Search Results - (( based optimisation based algorithm ) OR ( evolution classification problems algorithm ))

Search alternatives:

Refine Results
  1. 1
    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level

    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

    Published 2024
    thesis::doctoral thesis
    Save to List
    Saved in:
  2. 2
    A New Bats Echolocation-based Algorithm for Single Objective Optimisation

    A New Bats Echolocation-based Algorithm for Single Objective Optimisation by N. M., Yahya, Tokhi, M. Osman, Kasdirin, Hyreil Anuar

    Published 2016
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  3. 3
    Differential evolution for neural networks learning enhancement

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  4. 4
    A Modified Bats Echolocation-Based Algorithm for Solving Constrained Optimisation Problems

    A Modified Bats Echolocation-Based Algorithm for Solving Constrained Optimisation Problems by N. M., Yahya, Tokhi, M. O.

    Published 2017
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  5. 5
    Performance Comparison of FA, PSO and CS application in SINR Optimisation for LCMV Beamforming Technique

    Performance Comparison of FA, PSO and CS application in SINR Optimisation for LCMV Beamforming Technique by Doroody C., Kiong T.S.

    Published 2023
    Article
    Save to List
    Saved in:
  6. 6
    Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm

    Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm by Nik Mohamed Hazli, Nik Muhammad Aiman

    Published 2018
    “…The expected result is the algorithms are able to optimise the PID controller. …”
    Get full text
    Get full text
    Monograph
    Save to List
    Saved in:
  7. 7
    Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation

    Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation by M. F. F., Ab Rashid

    Published 2013
    “…The aim of this research is to establish a methodology and algorithm for integrating ASP and ALB optimisation using Particle Swarm Optimisation. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  8. 8
    A New Quadratic Binary Harris Hawk Optimization For Feature Selection

    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
    Save to List
    Saved in:
  9. 9
    A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application

    A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application by Zainal Abidin, Zulkifli

    Published 2011
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  10. 10
    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System

    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

    Published 2020
    “…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  11. 11
    Chaotic Immune Symbiotic Organisms Search algorithm for solving optimisation problem

    Chaotic Immune Symbiotic Organisms Search algorithm for solving optimisation problem by Zamani M.K.M., Musirin I., Suliman S.I., Mustaffa S.A.S.

    Published 2023
    “…Heuristics-based algorithms were introduced to counter the problem faced by classical optimisation techniques. …”
    Article
    Save to List
    Saved in:
  12. 12
    Bats echolocation-inspired algorithms for global optimisation problems

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…The algorithm is a hybrid algorithm that operates using dual level search strategy that takes merits of a particle swarm optimisation algorithm and a modified adaptive bats sonar algorithm. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  13. 13
    Aco-based feature selection algorithm for classification

    Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

    Published 2022
    “…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  14. 14
    Application of the bees algorithm for constrained mechanical design optimisation problem

    Application of the bees algorithm for constrained mechanical design optimisation problem by Kamaruddin, Shafie, Abd Latif, Mohd Arif Hafizi

    Published 2019
    “…Nowadays, many optimisation algorithms have been introduced due to the advancement of technology such as Teaching Learning Based Optimisation (TLBO), Ant Colony Optimisation (ACO), Particle Swarm Optimisation (PSO) and the Bees Algorithm. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  15. 15
    Evaluation of Vector Evaluated Particle Swarm Optimisation Enhanced with Non-dominated Solutions and Multiple Nondominated Leaders based on WFG Test Functions

    Evaluation of Vector Evaluated Particle Swarm Optimisation Enhanced with Non-dominated Solutions and Multiple Nondominated Leaders based on WFG Test Functions by Zuwairie, Ibrahim, Mohd Zaidi, Mohd Tumari, Mohd Falfazli, Mat Jusof, Kian, Sheng Lim

    Published 2014
    “…The improved VEPSO algorithms have been subjected to a series of numerical experiments based on ZDT benchmark datasets. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  16. 16
    Metaheuristic algorithms applied in ANN salinity modelling

    Metaheuristic algorithms applied in ANN salinity modelling by Khudhair, Zahraa S., Zubaidi, Salah L., Dulaimi, Anmar, Al-Bugharbee, Hussein, Muhsen, Yousif Raad, Putra Jaya, Ramadhansyah, Mohammed Ridha, Hussein, Raza, Syed Fawad, Ethaib, Saleem

    Published 2024
    “…The CPSOCGSA performance was evaluated by various single-based ones, including multi-verse optimiser (MVO), marine predator's optimisation algorithm (MPA), particle swarm optimiser (PSO), and the slim mould algorithm (SMA). …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  17. 17
    Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy

    Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy by Al-Dabbagh, Rawaa Dawoud, Neri, Ferrante, Idris, Norisma, Baba, Mohd Sapiyan

    Published 2018
    “…A trend that has emerged recently is to make the algorithm parameters automatically adapt to different problems during optimization, thereby liberating the user from the tedious and time-consuming task of manual setting. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  18. 18
    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution

    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

    Published 2017
    “…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  19. 19
    Artificial fish swarm optimization for multilayer network learning in classification problems

    Artificial fish swarm optimization for multilayer network learning in classification problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam

    Published 2012
    “…Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN.In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems.The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  20. 20
    Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems

    Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2012
    “…In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems. The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:

Search Tools: