Search Results - (( using optimization strategy algorithm ) OR ( variable learning based algorithm ))

Search alternatives:

Refine Results
  1. 1
  2. 2

    Multi-stage thermal-economical optimization of compact heat exchangers: A new evolutionary-based design approach for real-world problems by Yousefi, M., Darus, A.N., Yousefi, M., Hooshyar, D.

    Published 2015
    “…Learning automata based particle swarm optimization (LAPSO), is employed for handling nine design variables while satisfying various equality and inequality constraints. …”
    Get full text
    Get full text
    Article
  3. 3

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  4. 4

    Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

    Published 2025
    “…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
    Article
  5. 5

    A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

    Published 2023
    “…The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
    Get full text
    Get full text
    Article
  6. 6

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

    Published 2019
    “…Widespread models like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Evolutionary Strategy (ES) and Population-Based Incremental Learning (PBIL) dealing with the specified problems are also explored and compared. …”
    Get full text
    Get full text
    Thesis
  7. 7

    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

    Published 2012
    “…The ARTMAP system is dependent on training sequence presentation to determine the effectiveness of the learning processes, as well as the strength of the biasing parameter, lambda λ. The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. …”
    Get full text
    Get full text
    Conference or Workshop Item
  8. 8

    Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

    Published 2018
    “…Therefore, this was not incorporated in BBN models. Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
    Get full text
    Get full text
    Thesis
  9. 9

    Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation by Muslim, Farah Kamil Abid

    Published 2017
    “…Finally, the last objective is to improve the optimality of the new approach using a robust Machine Learning strategy. …”
    Get full text
    Get full text
    Get full text
    Thesis
  10. 10

    Design of Optimal Pitch Controller for Wind Turbines Based on Back-Propagation Neural Network by Shengsheng, Qin, Zhipeng, Cao, Feng, Wang, Ngu, Sze Song, Kho, Lee Chin, Hui, Cai

    Published 2024
    “…The model is simulated in MATLAB 2019b, real-time data are observed, and the control effect is compared with that of a Takagi–Sugeno optimal controller, firefly algorithm optimal controller and fuzzy controller. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  11. 11

    Development of robust procedures for partial least square regression with application to near infrared spectral data by Silalahi, Divo Dharma

    Published 2021
    “…In the in-processing, the PLSR model is very sensitive to the optimal number of PLS components used in the model fitting process. …”
    Get full text
    Get full text
    Thesis
  12. 12

    The optimization of technical trading strategy using genetic algorithm approach / Khairunnisa Musa by Musa, Khairunnisa

    Published 2006
    “…Recently, the use of genetic algorithm for the optimization of technical trading strategies has been receiving a great deal of attention. …”
    Get full text
    Get full text
    Thesis
  13. 13

    Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

    Published 2023
    “…The evolutionary algorithm has been extensively used to solve a range of combinatorial optimization problems. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  14. 14

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
    “…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
    Get full text
    Get full text
    Get full text
    Article
  15. 15

    An adaptively switching iteration strategy for population based metaheuristics / Nor Azlina Ab. Aziz by Nor Azlina, Ab. Aziz

    Published 2017
    “…Experiments conducted using three parent algorithms namely particle swarm optimization (PSO), which is a popular population-based optimizer with population and individual memories, gravitational search algorithm (GSA), a memoryless young optimizer, and simulated Kalman filter (SKF), a newly introduced optimization algorithm that use population’s memory to guide an agent’s search, show that iteration strategy is an algorithm dependent parameter as well as function dependent. …”
    Get full text
    Get full text
    Get full text
    Thesis
  16. 16

    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

    Published 2020
    “…In addition, the ranked order of the variables based on their importance differed across the ML algorithms. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  17. 17

    Optimization of operations of reservoir systems for hydropower generation in Tigris River Basin, Iraq by Al-Aqeel, Yousif Hashim Abdullah

    Published 2016
    “…The two strategies mentioned previously were also used in the combined GAOMs and SMs to determine the optimal operation policies for the multi-reservoir system in the case of using a new storage of Makhoul reservoir. …”
    Get full text
    Get full text
    Thesis
  18. 18

    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
  19. 19
  20. 20

    Optimal charging strategy for plug-in hybrid electric vehicle using evolutionary algorithm by Lee, Clement Yuon Sien

    Published 2016
    “…Upon this study, a control charging system is needed to control the charging so that the distribution network is not overloaded. An optimal charging strategy for plug-in hybrid electric vehicle (PHEV) is proposed and developed by using evolutionary algorithm to obtain the most suitable charging condition for each PHEV charging. …”
    Get full text
    Get full text
    Undergraduates Project Papers