Search Results - (( intelligence based aims algorithm ) OR ( intelligence based m algorithm ))

Refine Results
  1. 1
  2. 2

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…The dissertation aims to develop an effectively decomposed time-series nongradient- based artificial intelligence model for forecasting a time-series regression machine learning task. …”
    Get full text
    Get full text
    Get full text
    Thesis
  3. 3
  4. 4

    Hybrid bat algorithm for minimum dominating set problem by Abed, S.A., Rais, H.M.

    Published 2017
    “…However, population-based algorithms are not good in exploiting the search space in comparison to single-solution based methods, therefore we included simulated annealing (SA) algorithm to balance between exploitation and exploration in order to reach a best possible solution. …”
    Get full text
    Get full text
    Article
  5. 5

    A Novel Path Prediction Strategy for Tracking Intelligent Travelers by Motlagh, Omid Reza Esmaeili

    Published 2009
    “…It is proposed and shown that route-like intelligent motion is based on a combination of decisional and kinematical factors. …”
    Get full text
    Get full text
    Thesis
  6. 6
  7. 7

    African Buffalo Optimization by Odili, Julius Beneoluchi, M. N. M., Kahar

    Published 2016
    “…This paper presents an overview of major metaheuristic algorithms with the aim of providing a basis for the development of the African Buffalo Optimization algorithm which is a nature-inspired, population-based metaheuristic algorithm. …”
    Get full text
    Get full text
    Get full text
    Article
  8. 8
  9. 9
  10. 10
  11. 11
  12. 12

    Artificial Intelligence Forecasting for Transmission Line Ampacity by Hamed Y., Abd Rahman M.S., Ab Kadir M.Z.A., Osman M., Ariffin A.M., Ab Aziz N.F.

    Published 2023
    “…Dynamic line ratings can be modelled physically, statistically, and using machine learning and artificial intelligence. This chapter aims to address the implementation of machine learning and artificial intelligence algorithms in predicting the DLR of transmission systems. …”
    Book Chapter
  13. 13

    Conventional and intelligent models for detection and prediction of fluid loss events during drilling operations: a comprehensive review by Krishna, Shwetank, Ridha, Syahrir, Vasant, Pandian M., Ilyas, Suhaib Umer, Sophian, Ali

    Published 2020
    “…These predictive and detecting models comprise of Artificial Intelligence (AI) algorithms that require improvements for data reduction, universal prediction and compatibility. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  14. 14
  15. 15
  16. 16
  17. 17
  18. 18
  19. 19
  20. 20