Search Results - (( parallel optimization bees algorithm ) OR ( variable extracting sensor algorithm ))

  • Showing 1 - 12 results of 12
Refine Results
  1. 1

    Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function by Hammash, Nayif Mohammed

    Published 2012
    “…This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. …”
    Get full text
    Get full text
    Get full text
    Thesis
  2. 2

    Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm by Mohd Abdul Hadi, Osman, Mohd Fadzil Faisae, Ab Rashid, Nik Mohd Zuki, Nik Mohamed, Muhammad Ammar, Nik Mu’tasim

    Published 2024
    “…Through an extensive computational experiment involving a well-known benchmark suite, the ABC algorithm demonstrated remarkable performance, consistently outperforming several popular metaheuristic algorithms, including Genetic Algorithms, Particle Swarm Optimization, Memetic Algorithms, and Whale Optimization Algorithm in 75% of the problems. …”
    Get full text
    Get full text
    Get full text
    Article
  3. 3

    Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib by Dian Najihah , Abu Talib

    Published 2019
    “…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
    Get full text
    Get full text
    Get full text
    Thesis
  4. 4
  5. 5
  6. 6

    Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study by Wenjun, Ji, Adamchuk, Viacheslav I., Song, Chao Chen, Mat Su, Ahmad S., Ismail, Ashraf, Qianjun, Gan, Zhou, Shi, Biswas, Asim

    Published 2019
    “…In this field, it was not possible to predict extractable P and K using all tested sensor combinations or algorithms. …”
    Get full text
    Get full text
    Article
  7. 7
  8. 8

    Google the earth: what's next? by Mansor, Shattri

    Published 2010
    “…Technologically, the challenge is to design sensors that exhibit high sensitivity to the parameters of interest while minimizing instrument noise and impacts of other natural variables. …”
    Get full text
    Get full text
    Get full text
    Inaugural Lecture
  9. 9

    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid by Gaeid, Khalaf Salloum

    Published 2012
    “…The fault detection algorithm identifies the time and location of each fault. …”
    Get full text
    Get full text
    Thesis
  10. 10

    New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams by Immad , Shams

    Published 2022
    “…Despite the effective proposed GMPPT algorithm, the PSCs reduce the maximum power extraction capability of the PV system heavily due to the activation of bypass diodes. …”
    Get full text
    Get full text
    Get full text
    Thesis
  11. 11

    Oil palm female inflorescences anthesis stages identification using selected emissivities through thermal imaging and Machine Learning by Yousefidashliboroun, Mamehgol

    Published 2022
    “…This research studies different Machine Learning (ML) classification and ensemble techniques for the assessment of the four pollination stages consist of pre-anthesis I, pre-anthesis II, pre-anthesis III, and anthesis using thermal imaging. Different ML algorithms such as Random Forest (RF), k Nearest Neighbor (kNN), Support Vector Machine (SVM), Artificial Neural Network (ANN) as well as an ensemble method are used on data extracted from thermal images collected during infield oil palms pollination stages monitoring. …”
    Get full text
    Get full text
    Get full text
    Thesis
  12. 12

    Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm by Ahmadi, Seyedeh Parisa

    Published 2018
    “…In the first phase, spectral features and structural features were extracted for feature extraction. In the spectral features part, the descriptors include red (R), green (G), blue (B), near-infrared (NIR) digital numbers and a vegetation index (VI) was considered. …”
    Get full text
    Get full text
    Get full text
    Thesis