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  1. 1
    Extreme learning machine model for state-of-charge estimation of lithium-ion battery using gravitational search algorithm

    Extreme learning machine model for state-of-charge estimation of lithium-ion battery using gravitational search algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Saad M.H., Ayob A., Uddin M.N.

    Published 2023
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  2. 2
    Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm

    Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Rahman S.A., Saad M.H.M., Muttaqi K.M.

    Published 2024
    “…This paper presents an improved machine learning approach for the accurate and robust state of charge (SOC) in electric vehicle (EV) batteries using differential search optimized random forest regression (RFR) algorithm. …”
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  3. 3
    Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS

    Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Jaafar, Jafreezal

    Published 2017
    “…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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  4. 4
    Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries

    Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Ayob A., Saad M.H.M., Muttaqi K.M.

    Published 2023
    Conference Paper
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  5. 5
    Thematic textual hadith classification: an experiment in rapidminer using support vector machine (SVM) and naïve bayes algorithm

    Thematic textual hadith classification: an experiment in rapidminer using support vector machine (SVM) and naïve bayes algorithm by Yusof, Norzihani, Rosidi, Siti Aishah Rosidi, Ibrahim, Nuzulha Khilwani Ibrahim, Ahmed Ali, Ahmed El-Mogtaba Bannga

    Published 2020
    “…However, in this paper, we are not concentrating on the such learning of estimating, confirming or authenticating a Hadith. …”
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  6. 6
    Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm

    Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm by Lipu M.S.H., Hannan M.A., Hussain A., Saad M.H.M., Ayob A., Muttaqi K.M.

    Published 2023
    Conference Paper
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  7. 7
    State of Charge Estimation for Lithium-Ion Battery Using Recurrent NARX Neural Network Model Based Lighting Search Algorithm

    State of Charge Estimation for Lithium-Ion Battery Using Recurrent NARX Neural Network Model Based Lighting Search Algorithm by Lipu M.S.H., Hannan M.A., Hussain A., Saad M.H.M., Ayob A., Blaabjerg F.

    Published 2023
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  8. 8
    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 reason is that, SRT algorithm is sensitive to the accuracy of the learned preferences while MGT algorithm can generate Pareto-optimal offers even with an approximation of the learned preferences.…”
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  9. 9
    Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS

    Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

    Published 2017
    “…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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  10. 10
    Bayesian Network of Traffic Accidents in Malaysia

    Bayesian Network of Traffic Accidents in Malaysia by Zamzuri, Zamira Hasanah, Shabadin, Akmalia, Ishak, Siti Zaharah

    Published 2019
    “…By using Hill Climb (HC) and Tabu algorithms, the structure of the data was learnt and their relationship is estimated through the conditional probability based on the Bayes theorem. …”
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  11. 11
    An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction

    An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction by Ahanin, Fatemeh

    Published 2023
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  12. 12
    A resource-aware content adaptation approach for e-learning environment / Mohd Faisal Ibrahim

    A resource-aware content adaptation approach for e-learning environment / Mohd Faisal Ibrahim by Ibrahim, Mohd Faisal

    Published 2017
    “…The results showed that the decision algorithm improves the measurement by 28% and the degraded transcoded video does not affect students' comprehension.…”
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  13. 13
    Predicting Diseases Using Multi-BackPropagation

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

    Published 2002
    “…Multi-network approach does not require any changes in neural network learning algorithm. …”
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  14. 14
    A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal

    A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal by Aymen Taher , Ahmed al-Ashwal

    Published 2019
    “…Lastly, the incremental learning algorithm ABACOC is used to classify each feature of food classes. …”
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  15. 15
    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…Finally, one key drawback of estimating streamflow outlined above is that it does not account for variability. …”
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  16. 16
    A direct ensemble classifier for learning imbalanced multiclass data

    A direct ensemble classifier for learning imbalanced multiclass data by Samry @ Mohd Shamrie Sainin

    Published 2013
    “…The learning framework consists of ensemble learning and decision combiner model with general supervised learning algorithms as base learner. …”
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  17. 17
    Super resolution imaging using modified lanr based on separable filtering

    Super resolution imaging using modified lanr based on separable filtering by Somadina, Ike Chidiebere

    Published 2019
    “…In this research, the long-established single-image super-resolution problem is addressed by integrating the multiresolution property of Wavelet and the flexibility of Locally Anchored Neighbourhood Regression model to formulate a novel edgebased single image super resolution algorithm that allows robust estimation of missing frequency details in wavelet domain with complete enhancement procedure. …”
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  18. 18
    Application of boundary-fitted convolutional neural network to simulate non-Newtonian fluid flow behavior in eccentric annulus

    Application of boundary-fitted convolutional neural network to simulate non-Newtonian fluid flow behavior in eccentric annulus by Kumar, A., Ridha, S., Ilyas, S.U., Dzulkarnain, I., Pratama, A.

    Published 2022
    “…The performance of the algorithm is validated with experimental data available from published studies. …”
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  19. 19
    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
    “…The future work of the project can be done with additional features such as using a hybrid algorithm which is combining algorithms to improvise the feature descriptor or applying a machine learning technique to increase the efficiency of food recognition.…”
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  20. 20
    Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data

    Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data by Sleabi, Waleed Dhhan

    Published 2016
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