Search Results - adaptive over different ((optimization algorithm) OR (detection algorithm))

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  1. 1

    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
    “…In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. …”
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    Article
  2. 2

    A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network by Mustapha, Ibrahim

    Published 2016
    “…Simulation results show convergence, learning and adaptability of the RL based algorithms to dynamic environment toward achieving the optimal solutions. …”
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    Thesis
  3. 3

    An Optimal Design of Moving Objects Tracking Algorithm on FPGA by Elkhatib, Lina, Hussin, Fawnizu Azmadi, Xia, Likun, Sebastian , Patrick

    Published 2012
    “…The system implements a large amount of operations in order to apply a tracking algorithm called Adaptive Hybrid Difference. Two core units were built to implement the algorithm on FPGA, the adaptive threshold unit and the binary image builder unit. …”
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    Conference or Workshop Item
  4. 4

    An optimal design of moving objects tracking algorithm on FPGA by Elkhatib, Lina Noaman, Hussin, Fawnizu Azmadi, Xia, Likun, Sebastian , Patrick

    Published 2010
    “…The system implements a large amount of operations in order to apply a tracking algorithm called Adaptive Hybrid Difference. Two core units were built to implement the algorithm on FPGA, the adaptive threshold unit and the binary image builder unit. …”
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    Conference or Workshop Item
  5. 5

    An optimal design of moving objects tracking algorithm on FPGA by Elkhatib, Lina, Hussin, Fawnizu Azmadi, Xia, Likun, Sebastian , Patrick

    Published 2012
    “…The system implements a large amount of operations in order to apply a tracking algorithm called Adaptive Hybrid Difference. Two core units were built to implement the algorithm on FPGA, the adaptive threshold unit and the binary image builder unit. …”
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    Conference or Workshop Item
  6. 6

    Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm by Khoo, Thau Soon

    Published 2022
    “…It is difficult and challenging to develop an algorithm that can produce consistent near-optimal solutions even after many runs, average near-optimal solutions that have the least difference in magnitude, broader Pareto set, and iii achieve near-optimal solutions but highly sought after if it is commercially viable. …”
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    Final Year Project / Dissertation / Thesis
  7. 7

    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…The second taxonomy is a new taxonomy proposed to classify the adaptive DE algorithms in particular into two categories (DE with adaptive parameters and DE with adaptive parameters and strategies) considering the adaptive components used in this algorithm. …”
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    Thesis
  8. 8
  9. 9

    Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling by Al-Betar, Mohammed Azmi

    Published 2010
    “…Three hybridized versions are proposed which are incremental improvements over the preceding version: (i) Modified Harmony Search Algorithm (MHSA); (ii) Harmony Search Algorithm with Multi-Pitch Adjusting Rate (HSA-MPAR), and (iii) Hybrid Harmony Search Algorithm (HHSA). …”
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    Thesis
  10. 10

    Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems by Salih, Dhiadeen Mohammed

    Published 2015
    “…The WNMPC is developed by a proposed algorithm named adaptive updating rule (AUR) used with gradient descent optimization method to minimize a constrained cost function over the prediction and control horizons and to offer a robust control performances. …”
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    Thesis
  11. 11

    Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

    Published 2023
    “…Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. …”
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    Thesis
  12. 12

    Particle swarm optimization in multi-user orthogonal frequency-division multiplexing systems by Lye, Scott Carr Ken

    Published 2013
    “…While maintaining a target Bit Error Rate (BER), adaptive modulation optimizes the selection of modulation scheme and transmit power for each sub-carrier so that spectral efficiency is maximized. …”
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    Thesis
  13. 13

    OPTIMIZING HYBRID ELECTRIC VEHICLE ENERGY UTILIZATION BASED ON PARTICLE SWARM OPTIMIZATION ALGORITHM by Abang Ahmad Latif, Abang Sarbini

    Published 2023
    “…Hybrid electric technology has been adapted in automobiles for over a few decades with the introduction of the Toyota Prius in 1997. …”
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    Final Year Project Report / IMRAD
  14. 14

    Adaptive Traffic Prioritization Algorithm Over Ad Hoc Network Using IEEE 802.11e by Anuar, Ammar

    Published 2016
    “…This thesis proposes an adaptive traffic prioritization algorithm over ad hoc network using IEEE 802.11e standard that defines a set of Quality of Service enhancements for wireless LAN applications through modifications to the Media Access Control (MAC) layer. …”
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    Thesis
  15. 15

    Adaptive genetic algorithm to improve negotiation process by agents e-commerce by Ebadi, Sahar

    Published 2011
    “…The proposed adaptive negotiation model is named Aspirated Genetic Algorithm (AGA) negotiation model which is a hybrid negotiation system composed of different negotiation strategies, Aspiration concept,genetic algorithm and Bayesian learning. …”
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    Thesis
  16. 16

    Simulated real-time controller for tuning algorithm using modified hill climbing approach by Ahmed, Ahmed Abdulelah

    Published 2014
    “…Often, it is necessary to calibrate a certain parameters of a control system due to plant parameters fluctuation over time.In this research, an intelligent algorithmic tuning technique suitable for realtime system tuning based on hill climbing optimization algorithm and model reference adaptive control system (MRAC) technique is proposed. …”
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    Thesis
  17. 17

    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
    “…Improved predictions were observed for most soil properties based on sensor data fusion than those based on individual sensors. After choosing the optimal sensor combination for each soil property, the predictive capability was compared using different data mining algorithms, including support vector machines (SVM), random forest (RF), multivariate adaptive regression splines (MARS), and regression trees (CART). …”
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    Article
  18. 18

    Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

    Published 2009
    “…Such automated systems must rely on robust and effective algorithms for detection and prediction. Approach: The proposed detection system of epileptic seizure in EEG signals is based on Discrete Wavelet Transform (DWT) and Swarm Negative Selection (SNS) algorithm. …”
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    Article
  19. 19

    An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan by Ullah, S., Daud, H., Dass, S.C., Hadi, F.-T., Khalil, A.

    Published 2018
    “…However, the main problem with the EigenSpot method is that it cannot be adapted to detect more than one spatiotemporal hotspot. …”
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  20. 20

    An eigenspace approach for detecting multiple space-time disease clusters: Application to measles hotspots detection in khyber-pakhtunkhwa, Pakistan by Ullah, S., Daud, H., Dass, S.C., Hadi, F.-T., Khalil, A.

    Published 2018
    “…However, the main problem with the EigenSpot method is that it cannot be adapted to detect more than one spatiotemporal hotspot. …”
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    Article