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  1. 1
    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm

    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm by Dalatu, Paul Inuwa

    Published 2018
    “…We introduced two new approaches to normalization techniques to enhance the K-Means algorithms. …”
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  2. 2
    Logic Programming In Radial Basis Function Neural Networks

    Logic Programming In Radial Basis Function Neural Networks by Hamadneh, Nawaf

    Published 2013
    “…I used different types of optimization algorithms to improve the performance of the neural networks. …”
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  3. 3
    A new method for intermediate power point tracking for PV generator under partially shaded conditions in hybrid system

    A new method for intermediate power point tracking for PV generator under partially shaded conditions in hybrid system by Guichi, Amar, Talha, Abdelaziz, Berkouk, El Madjid, Mekhilef, Saad, Gassab, Samir

    Published 2018
    “…This technique is based on the combination of two algorithms, the particle swarm optimization algorithm for tracking the global maximum power point, while a newly developed algorithm is used for attaining any other supervisory control set point. …”
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  4. 4
    Weather prediction in Kota Kinabalu using linear regressions with multiple variables

    Weather prediction in Kota Kinabalu using linear regressions with multiple variables by Teong, Khan Vun, Chung, Gwo Chin, Jedol Dayou

    Published 2021
    “…The root mean square error is used to compare the performance of the algorithms. …”
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    Proceedings
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  5. 5
    Classification red blood cells using support vector machine

    Classification red blood cells using support vector machine by Akrimi J.A., Suliman A., George L.E., Ahmad A.R.

    Published 2023
    Conference Paper
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  6. 6
    Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks

    Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks by Mujahid Tabassum

    Published 2024
    thesis::doctoral thesis
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  7. 7
    Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions

    Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions by Shamshad, H., Ullah, F., Ullah, A., Kebande, V.R., Ullah, S., Al-Dhaqm, A.

    Published 2023
    “…For the model validation, we utilize widely used evaluation techniques: Mean Absolute Error, Root Mean Squared Error, Mean Absolute Percentage Error, and R-squared. …”
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  8. 8
    Production quantity estimation using an improved artificial neural network

    Production quantity estimation using an improved artificial neural network by Dzakiyullah, Raden Nur Rachman

    Published 2015
    “…These techniques were used to optimize attribute weighting on NNBP model. …”
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  9. 9
    Entropy in portfolio optimization / Yasaman Izadparast Shirazi

    Entropy in portfolio optimization / Yasaman Izadparast Shirazi by Yasaman Izadparast, Shirazi

    Published 2017
    “…The usefulness of this technique has been verified with Monte-Carlo simulation in the context of portfolio analysis. …”
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  10. 10
    A Comparative Study of Z-Score and Min-Max Normalization for Rainfall Classification in Pekanbaru

    A Comparative Study of Z-Score and Min-Max Normalization for Rainfall Classification in Pekanbaru by Rahmad Ramadhan, Laska, Anne Mudya, Yolanda

    Published 2024
    “…The findings demonstrate that applying normalization techniques effectively enhances classification performance compared to using unnormalized data. …”
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  11. 11
    A selective approach for energy-aware video content adaptation decision-taking engine in android based smartphone

    A selective approach for energy-aware video content adaptation decision-taking engine in android based smartphone by Ismail, Mohd Norasri

    Published 2019
    “…The EnVADE algorithm uses selective mechanism. Selective mechanism means the video segmented into scenes and adaptation process is done based on the selected scenes. …”
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  12. 12
    A selective approach for energy-aware video content adaptation decision-taking engine in android based smartphone

    A selective approach for energy-aware video content adaptation decision-taking engine in android based smartphone by Abd Rahim, Mohd Hilmi Izwan

    Published 2019
    “…The EnVADE algorithm uses selective mechanism. Selective mechanism means the video segmented into scenes and adaptation process is done based on the selected scenes. …”
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  13. 13
    Characterization of oil palm fruitlets using artificial neural network

    Characterization of oil palm fruitlets using artificial neural network by Olukayode, Ojo Adedayo

    Published 2014
    “…The training data for the models were obtained from dielectric and moisture content measurements and the obtained data were fitted into the quasi-static wave Equations and optimized using MATLAB complex root finding technique to obtain the normalized conductance, susceptance and the complex permittivity of the fruitlets. …”
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  14. 14
    Mean of correlation method for optimization of affective states detection in children

    Mean of correlation method for optimization of affective states detection in children by Rusli, Nazreen, Sidek, Shahrul Na'im, Md Yusuf, Hazlina, Ishak, Nor Izzati

    Published 2018
    “…This paper proposes an effective algorithm of texture analysis based on novel technique using Gray Level Co-occurrence Matrix approach to be applied so as to identify blood-flow region. …”
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  15. 15
    A Simulated Kalman Filter (SKF) approach in identifying optimum speed during cornering

    A Simulated Kalman Filter (SKF) approach in identifying optimum speed during cornering by Kamil Zakwan, Mohd Azmi, Nurul Afiqah, Zainal, Muhammad Aizzat, Zakaria, Anwar, P. P. Abdul Majeed

    Published 2021
    “…The algorithm is used to minimize the normal forces experienced by the driver based on the identified speed. …”
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  16. 16
    Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli

    Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

    Published 2014
    “…Neural network is an efficient tool for forecasting financial time series as well as many other areas and has shown a great success, outperforming other forecasting techniques. The backpropagation algorithm is one of the most famous algorithms to train neural network based on the mean square error (MSE) of ordinary least squares (OLS). …”
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  17. 17
    Performance comparison of GA and PSO based ANN training on medical dataset / Muhammad Amirul Danish Jamal

    Performance comparison of GA and PSO based ANN training on medical dataset / Muhammad Amirul Danish Jamal by Jamal, Muhammad Amirul Danish

    Published 2025
    “…Data preprocessing was carried out using min-max normalization, and an ANN architecture featuring 20 hidden neurons was created and optimized with MATLAB. …”
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  18. 18
    Automated calibration of baseline model for energy conservation using multi-objective Evolutionary Programming (EP) / Ahmad Amiruddin Mohammad Aris

    Automated calibration of baseline model for energy conservation using multi-objective Evolutionary Programming (EP) / Ahmad Amiruddin Mohammad Aris by Mohammad Aris, Ahmad Amiruddin

    Published 2019
    “…To evaluate the accuracy of building energy model, hourly criteria for Normalized Mean Biased Error (NMBE) and Coefficient of Variance Root Mean Squared Error (CV(RMSE)) as proposed by the IPMVP are used. …”
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  19. 19
    Ensemble deep learning approach for apple fruitlet detection from digital images

    Ensemble deep learning approach for apple fruitlet detection from digital images by Yusof, Mohamad Yusnisyahmi, Ishak, Iskandar, Sidi, Fatimah

    Published 2024
    “…The combination of activation function, optimization, batch normalization, and ensemble technique are later used to enhance the YOLOv5 ensemble model with the benefits of utilizing limited resources. …”
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  20. 20
    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
    “…An intelligent predictive model will replace the lengthy procedures by predicting the properties using known fiberboard characteristics. Back-propagation algorithm is a training method widely used in a multilayer perceptron Neural Network model. …”
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