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  1. 1

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Besides, some real data sets were examined to validate the proposed algorithm. Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
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  2. 2

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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  3. 3

    An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion by Haque, Ariful

    Published 2018
    “…To generate test cases that satisfy MC/DC criterion, many researchers adopt neighborhood based meta-heuristics algorithms (including that of Simulated Annealing and Hill Climbing) as the problem itself is neighborhood based. …”
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  4. 4

    Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment by Kalaf, Kalaf, Bayda Atiya

    Published 2017
    “…During the course of the present work, two fuzzy methods (modified Zimmermanns approach and modified angelovs approach ) and fourmeta-heuristics and hybrid meta heuristics including; simulated annealing (SA), modified simulated annealing (MSA), hybrid modified simulated annealing and simplex downhill (MSASD), hybrid modified simulated annealing and modified particle swarm optimization (MSAPSO) were proposed. …”
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  5. 5
  6. 6

    Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

    Published 2024
    “…The IWD is a recent metaheuristic population-based algorithm belonging to the swarm intelligent category which simulates the dynamic of the river systems. …”
    thesis::doctoral thesis
  7. 7

    Use of AR Block Processing for Estimating the State Variables of Power System by Mohd Nor, Nursyarizal, Jegatheesan, Ramiah, Perumal, Nallagownden

    Published 2008
    “…Samples of the local utility network for 103-bus parameter are collected and simulated using Burg and Modified Covariance algorithm to estimate the state variables. …”
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  8. 8

    Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques by Hammid, Ali Thaeer

    Published 2018
    “…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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  9. 9

    Solving optimal power flow problem with stochastic wind–solar–small hydro power using barnacles mating optimizer by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2021
    “…Statistical studies are performed to show the feasible and effectiveness of BMO compared with other selected metaheuristic algorithms. Based on the obtained results, the BMO has shown the best results for all cases of simulation study. …”
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    Article
  10. 10

    Green retrofitting of building using BIM-based sustainability optimization by Shizra Mughal, Ali Raza Khoso, Haris Najeeb, Muhammad Sufyan Noor Khan, Tauha Hussain Ali, Shabir Hussain Khahro

    Published 2024
    “…This research aims to reform the existing building by modifying the design parameters for an inefficient building envelope based on BIM simulation and data optimization results to optimize the overall energy consumption. …”
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  11. 11

    Green retrofitting of building using BIM-based sustainability optimization by Shizra Mughal, Ali Raza Khoso, Haris Najeeb, Muhammad Sufyan Noor Khan, Tauha Hussain Ali, Shabir Hussain Khahro

    Published 2024
    “…This research aims to reform the existing building by modifying the design parameters for an inefficient building envelope based on BIM simulation and data optimization results to optimize the overall energy consumption. …”
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  12. 12

    Robust correlation feature selection based support vector machine approach for high dimensional datasets by Baba, Ishaq Abdullahi, Mohammed, Mohammed Bappah, Jillahi, Kamal Bakari, Umar, Aliyu, Hendi, Hasan Talib

    Published 2025
    “…The second step utilizes the estimates of weights from the first step to select the most important variables for the model. The third step employs the support vector machine algorithm to calculate prediction values. …”
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  13. 13

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

    Published 2018
    “…The second test evaluates IFS in a controlled study using simulated datasets. Moreover, the third test used ten natural domain datasets obtained from UCI Repository, in about fifteen different experiments, using three to four different Machine Learning Algorithms for performance evaluation. …”
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  14. 14

    Dynamic two phase modelling and anfis-based control of ethylene copolymerization in catalytic Fluidized Bed Reactor / Mohammad Reza Abbasi by Mohammad Reza , Abbasi

    Published 2019
    “…The results showed that the dynamic model predicts more accurate results for Polydispersity Index (PDI), Molecular Weight Distribution (MWD), reactor temperature and polymer production rate. The open loop simulation analysis revealed that the behavior of the polyethylene fluidized bed reactor is strongly dependent on the superficial gas velocity and feed concentrations and that the process is highly sensitive and nonlinear, thus justifying the use of an advanced control algorithm for efficient control of the process variables. …”
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  15. 15

    Comparative modelling of strength properties of hydrated-lime activated rice husk-ash (HARHA) modified soft soil for pavement construction purposes by artificial neural network (AN... by Onyelowe, K. C., Alaneme, G. U., Onyia, M. E., Bui Van, D., Dimonyeka, M. U., Nnadi, E., Ogbonna, C., Odum, L. O., Aju, D. E., Abel, C., Udousoro, I. M., Onukwugha, E.

    Published 2021
    “…For the ANN model, feed forward back propagation and Levernberg Marquardt training algorithm were utilized for the model development with the optimized network architecture of 8-6-3 derived based on MSE performance criteria; while for the fuzzy logic model, the mamdani FIS with both triangular and trapezoidal membership function with both models formulated, simulated and computed using MATLAB toolbox. …”
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  16. 16

    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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  17. 17

    Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems by Tan, Joe Yee

    Published 2022
    “…In this case, the effectiveness and reliability of RMS is increase by combining the simulation with the optimization algorithm.…”
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  18. 18

    Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm by Zuwairie, Ibrahim, Nor Hidayati, Abd Aziz, Nor Azlina, Ab. Aziz, Saifudin, Razali, Mohd Saberi, Mohamad

    Published 2016
    “…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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  19. 19

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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  20. 20

    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

    Published 2022
    “…The performance of the proposed method is illustrated using simulation study and on glass vessel data with 1920 variables, cardiomyopathy microarray data with 6319 variables, and octane data with 226 dimensions. …”
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