Search Results - (( initial optimization based algorithm ) OR ( using combination learning algorithm ))

Refine Results
  1. 1

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…Firstly, an architecture for the clustering ensemble based on incremental genetic-based algorithms is proposed consisting of two phases: (i) to produce cluster partitions as initial populations, (ii) to combine cluster partitions and to generate final clustering solution by incremental genetic based clustering ensemble learning algorithm. …”
    Get full text
    Get full text
    Thesis
  2. 2

    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    Published 2017
    “…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
    Get full text
    Get full text
    Thesis
  3. 3

    An improved optimization algorithm-based prediction approach for the weekly trend of COVID-19 considering the total vaccination in Malaysia: A novel hybrid machine learning approac... by Ahmed, Marzia, Sulaiman, M. H., Mohamad, A. J., Rahman, Md. Mostafijur

    Published 2023
    “…This study concludes, based on its experimental findings, that hybrid IBMOLSSVM outperforms cross validations, original BMO, ANN and few other hybrid approaches with optimally optimized parameters.…”
    Get full text
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  4. 4
  5. 5
  6. 6

    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

    Published 2018
    “…Hence, this research has proposed three enhanced frameworks, namely, Optimized Gravitational-based (OGC), Density-Based Particle Swarm Optimization (DPSO), and Variance-based Differential Evolution with an Optional Crossover (VDEO) frameworks for data clustering. …”
    Get full text
    Get full text
    Thesis
  7. 7

    An ensemble data summarization approach based on feature transformation to learning relational data by Chung, Seng Kheau

    Published 2015
    “…In this thesis, a Feature Selection algorithm is investigated and proposed to optimize the TF-IDF vector space by selecting only relevant features from the initial TF-IDF vector space. …”
    Get full text
    Get full text
    Get full text
    Thesis
  8. 8

    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

    Published 2019
    “…To classify image noise type, the CNN trained with Backpropagation (BP) algorithm and Stochastic Gradient Descent (SGD) optimization technique are implemented. …”
    Get full text
    Get full text
    Get full text
    Thesis
  9. 9

    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

    Published 2024
    “…The second segmentation algorithm combines Delaunay triangulation clustering in the spatial domain and Particle Swarm Optimization (PSO). …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  10. 10

    An optimized ensemble for predicting reservoir rock properties in petroleum industry by Kenari, Seyed Ali Jafari

    Published 2013
    “…Ensemble is a learning algorithm that combines some experts instead of considering a single best expert for the predictions.The thesis proposed anoptimizing method leading to small structure of assemble GA. …”
    Get full text
    Get full text
    Thesis
  11. 11

    White blood cell recognition for biomarker model using improved convolutional neural network (CNN) by Mohd Safuan, Syadia Nabilah

    Published 2022
    “…However, with vast amount of WBCs data and various DL architectures available, tuning an optimal DL model is a daunting task. In this project, a diagnostic algorithm for WBCs’ DL analysis is proposed by combining transfer learning approach with fine tuning (FT) approach and tested on Kaggle dataset (9957 images). …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  12. 12
  13. 13
  14. 14
  15. 15

    A firefly algorithm based hybrid method for structural topology optimization by Gebremedhen, H.S., Woldemichael, D.E., Hashim, F.M.

    Published 2020
    “…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
    Get full text
    Get full text
    Article
  16. 16

    Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

    Published 2020
    “…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  17. 17

    Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling by Ullah, Wasif, Mohd Fadzil Faisae, Ab Rashid, Muhammad Ammar, Nik Mu’tasim

    Published 2025
    “…However, limited attention has been given to CHFS when considering holistic cost models using efficient algorithms. This paper presents a novel Greedy-Assisted Teaching-Learning-Based Optimization (GTLBO) algorithm for CHFS. …”
    Get full text
    Get full text
    Get full text
    Article
  18. 18
  19. 19

    Novel initialization strategy: Optimizing conventional algorithms for global maximum power point tracking by Al-Tawalbeh, Nedaa, Zafar, Muhammad Hamza, Mohd Radzi, Mohd Amran, Mohd Zainuri, Muhammad Ammirrul Atiqi, Al-Wesabi, Ibrahim

    Published 2024
    “…The major advantages of this approach are eliminating the need to modify the original algorithm, hybridizing with other algorithms, or employing any complex procedures, as in metaheuristic and optimization MPPT algorithms. …”
    Get full text
    Get full text
    Get full text
    Article
  20. 20