Search Results - (( variable learning based algorithm ) OR ( using adaptive method algorithm ))

Refine Results
  1. 1

    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
    “…Therefore, we aimed to classify six classes of freshly excised tissues from a set of electrical impedance measurement variables using five ensemble-based machine learning (ML) algorithms, namely, the random forest (RF), extremely randomized trees (ERT), decision tree (DT), gradient boosting tree (GBT) and AdaBoost (Adaptive Boosting) (ADB) algorithms, which can be subcategorized as bagging and boosting methods. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  2. 2

    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
    “…This study proposed an improved parameter estimation procedure for PEMFCs by using the GOOSE algorithm, which was inspired by the adaptive behaviours found in geese during their relaxing and foraging times. …”
    Article
  3. 3

    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…Based on the results obtained, a better prediction result can be produced by the proposed GA-BPNN learning algorithm.…”
    Get full text
    Get full text
    Thesis
  4. 4

    Effects of user selected conditions on modeling of dynamic systems using adaptive fuzzy model by Yaacob, Mohd. Shafiek, Jamaluddin, Hishamuddin

    Published 2001
    “…The method of selection of the input variables, the number of rules, and the learning rate are briefly discussed. …”
    Get full text
    Get full text
    Get full text
    Article
  5. 5

    Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.] by Mohd, Thuraiya, Jamil, Syafiqah, Masrom, Suraya, Ab Rahim, Norbaya

    Published 2021
    “…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
    Get full text
    Get full text
    Conference or Workshop Item
  6. 6

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
    Get full text
    Get full text
    Get full text
    Thesis
  7. 7

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

    Published 2017
    “…In this research work, a modified backpropagation neural network is combined with a modified chaos-search genetic algorithm for STLF of one day and a week ahead. Multiple modifications are carried out on the conventional back-propagation (BP) algorithm such as, improvements in the momentum factor and adaptive learning rate. …”
    Get full text
    Get full text
    Thesis
  8. 8

    Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning by Solihin M.I., Yanto, Hayder G., Maarif H.A.-Q.

    Published 2024
    “…One of the prominent methods to improve machine learning accuracy is by using ensemble method which basically employs multiple base models. …”
    Conference Paper
  9. 9

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
    Get full text
    Get full text
    Thesis
  10. 10

    Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

    Published 2020
    “…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through the use of Backtracking Search Algorithm (BSA) as an efficient optimization algorithm in learning process of ANFIS approach. …”
    Get full text
    Get full text
    Get full text
    Thesis
  11. 11

    Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail by Sh. Ismail, Faridah

    Published 2015
    “…An intelligent predictive model will replace the lengthy procedures by predicting the properties using known fiberboard characteristics. Back-propagation algorithm is a training method widely used in a multilayer perceptron Neural Network model. …”
    Get full text
    Get full text
    Thesis
  12. 12

    Revolutionizing video analytics: a review of action recognition using 3D by Jeddah, Yunusa Mohammed, Hassan Abdalla Hashim, Aisha, Khalifa, Othman Omran, Ibrahim, Adamu Abubakar

    Published 2024
    “…This paper provides an overview of recent research in 3D video action recognition, concentrating on different deep learning architectures, self-supervised learning, graph-based methods, fewshot and zero-shot learning, cross-modal action understanding, and model interpretability. …”
    Get full text
    Get full text
    Article
  13. 13

    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…Multilayer Feedforward Back Propagation (MLFFBP) was used. Among the available learning algorithms in the Neural Network Toolbox of MATLAB, three algorithms, gradient descent back propagation (TRAINGD), gradient descent with adaptive learning rule back propagation (TRAINGDA) and the Levenberg-Marquardt (TRAINLM) were studied. …”
    Get full text
    Get full text
    Thesis
  14. 14

    A deep learning approach for facial detection in targeted billboard advertising / Lau Sian En by Lau , Sian En

    Published 2025
    “…This system utilises sophisticated deep learning algorithm using Convolutional Neural Network (CNN) to identify and examine human faces, enabling advertisers to customise their content according to demographic variables including age and gender. …”
    Get full text
    Get full text
    Get full text
    Thesis
  15. 15

    Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration by Chia, Min Yan

    Published 2022
    “…As for the NNE, a novel meta-learner based on the stochastic-enabled extreme learning machine integrated with whale optimisation algorithm (WOA-ELM) was developed and used in such an application for the first time. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  16. 16
  17. 17

    Computational Thinking : Experiences of Rural Pupils in Sarawak Primary School by Nur Hasheena, Anuar

    Published 2021
    “…The samples were chosen through the purposive sampling method. The study employed embedded mixed methods design using a quasi-experimental approach which aims to provide an in-depth understanding of how pupils in remote rural area adapt and process to learning Computational Thinking skills (i.e., abstraction, algorithmic thinking, and decomposition) as well as their attitudes towards computational thinking practices by engaging in an unplugged game-based, art-based, Scratch programming and robotic activities through a revised Computational Thinking pedagogical model. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  18. 18

    Predictive Framework for Imbalance Dataset by Megat Norulazmi, Megat Mohamed Noor

    Published 2012
    “…This research was conducted based on limited number of datasets, test sets and variables. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  19. 19

    Predictive modeling of land surface temperature (LST) based on Landsat-8 satellite data and machine learning models for sustainable development by Pande C.B., Egbueri J.C., Costache R., Sidek L.M., Wang Q., Alshehri F., Din N.M., Gautam V.K., Chandra Pal S.

    Published 2025
    “…The ensemble framework combines three powerful machine learning algorithms: XG-Boost, Bagging-XG-Boost, and AdaBoost, to enhance the accuracy and robustness of LST predictions. …”
    Article
  20. 20

    Schelkunoff array synthesis methods using adaptive-iterative algorithm by Abdul Latiff, Nurul Mu'azzah

    Published 2003
    “…Basically, this algorithm is a combination of iterative algorithm with adaptive algorithm. …”
    Get full text
    Get full text
    Get full text
    Thesis