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  1. 1
    Development of optimization Alghorithm for uncertain non-linear dynamical system

    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
    “…To strengthen the findings, theoretical analyses were done on each algorithm. These include optimality, stability, convergence, and the rate of convergence analyses. …”
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  2. 2
    A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction

    A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction by Sabo, Aliyu, Abdul Wahab, Noor Izzri, Mohd Radzi, Mohd Amran, Mailah, Nashiren Farzilah

    Published 2013
    “…The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. …”
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  3. 3
    Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm

    Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm by Rosmazi, Rosli, Zamri, Mohamed

    Published 2021
    “…The final value of the fitness function and the iteration number it took to converge were used as the qualifying indicator to the proposed cuckoo search algorithm efficiency. A comparison was done against particle swarm optimization, genetic algorithm, and sine–cosine algorithm, where the modified cuckoo search algorithm showed the lowest root mean square error and fastest convergence rate among the three algorithms.…”
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  4. 4
    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network

    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

    Published 2016
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  5. 5
    Development Of Artificial Bee Colony (Abc) Variants And Memetic Optimization Algorithms

    Development Of Artificial Bee Colony (Abc) Variants And Memetic Optimization Algorithms by Sulaiman, Noorazliza

    Published 2017
    “…One of BIAs, artificial bee colony (ABC) optimization algorithm, has shown excellent performance in many applications compared to other optimization algorithms. …”
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  6. 6
    An ensemble of neural network and modified grey wolf optimizer for stock prediction

    An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

    Published 2019
    “…The proposed approachoutperforms existing available meta-heuristic algorithms. Specifically, the proposed model achieved 97% classification rate, 95% precise prediction and less than 2.0 error rate. …”
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  7. 7
    A modified crow search algorithm with niching technique for numerical optimization

    A modified crow search algorithm with niching technique for numerical optimization by Islam, J., Vasant, P.M., Negash, B.M., Watada, J.

    Published 2019
    “…Despite its easy implementation, crow search algorithm has weakness to find global optima and suffers from slow convergence rate in multi-modal optimization problems. …”
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  8. 8
    A modified crow search algorithm with niching technique for numerical optimization

    A modified crow search algorithm with niching technique for numerical optimization by Islam, J., Vasant, P.M., Negash, B.M., Watada, J.

    Published 2019
    “…Despite its easy implementation, crow search algorithm has weakness to find global optima and suffers from slow convergence rate in multi-modal optimization problems. …”
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  9. 9
    Parallel metaheuristic algorithm for route planning using CUDA

    Parallel metaheuristic algorithm for route planning using CUDA by Looi, Daniel Jun Jie

    Published 2025
    “…Area of Study: Massively Parallel Computing, Combinatorial Optimization Keywords: Parallel Metaheuristic Algorithm, Travelling Salesman Problem, CUDA, GPU, Genetic Algorithm…”
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  10. 10
    Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function

    Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function by Hammash, Nayif Mohammed

    Published 2012
    “…This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. …”
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  11. 11
    A modified niching crow search approach to well placement optimization

    A modified niching crow search approach to well placement optimization by Islam, J., Rahaman, M.S.A., Vasant, P.M., Negash, B.M., Hoqe, A., Alhitmi, H.K., Watada, J.

    Published 2021
    “…In this article, a modified crow search algorithm is proposed to tackle the well placement optimization problem. …”
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  12. 12
    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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  13. 13
    Voting algorithms for large scale fault-tolerant systems

    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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  14. 14
    Normative Fish Swarm Algorithm For Global Optimization With Applications

    Normative Fish Swarm Algorithm For Global Optimization With Applications by Tan, Weng Hooi

    Published 2019
    “…Artificial Fish Swarm Algorithm (AFSA) have become popular optimization technique used to solve various problems, Nevertheless, according to surveys, the existing fish swarm algorithms still have some deficiencies to strike the exact optimum within appropriate convergence rate. …”
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  15. 15
    A modified Q-learning path planning approach using distortion concept and optimization in dynamic environment for autonomous mobile robot

    A modified Q-learning path planning approach using distortion concept and optimization in dynamic environment for autonomous mobile robot by Low, Ee Soong, Ong, Pauline, Low, Cheng Yee

    Published 2023
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  16. 16
    A modified Q-learning path planning approach using distortion concept and optimization in dynamic environment for autonomous mobile robot

    A modified Q-learning path planning approach using distortion concept and optimization in dynamic environment for autonomous mobile robot by Ee Soong Low, Ee Soong Low, Pauline Ong, Pauline Ong, Cheng Yee Low, Cheng Yee Low

    Published 2023
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  17. 17
    A review of genetic algorithms and parallel genetic algorithms on Graphics Processing Unit (GPU)

    A review of genetic algorithms and parallel genetic algorithms on Graphics Processing Unit (GPU) by Mohd Johar, Fauzi, Azmin, Farah Ayuni, Suaidi, Mohd Kadim, Shibghatullah, Abdul Samad, Ahmad, Badrul Hisham, Salleh, Siti Nadzirah, Abdul Aziz, Mohd Zainol Abidin, Md Shukor, Mahfuzah

    Published 2013
    “…Genetic Algorithms (GAs) is proven to be effective in solving many optimization tasks. …”
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  18. 18
    Modified Particle Swarm Optimization with Time Varying Acceleration Coefficients for Economic Load Dispatch with Generator Constraints

    Modified Particle Swarm Optimization with Time Varying Acceleration Coefficients for Economic Load Dispatch with Generator Constraints by Abdullah, M.N., Bakar, Ab Halim Abu, Rahim, N.A., Mokhlis, Hazlie, Illias, Hazlee Azil, Jamian, J.J.

    Published 2014
    “…The effectiveness of MPSO-TVAC algorithm is tested on different power systems with POZ, ramp-rate limits and transmission loss constraints. …”
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  19. 19
    Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning

    Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Aloufi, Khalid, Kamal Z., Zamli

    Published 2019
    “…Two HS parameters were automatically updated using GWO, namely, pitch adjustment rate and bandwidth. The proposed hybrid algorithm for global optimization problems is called GWO-HS. …”
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  20. 20
    Memoryless modified symmetric rank-one method for large-scale unconstrained optimization

    Memoryless modified symmetric rank-one method for large-scale unconstrained optimization by Modarres, Farzin, Abu Hassan, Malik, Leong, Wah June

    Published 2009
    “…In this study, we present a scaled memoryless modified Symmetric Rank-One (SR1) algorithm and investigate the numerical performance of the proposed algorithm for solving large-scale unconstrained optimization problems. …”
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