Search Results - (( variable learning space algorithm ) OR ( java application tree algorithm ))

Refine Results
  1. 1
  2. 2

    Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

    Published 2007
    “…The preparation phase transforms the original dialogue corpus into phrases space. In the selection phase, a new variable length genetic algorithm is applied to select the lexical cues. …”
    Get full text
    Get full text
    Thesis
  3. 3

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4

    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
    Get full text
    Get full text
    Thesis
  5. 5
  6. 6
  7. 7
  8. 8

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
    Get full text
    Get full text
    Get full text
    Thesis
  9. 9

    Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications by Shanmugam Y., Narayanamoorthi R., Ramachandaramurthy V.K., Bernat P., Shrestha N., Son J., Williamson S.S.

    Published 2025
    “…The ML approach, which predicts optimal design parameters with a trained dataset, is more efficient with reduced duration than conventional finite element analysis (FEA) tools and stochastic methods. The learning algorithms consider variables such as core structure, cross-coupling effect, and coil flux pipe length. …”
    Article
  10. 10

    Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining by Sivarao, Subramonian

    Published 2009
    “…One such method is machine learning, which involves using a computer algorithm to capture hidden knowledge from data. …”
    Get full text
    Get full text
    Book Chapter
  11. 11

    An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection by Ayodele Nojeem, Lasisi

    Published 2018
    “…Real-Valued Negative Selection Algorithm with Variable-Sized Detectors (V-Detectors) is an offspring of AIS and demonstrated its potentials in the field of anomaly detection. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  12. 12

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  13. 13

    AI powered asthma prediction towards treatment formulation: an android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Md Muzahid, Abu Jafar, Sarker, Md Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md

    Published 2022
    “…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
    Get full text
    Get full text
    Get full text
    Article
  14. 14

    Antidepressant Treatment Response Prediction With Early Assessment of Functional Near-Infrared Spectroscopy and Micro-RNA by Lee, Lok Hua, Ho, Cyrus Su Hui, Chan, Yee Ling, Tay, Gabrielle Wann Nii, Lu, Cheng-Kai, Tang, Tong Boon

    Published 2025
    “…To address this, the aim of the current study is to investigate MDD ATR at three response levels using fNIRS and micro-ribonucleic acids (miRNAs). Our proposed algorithm includes a custom inter-subject variability reduction based on the principal component analysis (PCA). …”
    Get full text
    Get full text
    Article
  15. 15

    AI powered asthma prediction towards treatment formulation : An android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Muzahid, Abu Jafar Md, Sarker, Md. Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md.

    Published 2022
    “…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16
  17. 17

    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 SCSO algorithm replicates the hunting and searching strategies of the sand cat while having the advantage of avoiding local optima and finding the ideal solution with minimal control variables. …”
    Get full text
    Get full text
    Article
  18. 18

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

    Published 2012
    “…Experimental results suggested that the class probability distribution function of a prediction model has to be closer to a training dataset; less skewed environment enable learning schemes to discover better function F in a bigger Fall space within a higher dimensional feature space, data sampling and partition size is appear to proportionally improve the precision and recall if class distribution ratios are balanced. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  19. 19

    Sensorless induction motor speed control for electric vehicles using enhanced hybrid flux estimator with ann-ifoc controller by Sepeeh, Muhamad Syazmie

    Published 2022
    “…The sensorless ANN-IFOC was modelled, simulated, and tested using MATLAB/Simulink for a 20Hp EV motor based on a small Renault Twizy EV model and triggered by the space-vector pulse-width modulation (SVPWM). The results of the ANN-IFOC hybrid estimator were obtained in four cases, which were 1) constant high and low speeds, 2) constant speed against parameter variation, 3) variable speed, and 4) variable load torque disturbances. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  20. 20

    Multivariate Based Analysis of Methane Adsorption Correlated to Toc and Mineralogy Impact from Different Shale Fabrics by Irfan, S.A., Azli, N.M., Abdulkareem, F.A., Padmanabhan, E.

    Published 2021
    “…The statistical analysis presented in this study incorporated one of the best regression models algorithms based on machine learning approach to study the adsorption variation with shale fabric this study. …”
    Get full text
    Get full text
    Conference or Workshop Item