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  1. 1
    Optimized clustering with modified K-means algorithm

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

    Published 2021
    “…Clustering technique is able to find hidden patterns and to extract useful information from huge data. Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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  2. 2
    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
    Review
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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

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

    Published 2018
    “…We have chosen four neighborhood based algorithms which are commonly used in optimization problems and divided them in newly implemented and re-implemented category. …”
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  4. 4
    Simulation Of Token Bucket Algorithm For Network Traffic Performance

    Simulation Of Token Bucket Algorithm For Network Traffic Performance by Yusof, Robiah, Mat Nawi, Nor Afifah

    Published 2020
    “…In this research, the optimal size of bucket in Token Bucket Algorithm(TBA)is used as one of the techniques in traffic shaping. …”
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  5. 5
    Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems

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

    Published 2024
    “…The solution’s construction is modified using the concept of global best operator that is used in the Particle Swarm Optimization (PSO). …”
    thesis::doctoral thesis
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  6. 6
    An application of improved salp swarm algorithm for optimal power flow solution considering stochastic solar power generation

    An application of improved salp swarm algorithm for optimal power flow solution considering stochastic solar power generation by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2023
    “…This paper describes the use of an improved version of the Salp Swarm Algorithm, known as iSSA, to address Optimal Power Flow (OPF) issues in power system management. …”
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  7. 7
    Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi

    Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi by Seyed Mohsen , Mousavi

    Published 2018
    “…A Modified Particle Swarm Optimization (MPSO) algorithm, a Genetic Algorithm (GA), a modified fruit fly optimization algorithm (MFOA) and a simulated annealing (SA) algorithm were used to find the optimal solution. …”
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  8. 8
    Power quality improvement in distribution systems considering Optimum D-STATCOM placement

    Power quality improvement in distribution systems considering Optimum D-STATCOM placement by Farhoodnea, Masoud, Azah Mohamed, Hussain Shareef, Zayandehroodi, Hadi

    Published 2013
    “…The voltage and power limits for individual buses are considered as the constraints to control optimization variables. The proposed FA is implemented using the Matlab software on modified IEEE 16- and 34-bus test systems. …”
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  9. 9
    Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques

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

    Published 2018
    “…Secondly, this approach hybridizing the FA with the rough algorithm (RA), where RA is used to control the steps of randomness for the FA while optimizing the weights of the standard BPNN model. …”
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  10. 10
    Solving the optimal power flow problems using the superiority of feasible solutions-moth flame optimizer

    Solving the optimal power flow problems using the superiority of feasible solutions-moth flame optimizer by Alam, Mohammad Khurshed

    Published 2024
    “…The main goal of this study is to use a cuttingedge version of recent metaheuristic algorithm, namely Moth-Flame Optimizer (MFO) algorithm for solving the mentioned OPF problems. …”
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  11. 11
    Solving optimal power flow problem with stochastic wind–solar–small hydro power using barnacles mating optimizer

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

    Published 2021
    “…In this paper, recent metaheuristic algorithm namely Barnacles Mating Optimizer (BMO) will be used to solve three objective functions of OPF problem viz. (1) cost minimization of the power generation that consists of thermal and stochastic wind–solar–small hydro power generations, (2) power loss minimization, and (3) combined cost and emission minimization of mentioned power generations. …”
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  12. 12
    Use of AR Block Processing for Estimating the State Variables of Power System

    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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  13. 13
    OPTIMIZATION OF TWO FISH ENCRYPTION ALGORITHM ON FPGA

    OPTIMIZATION OF TWO FISH ENCRYPTION ALGORITHM ON FPGA by DORE RAJA, ANAND A RAJA

    Published 2004
    “…For this project, 2 different optimized designs were implemented. The first design (Design I) was implemented with minimum hardware resources usage, using a single F -Function (modified) and was optimized with reasonable latency, throughput and throughput per gate. …”
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  14. 14
    Optimization Of Twofish Encryption Algorithm On FPGA

    Optimization Of Twofish Encryption Algorithm On FPGA by Raja, Ananda Raja Dore, Zain Ali, Noohul Basheer, Hussin, Fawnizu Azmadi

    Published 2005
    “…Both Design I and Design 2 were written using VHDL, simulated using ALDEC, synthesized using XILINX Synthesizing Tools, implemented using XILINX ISE6.2i implementation tools and download onto the Spartan 2 FPGA board using BEDLOAD utility program. …”
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  15. 15
    Green retrofitting of building using BIM-based sustainability optimization

    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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  16. 16
    Green retrofitting of building using BIM-based sustainability optimization

    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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  17. 17
    Robust correlation feature selection based support vector machine approach for high dimensional datasets

    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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  18. 18
    Information Theoretic-based Feature Selection for Machine Learning

    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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  19. 19
    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data

    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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  20. 20
    Comparative modelling of strength properties of hydrated-lime activated rice husk-ash (HARHA) modified soft soil for pavement construction purposes by artificial neural network (ANN) and fuzzy logic (FL)

    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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