Search Results - (( developing comparative optimization algorithm ) OR ( java implication based algorithm ))

Refine Results
  1. 1
  2. 2

    Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah by Ali, Sadollah

    Published 2013
    “…In addition, two novel optimization methods are developed and presented which are named the mine blast algorithm (MBA) and the water cycle algorithm (WCA). …”
    Get full text
    Get full text
    Thesis
  3. 3
  4. 4

    Hybrid particle swarm optimization algorithm with fine tuning operators by Murthy, G.R., Arumugam, M.S., Loo, C.K.

    Published 2009
    “…From several comparative analyses, it is clearly seen that the performance of all the three PSO algorithms (pf-PSO, ePSO, and hybrid PSO) is considerably improved with various fine tuning operators and sometimes more competitive than the recently developed PSO algorithms.…”
    Get full text
    Get full text
    Article
  5. 5
  6. 6

    Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions by Mazlina, Abdul Majid, Alsariera, Yazan A., Alamri, Hammoudeh S., Nasser, Abdullah M., Kamal Z., Zamli

    Published 2014
    “…Over the last 30 years, many meta-heuristic algorithms have been developed in the literature including that of Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search Algorithm (HS) to name a few. …”
    Get full text
    Get full text
    Conference or Workshop Item
  7. 7

    Long term energy demand forecasting based on hybrid, optimization: Comparative study by Musa, Wahab, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
    Get full text
    Get full text
    Get full text
    Article
  8. 8

    Development of New Genetic Algorithm Software for Blow Mould Process by K., Kadirgama, M. M., Noor, R., Daud, M. R. M., Rejab

    Published 2008
    “…The approach is based on newly development of Genetic Algorithm software. In this work, the objectives were to optimized parameters with newly develop software and compare with statistical software. …”
    Get full text
    Get full text
    Conference or Workshop Item
  9. 9

    A New Quadratic Binary Harris Hawk Optimization For Feature Selection by Abdullah, Abdul Rahim, Too, Jing Wei, Mohd Saad, Norhashimah

    Published 2019
    “…In this study, twenty-two datasets collected from the UCI machine learning repository are used to validate the performance of proposed algorithms. A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
    Get full text
    Get full text
    Get full text
    Article
  10. 10
  11. 11

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…Also, fed batch fermentation problems in winery wastewater treatment and biogas generation from sewage sludge are developed for optimization. Though DE traditionally performs better than other evolutionary algorithms and swarm intelligence techniques in optimization of fed-batch fermentation, BSA edged DE and other recent metaheuristics to emerge as superior optimization method in this work. …”
    Get full text
    Get full text
    Thesis
  12. 12
  13. 13

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

    Published 2019
    “…Its optimality has inspired the development of a metaheuristic algorithm called Heuristic Kalman Algorithm (HKA) in 2009. …”
    Get full text
    Get full text
    Thesis
  14. 14

    Comparative analysis of sine cosine and social network search-based algorithm for software test redundancy reduction optimization by Mekeng, Ambros Magnus Rudolf, Kamal Z., Zamli, Muhammad Zarlis, .

    Published 2024
    “…Acknowledging the fact that no single metaheuristic algorithm is superior than its counterparts as well as taking the opportunity to adopt recent algorithm, our work present a comparative study (i.e., solving the TRR problem) using two recently developed metaheuristic algorithms namely the Social Network Search Algorithm (SNS) and the Sine Cosine Algorithm (SCA). …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  15. 15

    Predicting attackers of online shaming using ant colony optimization / Noor Shafiqa Fazlien Mohamad Fauzi by Mohamad Fauzi, Noor Shafiqa Fazlien

    Published 2020
    “…In order to predict the attackers of online shaming, Ant Colony Optimization Algorithm will be used and it will be compared with J48 algorithm. …”
    Get full text
    Get full text
    Thesis
  16. 16

    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

    Published 2024
    “…In the fourth phase, the newly developed algorithm undergoes testing on the formulated ROOPs and compared to several contemporary optimizer algorithms. …”
    Get full text
    Get full text
    Thesis
  17. 17

    Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

    Published 2018
    “…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
    Get full text
    Get full text
    Get full text
    Thesis
  18. 18

    Multi-objective optimization of stand-alone hybrid renewable energy system by genetic algorithm by Nejad, Mohsen Fadaee

    Published 2013
    “…HOGA (Hybrid Optimization by Genetic Algorithms) is developed by Dr.Lopez from Zaragoza university in Spain. …”
    Get full text
    Get full text
    Thesis
  19. 19

    The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment by Kok, Kai Yit

    Published 2016
    “…The performance of the IE algorithm was compared with that of PSO, GA, DE, and BBO at their respective optimized settings. …”
    Get full text
    Get full text
    Thesis
  20. 20

    Assembly sequence optimization using the bees algorithm by Kamaruddin, Shafie, Azmi, Nabilah, Sukindar, Nor Aiman

    Published 2022
    “…As a result, the Bees Algorithm outperforms other algorithms in dealing with the multi-modal optimization problem of assembly sequence optimization.…”
    Get full text
    Get full text
    Get full text
    Get full text
    Book Chapter