Search Results - intelligence valid ((svm algorithm) OR (((force algorithm) OR (tree algorithm))))

Refine Results
  1. 1

    A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation by Mohd Ali, Nursabillilah, Besar, Rosli, Ab Aziz, Nor Azlina

    Published 2023
    “…The study involved three machine learning algorithms, random forest (RF), extra tree (ET), and support vector machine (SVM). …”
    Get full text
    Get full text
    Get full text
    Article
  2. 2

    Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination by Nallakukkala, Sirisha, Tackie-Otoo, Bennet Nii, Aliyu, Ruwaida, Lal, Bhajan, Nallakukkala, Jagadish Ram Deepak, Devi, Gayathri

    Published 2025
    “…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
    Get full text
    Get full text
    Article
  3. 3

    Neutralisation state driven single-agent search strategy for solving constraint satisfaction problem / Saajid Akram Ahmed Abuluaih by Ahmed Abuluaih, Saajid Akram

    Published 2019
    “…Since Constraint Satisfaction Problem (CSP) is an NP-complete problem, brute-force search algorithms such as Backtracking algorithm (BT) are required as the guarantee to find a solution, when there is one. …”
    Get full text
    Get full text
    Thesis
  4. 4

    Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2019
    “…This paper presents two intelligent algorithms that hybridized between ant colony optimization (ACO) and SVM for tuning SVM parameters and selecting feature subset without having to discretize the continuous values. …”
    Get full text
    Get full text
    Get full text
    Article
  5. 5
  6. 6

    Prediction of photovoltaic system output using hybrid Cuckoo Search Least Square Support Vector Machine / Muhammad Aidil Adha Aziz by Aziz, Muhammad Aidil Adha

    Published 2019
    “…The performance of CS-LSSVM is compared with those obtained from LS-SVM using cross-validation technique in terms of accuracy. …”
    Get full text
    Get full text
    Thesis
  7. 7
  8. 8
  9. 9

    Dual-tone multifrequency signal detection using support vector machines by Nagi J., Tiong S.K., Yap K.S., Ahmed S.K.

    Published 2023
    “…A SVM classifier is trained using the estimated fundamental DTMF carrier frequencies, and is validated using the input samples for classification of low and high DTMF frequency groups. …”
    Conference paper
  10. 10

    A comparative analysis of machine learning algorithms for diabetes prediction by Alansari, Waseem Abdulmahdi, Masnizah Mohd

    Published 2024
    “…During the DD2019 experiment, the RF and SVM algorithms demonstrated the highest levels of accuracy, achieving 96.65% and 93.93%, respectively. …”
    Get full text
    Get full text
    Get full text
    Article
  11. 11
  12. 12

    Real-time human activity recognition using external and internal spatial features by Htike@Muhammad Yusof, Zaw Zaw, Egerton, Simon, Kuang, Ye Chow

    Published 2010
    “…Activities are classified by a support vector machine (SVM) with a radial basis kernel. Optimal parameters for the SVM are found through a 10-fold cross-validation. …”
    Get full text
    Get full text
    Get full text
    Proceeding Paper
  13. 13

    Data Classification and Its Application in Credit Card Approval by Thai , VinhTuan

    Published 2004
    “…This project is involved with identification of the available algorithms used in data classification and the implementation of C4.5 decision tree induction algorithm in solving the data classifying task. …”
    Get full text
    Get full text
    Final Year Project
  14. 14

    A comparative study of supervised machine learning approaches for slope failure production by Deris A.M., Solemon B., Omar R.C.

    Published 2023
    “…The prediction result from testing data was validated based on statistical analysis. The result shows that SVM model has outperformed DT model by giving the prediction accuracy of 97%. ith the advent of technology and the introduction of computational intelligent methods, the prediction of slope failure using the machine learning (ML) approach is rapidly growing for the past few decades. …”
    Conference Paper
  15. 15
  16. 16
  17. 17

    Real time self-calibration algorithm of pressure sensor for robotic hand glove system by Almassri, Ahmed M. M.

    Published 2019
    “…The proposed method was validated by comparing the output force of PSCA with the experimental target force from load cell (reference). …”
    Get full text
    Get full text
    Thesis
  18. 18

    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

    Published 2024
    “…Finally, the proposed algorithms were also validated on another dataset of a university campus in a different region. …”
    Get full text
    Get full text
    Thesis
  19. 19

    Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines by Nagi J., Yap K.S., Tiong S.K., Ahmed S.K., Nagi F.

    Published 2023
    “…Key innovations include the use of a Finite Impulse Response (FIR) bandpass filter for reduction of noise from DTMF input samples, and Support Vector Machines (SVM) for intelligent classification of the detected DTMF carrier frequencies. …”
    Conference paper
  20. 20

    Optimizing the Social Force Model Using New Hybrid WOABAT-IFDO in Crowd Evacuation in Panic Situation by Hamizan, Sharbini, Roselina, Sallehuddin, Habibollah, Haron

    Published 2022
    “…As the current classical evacuation model, the Social Force Model lacks decision-making ability for finding the best directions towards an exit. …”
    Get full text
    Get full text
    Get full text
    Proceeding