Search Results - (( (learner OR learned) generated using algorithm ) OR ( java application reoptimize algorithm ))

Search alternatives:

Refine Results
  1. 1
    Ensemble model of Artificial Neural Networks with randomized number of hidden neurons

    Ensemble model of Artificial Neural Networks with randomized number of hidden neurons by Fatai Adesina, Anifowose, Jane, Labadin

    Published 2013
    “…Ten base learners of the ANN model were created with each using a randomly generated number of hidden neurons. …”
    Get full text
    Get full text
    Get full text
    Proceeding
    Save to List
    Saved in:
  2. 2
    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization

    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2015
    “…This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  3. 3
    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization

    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2014
    “…This paper presents a classification of android malware using candidate detectors generated from an unsupervised association rule of Apriori algorithm improved with particle swarm optimization to train three different supervised classifiers. …”
    Get full text
    Get full text
    Get full text
    Proceeding Paper
    Save to List
    Saved in:
  4. 4
    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  5. 5
    Bridging Mayer’s cognitive theory of multimedia learning and computational thinking in tackling the cognitive load issues among young digital natives : a conceptual framework

    Bridging Mayer’s cognitive theory of multimedia learning and computational thinking in tackling the cognitive load issues among young digital natives : a conceptual framework by Wan Nor Ashiqin Wan Ali, Wan Ahmad Jaafar Wan Yahaya

    Published 2022
    “…The purpose of this paper is to study the relationship between CT and Mayer’s Cognitive Theory of Multimedia Learning (CTML) on the cognitive load of the learners. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  6. 6
    Reimagining English language learning: a systematic review of AI integration in classroom practice (2019–2024)

    Reimagining English language learning: a systematic review of AI integration in classroom practice (2019–2024) by Ibrahim Brian, Muhammad Shyazzwan

    Published 2025
    “…Based on 48 peer-reviewed empirical studies published between 2019 and 2024, the review explores how AI tools, particularly Natural Language Processing (NLP), Intelligent Tutoring Systems (ITS), and generative AI, support personalized learning, increase engagement, and strengthen skill development among English language learners. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  7. 7
    An automated learner for extracting new ontology relations

    An automated learner for extracting new ontology relations by Amaal Saleh Hassan, Al Hashimy, Narayanan, Kulathuramaiyer

    Published 2013
    “…Also we present a novel approach of learning based on the best lexical patterns extracted, besides two new algorithms the CIA and PS that provide the final set of rules for mining causation to enrich ontologies.…”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  8. 8
    Automated bilateral negotiation with incomplete information in the e-marketplace.

    Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

    Published 2011
    “…The reason is that, SRT algorithm is sensitive to the accuracy of the learned preferences while MGT algorithm can generate Pareto-optimal offers even with an approximation of the learned preferences.…”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  9. 9
    Exploring the unseen: Unleashing the potential of Synthesia AI in pedagogical approaches / Ts. Jacqueline Joseph

    Exploring the unseen: Unleashing the potential of Synthesia AI in pedagogical approaches / Ts. Jacqueline Joseph by Joseph, Jacqueline

    Published 2023
    “…Synthesis AI is an advanced innovation that utilizes AI and deep learning algorithms to create educational videos with a humanlike voice actor. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  10. 10
    Pairwise Test Suite Generation Using Adaptive Teaching Learning-Based Optimization Algorithm with Remedial Operator

    Pairwise Test Suite Generation Using Adaptive Teaching Learning-Based Optimization Algorithm with Remedial Operator by Fakhrud, Din, Kamal Z., Zamli

    Published 2019
    “…Being a NP-complete problem, pairwise test suite generation problem has been addressed using several meta-heuristic algorithms including the Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm in the literature. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  11. 11
    Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China

    Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China by Sattar Hanoon M., Najah Ahmed A., Razzaq A., Oudah A.Y., Alkhayyat A., Feng Huang Y., kumar P., El-Shafie A.

    Published 2024
    “…Three different scenarios are examined, such as scenario1 (SC1): used to predict daily power generation, scenario 2 (SC2): used to predict power generation for monthly prediction and scenario 3 (SC3): used to predict hydropower generation (HPG) seasonally. …”
    Article
    Save to List
    Saved in:
  12. 12
    Clustering ensemble learning method based on incremental genetic algorithms

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  13. 13
    New Learning Models for Generating Classification Rules Based on Rough Set Approach

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…Recently, different models were used to generate knowledge from vague and uncertain data sets such as induction decision tree, neural network, fuzzy logic, genetic algorithm, rough set theory, and others. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  14. 14
    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)

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

    Published 2024
    “…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  15. 15
    Unsupervised learning of image data using generative adversarial network

    Unsupervised learning of image data using generative adversarial network by Rayner Alfred, Lun,, Chew Ye

    Published 2020
    “…Based on the results obtained, the GAN algorithm can learn the internal representation of data without labels and can act as good features extractor. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceedings
    Save to List
    Saved in:
  16. 16
    A review on security and privacy issues in E-learning and the MapReduce aproach

    A review on security and privacy issues in E-learning and the MapReduce aproach by Noor Akma, Abu Bakar, Mazlina, Abdul Majid, Khalid, Adam, Kirahman, Ab Razak, Noorhuzaimi@Karimah, Mohd Noor

    Published 2019
    “…Then, we proposed e-Learning using MapReduce algorithm in protecting the security and privacy of eLearning. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  17. 17
    Next generation insect taxonomic classification by comparing different deep learning algorithms

    Next generation insect taxonomic classification by comparing different deep learning algorithms by Song-Quan Ong, Suhaila Ab. Hamid

    Published 2022
    “…The results show that different taxonomic ranks require different deep learning (DL) algorithms to generate high-performance models, which indicates that the design of an automated systematic classification pipeline requires the integration of different algorithms. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  18. 18
    Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS

    Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

    Published 2017
    “…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  19. 19
    Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation

    Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation by Lateh, Masitah bdul

    Published 2020
    “…From the previous studies, there are solutions to improve learning accuracy and predictive capability where some artificial data will be added to the system using artificial data generation approach. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  20. 20
    Ensemble learning for multidimensional poverty classification

    Ensemble learning for multidimensional poverty classification by Azuraliza Abu Bakar, Rusnita Hamdan, Nor Samsiah Sani

    Published 2020
    “…The goal of this study was to determine whether ensemble learning method (random forest) can classify poverty and hence produce multidimensional poverty indicator compared to based learner method using eKasih dataset. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:

Search Tools: