Search Results - (( its application learning algorithm ) OR ( mobile application bat algorithm ))*

Search alternatives:

Refine Results
  1. 1
    Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm

    Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm by ,, Dwi Pebrianti, Ann Ayop azmi, Nurnajmi Qasrina, Bayuaji, Luhur, Suarin, Nur Aisyah Syafinaz, ,, Muhammad Syafrullah

    Published 2022
    “…Three different optimization algorithms which are Bat Algorithm (BA), Bat Algorithm with Mutation (BAM) and Extended Bat Algorithm (EBA) are implemented to optimize the value of PID controller gain for wheel mobile robot. …”
    Get full text
    Get full text
    Book Chapter
    Save to List
    Saved in:
  2. 2
    PID controller design for mobile robot using Bat Algorithm with Mutation (BAM)

    PID controller design for mobile robot using Bat Algorithm with Mutation (BAM) by Pebrianti, Dwi, Indra, Riyanto, Bayuaji, Luhur, Muhammad Syafrullah, ., Arumgam, Yogesvaran, Nurnajmin Qasrina, Ann

    Published 2019
    “…Here, an optimization algorithm called Bat Algorithm with Mutation (BAM) is proposed to optimize the value of PID controller gain for mobile robot. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  3. 3
    Multi-Robot Learning with Bat Algorithm With Mutation (Bam)

    Multi-Robot Learning with Bat Algorithm With Mutation (Bam) by Chandrathevan, Sathiamurthy

    Published 2022
    “…BAT algorithm is implemented to achieve the target. …”
    Get full text
    Get full text
    Undergraduates Project Papers
    Save to List
    Saved in:
  4. 4
    Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali

    Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali by Ihsan , Ali

    Published 2024
    “…To address relay node selection and data scheduling issues, Energy-Efficient Scheduling (EES) and Energy-Efficient Un-Scheduling (EEUS) methods have been introduced using the Improved Discrete Bat Algorithm (IDBA) along with the Adaptive Warshal Floyd algorithm (AWF). …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  5. 5
    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff

    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

    Published 2017
    “…Thus, it can be concluded that QEEA algorithm is the most energy efficient and the best candidate for provisioning the QoS for the real time (RT) and non-real time (NRT) applications.…”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  6. 6
    Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network

    Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network by Azian Azamimi, Uwate, Yoko, Nishio, Yoshifumi

    Published 2010
    Subjects: Get full text
    Working Paper
    Save to List
    Saved in:
  7. 7
    A modified generalized RBF model with EM-based learning algorithm for medical applications

    A modified generalized RBF model with EM-based learning algorithm for medical applications by Ma, Li Ya, Abdul Rahman, Abdul Wahab, Quek, Chai

    Published 2006
    “…Radial Basis Function (RBF) has been widely used in different fields, due to its fast learning and interpretability of its solution. …”
    Get full text
    Get full text
    Get full text
    Proceeding Paper
    Save to List
    Saved in:
  8. 8
    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA

    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

    Published 2012
    “…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  9. 9
    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection

    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…Two main improvements were included into the original SSA algorithm to alleviate its drawbacks and adapt it for feature selection problems. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  10. 10
    Q-learning whale optimization algorithm for test suite generation with constraints support

    Q-learning whale optimization algorithm for test suite generation with constraints support by Hassan, Ali Abdullah, Salwani, Abdullah, Kamal Z., Zamli, Rozilawati, Razali

    Published 2023
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  11. 11
    Ensemble dual recursive learning algorithms for identifying flow with leakage

    Ensemble dual recursive learning algorithms for identifying flow with leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  12. 12
    Active force control with iterative learning control algorithm for a vehicle suspension

    Active force control with iterative learning control algorithm for a vehicle suspension by Rosmazi, Rosli

    Published 2013
    “…The research focuses on the application of an active force control (AFC) strategy with iterative learning control (ILC) algorithms to compensate for the various introduced road profiles or 'disturbances' in a quarter car suspension system as an improvement to ride comfort performance. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  13. 13
    Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding

    Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding by Mahmoud, Omer, Anwar, Farhat, Salami, Momoh Jimoh Emiyoka

    Published 2007
    “…The essence of this study is to investigate the most efficient and effective training methods for use in image compression and its subsequent applications. The obtained results show that the Quasi-Newton based algorithm has better performance as compared to the other two algorithms.…”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  14. 14
    FASTA-ELM: a fast adaptive shrinkage/thresholding algorithm for extreme learning machine and its application to gender recognition

    FASTA-ELM: a fast adaptive shrinkage/thresholding algorithm for extreme learning machine and its application to gender recognition by Mahmood, Saif F., Marhaban, Mohammad Hamiruce, Rokhani, Fakhrul Zaman, Samsudin, Khairulmizam, Arigbabu, Olasimbo Ayodeji

    Published 2017
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  15. 15
    Machine learning: tasks, modern day applications and challenges

    Machine learning: tasks, modern day applications and challenges by Aljuaid, Lamyaa Zaed, Koh, Tieng Wei, Sharif, Khaironi Yatim

    Published 2019
    “…Machine learning algorithms learned from available data. Further, this learning laid the foundation to develop AI for the various systems around us. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  16. 16
    Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic

    Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

    Published 2004
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  17. 17
    Global-Local Partial Least Squares Discriminant Analysis And Its Extension In Reproducing Kernel Hilbert Space

    Global-Local Partial Least Squares Discriminant Analysis And Its Extension In Reproducing Kernel Hilbert Space by Muhammad, Aminu

    Published 2021
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  18. 18
    Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm

    Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

    Published 2018
    “…Type 2 fuzzy logic system has more parameters than the type 1 fuzzy logic system and is therefore much more complex than its counterpart. This paper proposes optimal parameters for an extreme learning machine-based interval type 2 fuzzy logic system to learn its best configuration. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  19. 19
    Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems

    Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems by Abdul Hamid, Norhamreeza, Mohd Nawi, Nazri, Ghazali, Rozaida, Mohd Salleh, Mohd Najib

    Published 2011
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  20. 20
    Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing

    Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing by Goh, Kwang Yi

    Published 2023
    “…We enhanced the Q-Learning algorithm for action selection based on potential action abilities and proposed a tool, namely CrashDroid, that allows the automation of testing context-aware Android applications. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:

Search Tools: