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  1. 1
    Deterministic Image Enhancement Based on Fuzzy Method

    Deterministic Image Enhancement Based on Fuzzy Method by Libao Yang, Suzelawati Zenian, Rozaimi Zakaria

    Published 2022
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  2. 2
    Model selection approaches of water quality index data

    Model selection approaches of water quality index data by Kamarudin, Nur Azulia, Ismail, Suzilah

    Published 2016
    “…Automatic model selection by using algorithm can avoid huge variability in model specification process compared to manual selection.With the employment of algorithm, the right model selected is then also used for forecasting purposes. …”
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  3. 3
    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network

    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…Based on the results obtained, a better prediction result can be produced by the proposed GA-BPNN learning algorithm.…”
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  4. 4
    Information Theoretic-based Feature Selection for Machine Learning

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…Thus, this thesis has developed and evaluated a filter based Information Theoretic-based Feature Selection (IFS) for machine learning. …”
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  5. 5
    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis

    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

    Published 2019
    “…Furthermore, a systematic feature selection approach was proposed in which search algorithms (Ant-Search, Best First-Search and Particle Swamp Optimization (PSO) - Search) performance were evaluated to select the most significant features. …”
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  6. 6
    Extremal region detection and selection with fuzzy encoding for food recognition

    Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

    Published 2019
    “…The second algorithm reduces the quantity of interest regions by using the Extremal Region Selection (ERS) algorithm. …”
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  7. 7
    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification

    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

    Published 2020
    “…The results indicated that good classification performance depends on these factors. All algorithms showed more stability and accuracy when training size applied is more than 6% by the Equal Sample Rate (ESR) method with six variables. …”
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  8. 8
    Evaluation of lightning return stroke current using measured electromagnetic fields

    Evaluation of lightning return stroke current using measured electromagnetic fields by Mahdi, Izadi

    Published 2012
    “…However, the improvement of Deindorfer and Uman on the Heidler function with an unknown variable is selected as the general channel base current function. …”
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  9. 9
    Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak

    Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak by Emily Sing Kiang, Siew

    Published 2025
    “…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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  10. 10
    Neural network based adaptive pid controller for shell-and-tube heat exchanger

    Neural network based adaptive pid controller for shell-and-tube heat exchanger by Othman, Mohamad Hakimi

    Published 2019
    “…Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. Single hidden layer feed forward neural networks with 20 neurons in hidden layer was selected. …”
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  11. 11
    Neural network based adaptive pid controller for shell-and-tube heat exchanger: article

    Neural network based adaptive pid controller for shell-and-tube heat exchanger: article by Othman, Mohamad Hakimi

    Published 2019
    “…Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. Single hidden layer feed forward neural networks with 20 neurons in hidden layer was selected. …”
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  12. 12
    Modelling monthly pan evaporation utilising Random Forest and deep learning algorithms

    Modelling monthly pan evaporation utilising Random Forest and deep learning algorithms by Abed M., Imteaz M.A., Ahmed A.N., Huang Y.F.

    Published 2023
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  13. 13
    Perturbation stochastic model updating of a bolted structure / Mohamad Azam Shah Aziz Shah

    Perturbation stochastic model updating of a bolted structure / Mohamad Azam Shah Aziz Shah by Aziz Shah, Mohamad Azam Shah

    Published 2022
    “…The SMU method based on the improved model was used to predict the variability of the dynamic behaviour of the structure. …”
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  14. 14
    The use of heuristic ordering and particle swarm optimization for nurse scheduling problem

    The use of heuristic ordering and particle swarm optimization for nurse scheduling problem by Mohd Rasip, Norhayati

    Published 2017
    “…The comparison of the result of HOPSO, harmony search algorithm (HSA) and heuristic variable neighborhood search (HVNS) is presented. …”
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  15. 15
    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani

    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

    Published 2018
    “…To evaluate the performance of the Weibull parameters’ estimator methods, two sets of data are considered, one based on simulated data with different random variable size and the other based on actual data collected from a wind farm in Iran. …”
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  16. 16
    Model Prediction Of Pm2.5 And Pm10 Using Machine Learning Approach

    Model Prediction Of Pm2.5 And Pm10 Using Machine Learning Approach by Hamid, Norfarhanah

    Published 2021
    “…Based on the feature selection, model development was built with and without input selection using the Nonlinear Autoregressive with Exogeneous Input (NARX) neural network model which made use of 10 number of hidden neurons and 2 number of delays, implementing Levenberg-Marquardt as training algorithm. …”
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  17. 17
    Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis

    Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis by Adnani, Seyedeh Atena

    Published 2011
    “…The synthetic reaction was optimized by Taguchi method based on orthogonal array to evaluate the effect of each parameters and interactive effects of reaction parameters including temperature, time, amount of enzyme, amount of molecular sieve, amount of solvent, and molar ratio of substrates (xylitol: fatty acid). …”
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  18. 18
    SWAT and ANN model hydrological assessment using Malaysia soil data / Khairi Khalid

    SWAT and ANN model hydrological assessment using Malaysia soil data / Khairi Khalid by Khalid, Khairi

    Published 2017
    “…The evolution of distributed watershed models has been established for more accurate representation of the hydrological system by considering the spatial variability of model parameters and inputs. The research aims to evaluate the performance and hydrological response of the Soil Water Assessment Tool (SWAT) process-based model in tropical river basin using Malaysia soil data. …”
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  19. 19
    Shear strength test on unsaturated soil using natural microscopic surface tension force / Basharudin Abdul Hadi

    Shear strength test on unsaturated soil using natural microscopic surface tension force / Basharudin Abdul Hadi by Abdul Hadi, Basharudin

    Published 2017
    “…There were two sets of algorithms in developing the UPLRB ANN model and every algorithm set consisted of model inputs data preparation, neural network 29 30 base of the specimen until the flow ceased..…”
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  20. 20
    Cryptanalysis on the modulus N=p2q and design of rabin-like cryptosystem without decryption failure

    Cryptanalysis on the modulus N=p2q and design of rabin-like cryptosystem without decryption failure by Asbullah, Muhammad Asyraf

    Published 2015
    “…In this thesis, we also develop a new cryptographic hard problem based on a special instance of a linear Diophantine equation in two variables, with some provided restrictions and carefully selected parameters. …”
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