Search Results - (( model evaluation method algorithm ) OR ( swarm optimization learning algorithms ))

Refine Results
  1. 1

    Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method by Abbaszadeh M., Soltani-Mohammadi S., Ahmed A.N.

    Published 2023
    “…Copper deposits; Deposits; Geology; Learning algorithms; Mineralogy; Static Var compensators; Support vector machines; Three dimensional computer graphics; Alteration zones; Grid search; Grid-search method; Mineralization zone; Model Selection; Particle swarm optimization algorithm; Penalty parameters; Performance; Support vector classifiers; Support vectors machine; Particle swarm optimization (PSO); accuracy assessment; algorithm; classification; computer simulation; copper; geological survey; mineral alteration; mineralization; numerical model; ore deposit; parameterization; performance assessment; porphyry; resource assessment; support vector machine; three-dimensional modeling; Iran…”
    Article
  2. 2
  3. 3

    An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system by Islam N.N., Hannan M.A., Shareef H., Mohamed A.

    Published 2023
    “…Damping; Eigenvalues and eigenfunctions; Electric power systems; Learning algorithms; Optimization; Particle swarm optimization (PSO); Problem solving; State space methods; Test facilities; Backtracking search algorithms; Multi machine power system; Power system damping; Power system oscillations; Power system stability; Power System Stabilizer; System stability; algorithm; Article; backtracking search algorithm; bacterial foraging optimization algorithm; machine; mathematical analysis; mathematical computing; mathematical parameters; particle swarm optimization; power supply; power system stabilizer; process optimization; statistical model…”
    Article
  4. 4

    Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

    Published 2024
    “…This study emphasizes the importance of Machine Learning and Particle Swarm Optimization (PSO) in the context of predictive modeling and cost optimization within the field of construction project management. …”
    Get full text
    Get full text
    Article
  5. 5

    Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost by Chen, Suihai, Bong, Chih How, Chiu, Po Chan

    Published 2024
    “…PSO-EBGWO is used to optimize the parameters of the CatBoost model. In this method, the Gray Wolf optimized algorithm (EBGWO) is further optimized by particle swarm optimization (PSO), and when combined with it, the convergence performance of the model is improved, the parameters of the model are reduced, and the model is simplified. …”
    Get full text
    Get full text
    Get full text
    Article
  6. 6

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…This exploration and exploitation method followed in the proposed HACPSO algorithm makes it to converge to global optima with more efficiency than the original Cuckoo Search (CS) algorithm. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  7. 7

    Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection by Norfadzlan, Yusup, Izzatul Nabila, Sarbini, Dayang Nurfatimah, Awang Iskandar, Azlan, Mohd Zain, Didik Dwi, Prasetya

    Published 2026
    “…In the experiment, we conducted an evaluation of the effectiveness and efficiency of four nature-inspired binary algorithms for optimization namely Binary Particle Swarm Optimization (BPSO), Binary Grey Wolf Optimization algorithm (BGWO), Binary Differential Evolution algorithm (BDE), and Binary Salp Swarm algorithm (BSS) - in the context of human activity recognition (HAR). …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  8. 8
  9. 9

    Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

    Published 2019
    “…Numerous researchers have tried different methods to enhance the algorithm to improve performance, some of these methods include Support Vector Machine (SVM), Decision Trees, Extreme Learning Machine (ELM), Kernel Extreme Learning Machine (KELM), and Deng’s Reduced Kernel Extreme Learning Machine (RKELM). …”
    Get full text
    Get full text
    Get full text
    Thesis
  10. 10

    Backtracking Search Algorithm Based Fuzzy Charging-Discharging Controller for Battery Storage System in Microgrid Applications by Faisal M., Hannan M.A., Ker P.J., Uddin M.N.

    Published 2023
    “…Battery management systems; Charging (batteries); Controllers; Fuzzy logic; Fuzzy sets; Learning algorithms; Loading; Membership functions; Optimization; Particle swarm optimization (PSO); Secondary batteries; Backtracking search algorithms; Battery energy storage; Battery energy storage systems; Fuzzy controllers; Fuzzy logic control system; Fuzzy membership function; Micro grid; State of charge; Battery storage…”
    Article
  11. 11

    Prostate cancer prediction using feedforward neural network trained with particle swarm optimizer by Jui, Julakha Jahan, Molla, M. M.Imran, Alam, Mohammad Khurshed, Ferdowsi, Asma

    Published 2022
    “…The experimental results are evaluated using the mean, best, worst, and standard deviation (Std.) values of the fitness function and compared with other learning algorithms for FNNs, including the Salp Swarm Algorithm (SSA) and Sine Cosine Algorithm (SCA). …”
    Get full text
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  12. 12
  13. 13

    Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

    Published 2017
    “…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
    Get full text
    Get full text
    Get full text
    Thesis
  14. 14
  15. 15
  16. 16
  17. 17

    Improving earth surface temperature forecasting through the optimization of deep learning hyper-parameters using barnacles mating optimizer by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Muhammad 'Arif, Mohamad

    Published 2024
    “…The forecasting model is trained on a global temperature dataset with seven inputs and compared with DL models optimized by Particle Swarm Optimization (PSO), Harmony Search Algorithm (HSA), and Ant Colony Optimization (ACO). …”
    Get full text
    Get full text
    Get full text
    Article
  18. 18

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
    Get full text
    Get full text
    Thesis
  19. 19

    State of Charge Estimation for Lithium-Ion Battery Using Recurrent NARX Neural Network Model Based Lighting Search Algorithm by Lipu M.S.H., Hannan M.A., Hussain A., Saad M.H.M., Ayob A., Blaabjerg F.

    Published 2023
    “…Backpropagation; Charging (batteries); Ions; Learning algorithms; Lighting; Lithium-ion batteries; Particle swarm optimization (PSO); Radial basis function networks; Back-propagation neural networks; Electrochemical reactions; NARX neural network; Non-linear autoregressive with exogenous; Radial basis function neural networks; Search Algorithms; State of charge; State-of-charge estimation; Battery management systems…”
    Article
  20. 20

    Software defect prediction framework based on hybrid metaheuristic optimization methods by Wahono, Romi Satria

    Published 2015
    “…The proposed framework and models that are are considered to be the specific research contributions of this thesis are: 1) a comparison framework of classification models for software defect prediction known as CF-SDP, 2) a hybrid genetic algorithm based feature selection and bagging technique for software defect prediction known as GAFS+B, 3) a hybrid particle swarm optimization based feature selection and bagging technique for software defect prediction known as PSOFS+B, and 4) a hybrid genetic algorithm based neural network parameter optimization and bagging technique for software defect prediction, known as NN-GAPO+B. …”
    Get full text
    Get full text
    Get full text
    Thesis