a steganography algorithm since there is a level of variability (i.e intra-user variability) within handwritten signature samples of an individual. …”
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  13. 13
    Production and characterization of biochar derived from oil palm wastes, and optimization for zinc adsorption

    Production and characterization of biochar derived from oil palm wastes, and optimization for zinc adsorption by Zamani, Seyed Ali

    Published 2015
    “…The incremental back propagation algorithm demonstrated the best results and which has been used as learning algorithm for ANN in combination with Genetic Algorithm in the optimization. …”
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  14. 14
    Machining characteristics of hastelloy c-2000 in end milling using artificial intelligence approach

    Machining characteristics of hastelloy c-2000 in end milling using artificial intelligence approach by Nurul Hidayah, Razak

    Published 2012
    “…Artificial Neural network (ANN) prediction model was developed with back propagation algorithm with the use of multilayer perceptron and activation function of hyperbolic tangent. …”
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