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  1. 1
    Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC)

    Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC) by Ibrahim, Kamarul 'Asri, Ahmad, Arshad, Ali, Mohamad Wijayanuddin, Mak, Weng Yee

    Published 2006
    “…In this research work, an FDD algorithm is developed using MSPC and correlation coefficients between process variables. …”
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  2. 2
    Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV

    Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV by Sirunyan, A. M., Tumasyan, A. R., Adam, Wolfgang, Ambrogi, Federico, Asilar, Ece, Md. Ali, Mohd. Adli

    Published 2018
    “…In this paper, the discriminating variables and the algorithms used for heavy-flavour jet identification during the first years of operation of the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV, are presented. …”
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  3. 3
    Modeling of flood water level prediction using NNARX / Fazlina Ahmat Ruslan

    Modeling of flood water level prediction using NNARX / Fazlina Ahmat Ruslan by Ahmat Ruslan, Fazlina

    Published 2015
    “…Comparison results have shown that the pre-screening method has an essential role in determining an effective process representation especially in real-time multivariable identification framework where a priori knowledge is not available and would help in resultant model generalization performance as opposed to simply using all available model input variables. …”
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  4. 4
    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING

    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    Published 2017
    “…The correlation analysis is used for the identification and selection of the most influential input variable vector (IVV). …”
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  5. 5
    Model input and structure selection in multivariable dynamic modeling of batch distillation column pilot plant / Ilham Rustam

    Model input and structure selection in multivariable dynamic modeling of batch distillation column pilot plant / Ilham Rustam by Rustam, Ilham

    Published 2015
    “…Comparison results have shown that the pre-screening method has an essential role in determining an effective process representation especially in real-time multivariable identification framework where a priori knowledge is not available and would help in resultant model generalization performance as opposed to simply using all available model input variables. …”
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  6. 6
    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi

    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi by Dejamkhooy, Abdolmajid, Asefi, Sajjad

    Published 2018
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  7. 7
    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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  8. 8
    Fault detection and diagnosis using rule-based support system on fatty acid fractionation column

    Fault detection and diagnosis using rule-based support system on fatty acid fractionation column by Yann, H. H., Ali, Mohamad Wijayanuddin, Kamsah, Mohd Zaki

    Published 2003
    “…Identification of causes, consequences and suggested actions for each deviation assisted by Hazard and Operability Study (HAZOP) analysis are generated into rule-based algorithm. …”
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  9. 9
    A PLC-based Hybrid Fuzzy PID Controller for PWM-driven Variable Speed Drive

    A PLC-based Hybrid Fuzzy PID Controller for PWM-driven Variable Speed Drive by ARROFIQ, MUHAMMAD

    Published 2010
    “…A simulation model in MA TLAB/Simulink is developed using system identification technique to perform verification of the PLCbased intelligent controller of the PWM-driven VVVF algorithm. …”
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  10. 10
    Feature Ranking Techniques For 3D ATS Drug Molecular Structure Identification

    Feature Ranking Techniques For 3D ATS Drug Molecular Structure Identification by Saw, Yee Ching

    Published 2018
    “…Existing laboratory analysis techniques of ATS drug identification have their challenges which include the cost of training expert operators, the cost of acquired materials, and the dangers involved in operating the experiments. …”
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  11. 11
    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
    “…MARSpline multivariate data mining predictive approach was implemented using morphometric indices and topographical derived parameter as independent variables. …”
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  12. 12
    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy

    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  13. 13
    Oil palm female inflorescences anthesis stages identification using selected emissivities through thermal imaging and Machine Learning

    Oil palm female inflorescences anthesis stages identification using selected emissivities through thermal imaging and Machine Learning by Yousefidashliboroun, Mamehgol

    Published 2022
    “…This research studies different Machine Learning (ML) classification and ensemble techniques for the assessment of the four pollination stages consist of pre-anthesis I, pre-anthesis II, pre-anthesis III, and anthesis using thermal imaging. Different ML algorithms such as Random Forest (RF), k Nearest Neighbor (kNN), Support Vector Machine (SVM), Artificial Neural Network (ANN) as well as an ensemble method are used on data extracted from thermal images collected during infield oil palms pollination stages monitoring. …”
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  14. 14
    Hospital site suitability assessment using three machine learning approaches: evidence from the Gaza strip in Palestine

    Hospital site suitability assessment using three machine learning approaches: evidence from the Gaza strip in Palestine by Almansi, Khaled Yousef, Mohamed Shariff, Abdul Rashid, Abdullah, Ahmad Fikri, Syed Ismail, Sharifah Norkhadijah

    Published 2021
    “…The results of the predicted sites were validated using CFS cross-validation and the receiver operating characteristic (ROC) curve metrics. …”
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  15. 15
    Embedded mini-analyzer device for in situ wide range heavy metal identification and concentration detection

    Embedded mini-analyzer device for in situ wide range heavy metal identification and concentration detection by Mazaheri, Amin

    Published 2018
    “…Voltammetry as electrochemical technique is used in this project for the heavy metals detection. …”
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  16. 16
    Faulty sensor detection mechanism using multi-variate sensors in IoT

    Faulty sensor detection mechanism using multi-variate sensors in IoT by Al-Atrakchii, Khaldoon Ammar

    Published 2019
    “…The first proposed method is a logical mechanism uses three different types of. The second method proposed is based on a correlation method that can exploit the multi-variable sensor which existing in IoT application. …”
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  17. 17
    Multi-objective Sustainability Assessment of Levulinic Acid Production from Empty Fruit Bunch

    Multi-objective Sustainability Assessment of Levulinic Acid Production from Empty Fruit Bunch by Hafyan, R.H., Bhullar, L., Putra, Z.A., Bilad, M.R., Wirzal, M.D.H., Nordin, N.A.H.M.

    Published 2020
    “…These conflicting objectives were solved using multi-objective optimization. Genetic algorithm (GA) was conducted in MATLAB to generate a Pareto-optimal front. …”
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  18. 18
    Using Metaheuristics Algorithms (MHAs) to Optimize Water Supply Operation in Reservoirs: a Review

    Using Metaheuristics Algorithms (MHAs) to Optimize Water Supply Operation in Reservoirs: a Review by Almubaidin M.A.A., Ahmed A.N., Sidek L.B.M., Elshafie A.

    Published 2023
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  19. 19
    Reduced torque ripple and switching frequency using optimal DTC switching strategy for open-end winding induction machines

    Reduced torque ripple and switching frequency using optimal DTC switching strategy for open-end winding induction machines by Abd Rahim, Muhd Khairi

    Published 2017
    “…The main benefit of the proposed strategy is its simplicity, where the DTC improvements can be obtained without the common approach, i.e. the use of Space Vector Modulation (SVM) which involves complex control algorithms. …”
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  20. 20
    Variable Global Optimization min-sum (VGOMS) algorithm of decode-and forward-protocol for the relay node in the cooperative channel

    Variable Global Optimization min-sum (VGOMS) algorithm of decode-and forward-protocol for the relay node in the cooperative channel by Hushairi, Zen, Al-Khalid, Hj Othman, Khairuddin, Abdul Hamid, Jamaah, Suut

    Published 2020
    “…The proposed VGOMS algorithm apply the optimization scaling factor at the bit node processing of the variable node operation which have significantly less complexity as compared with the check node operation or both variable node and check node operation. …”
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