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  1. 1
    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…In addition, the hyperparameter tuning problem is considered in this research to improve the developed hybrid model by using the AOA algorithm. Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
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  2. 2
    The enhanced BPNN-NAR and BPNN-NARMA models for Malaysian aggregate cost indices with outlying data

    The enhanced BPNN-NAR and BPNN-NARMA models for Malaysian aggregate cost indices with outlying data by Ahmad Kamaruddin, Saadi, Md Ghani, Nor Azura, Mohamed Ramli, Norazan

    Published 2015
    “…In theory, the most common training algorithm for Backpropagation algorithms leans on reducing ordinary least squares estimator (OLS) or more specifically, the mean squared error (MSE). …”
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  3. 3
    A network aware based recommender system for VOIP application service in eLearning environment / Nazdiana Ab. Wahab

    A network aware based recommender system for VOIP application service in eLearning environment / Nazdiana Ab. Wahab by Ab. Wahab, Nazdiana

    Published 2009
    “…This paper showed the integration of VOIP in a simple eLearning prototype system. A network aware based algorithm is used to recommend users the best VOIP services available at that point of time (whether audio, video or data) based on the real time data obtained from bandwidth measurement tool. …”
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  4. 4
    Automated bilateral negotiation with incomplete information in the e-marketplace.

    Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

    Published 2011
    “…The MGT algorithm is useful to explore the properties of the Pareto-optimal offers. …”
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  5. 5
    Apply and optimize machine learning algorithms for estimating battery health

    Apply and optimize machine learning algorithms for estimating battery health by Chin, Wai Yee

    Published 2025
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  6. 6
    Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat

    Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat by Chia , Yu Huat

    Published 2024
    “…While 3D numerical analysis provides accurate SS estimates, it is time-consuming. To enhance prediction efficiency, validated numerical models serve as the foundation for data generation. …”
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  7. 7
    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer

    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

    Published 2021
    “…Multi-Verse Optimizer (MVO) is one of the most recent robust nature-inspired metaheuristic algorithm. It has been successfully implemented and used in various areas such as machine learning applications, engineering applications, network applications, parameter control, and other similar applications to solve optimization problems. …”
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  8. 8
    Mobile application for blood donation using geolocation and rule-based algorithm / Muhammad Firzan Azrai Nuzilan and Mohd Ali Mohd Isa

    Mobile application for blood donation using geolocation and rule-based algorithm / Muhammad Firzan Azrai Nuzilan and Mohd Ali Mohd Isa by Nuzilan, Muhammad Firzan Azrai, Mohd Isa, Mohd Ali

    Published 2021
    “…Besides, the rule-based algorithm is estimated to make the blood donation process goes efficiently by filtering the characteristic so that only suitable donor can donate the blood. …”
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  9. 9
    Predicting Diseases Using Multi-BackPropagation

    Predicting Diseases Using Multi-BackPropagation by Wan Hussain, Wan Ishak

    Published 2002
    “…However, learning usually involves a large amount of data. If more data is used, the network complexity will be increased. Complex network is hard to learn and take more time to generalize. …”
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  10. 10
    Deep Reinforcement Learning For Control

    Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

    Published 2021
    “…The complete project is carried out in the CARLA simulator to determine how to operate in discrete action space using Deep Reinforcement Learning (DRL) algorithms. …”
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  11. 11
    Enhancing the QoS performance for mobile station over LTE and WiMAX networks / Mhd Nour Hindia

    Enhancing the QoS performance for mobile station over LTE and WiMAX networks / Mhd Nour Hindia by Hindia, Mhd Nour

    Published 2015
    “…The selection is based on the user preferences since it uses a self-learning algorithm to determine triggers and handover thresholds dynamically. …”
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  12. 12
    Density subspace clustering: a case study on perception of the required skill

    Density subspace clustering: a case study on perception of the required skill by Sembiring, Rahmat Widia

    Published 2014
    “…In the early stage, the present research estimates density dimensions and the results are used as input data to determine the initial cluster based on density connection, using DBSCAN algorithm. …”
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  13. 13
    State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model

    State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model by Dickson Neoh Tze How, Dr.

    Published 2023
    “…In the first stage, the model is pre-trained using unlabeled data with unsupervised learning. …”
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  14. 14
    Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions

    Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Al-Garadi, Mohammed Ali

    Published 2019
    “…These sensors are pre-processed and different feature sets such as time domain, frequency domain, wavelet transform are extracted and transform using machine learning algorithm for human activity classification and monitoring. …”
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  15. 15
    Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration

    Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration by Chia, Min Yan

    Published 2022
    “…As for the NNE, a novel meta-learner based on the stochastic-enabled extreme learning machine integrated with whale optimisation algorithm (WOA-ELM) was developed and used in such an application for the first time. …”
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  16. 16
    Applications of Data-driven Models for Daily Discharge Estimation Based on Different Input Combinations

    Applications of Data-driven Models for Daily Discharge Estimation Based on Different Input Combinations by Kumar M., Elbeltagi A., Pande C.B., Ahmed A.N., Chow M.F., Pham Q.B., Kumari A., Kumar D.

    Published 2023
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  17. 17
    EstiCal: food calorie image recognition mobile application by using feature descriptor technique / Muhammad Asyraf Suhaimi

    EstiCal: food calorie image recognition mobile application by using feature descriptor technique / Muhammad Asyraf Suhaimi by Suhaimi, Muhammad Asyraf

    Published 2018
    “…However, lack of automation in the application makes user taking too much time in manually record the data causes them to lose interest and does not want to use the application. …”
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  18. 18
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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  19. 19
    Development of predictive modeling and deep learning classification of taxi trip tolls

    Development of predictive modeling and deep learning classification of taxi trip tolls by Al-Shoukry, Suhad, M. Jawad, Bushra Jaber, Zalili, Musa, Sabry, Ahmad H.

    Published 2022
    “…Using a classification algorithm, it is possible to extract drop-off and pickup locations from taxi trip data and estimate if the tour would incur tolls. …”
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  20. 20
    Prediction Of Petroleum Reservoir Properties Using Nonlinear Feature Selection And Ensembles Of Computational Intelligence Techniques

    Prediction Of Petroleum Reservoir Properties Using Nonlinear Feature Selection And Ensembles Of Computational Intelligence Techniques by Anifowose, Fatai Adesina

    Published 2015
    “…The recent use of advanced and sophisticated data acquisition tools has led to a data explosion accompanied by very high dimensional data and increased uncertainties. …”
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