Search Results - adoption over different ((estimation algorithm) OR (optimization algorithm))

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  1. 1

    Automatic control of flotation process using computer vision by Saravani, Ali Jahed

    Published 2015
    “…Bubble size distribution which is regarded as the most important characteristics of froth structure, is being addressed in this thesis by using a segmentation algorithm. A marker based watershed algorithm had been adopted and improved so as to prevent the over segmentation of big bubbles and able to adapt itself with different scenario of froth images. …”
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    Thesis
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  3. 3

    Performance Modeling And Size Optimization Of A Standalone Photovoltaic System by Abdul Qayoom, Jakhrani

    Published 2013
    “…The proposed optimal sizing method determines the required PV array area and battery storage capacity for the system load with least possible cost and predefined power reliability.The results of the adopted models and developed sizing method were validated by conducting sensitivity analysis of model parameters. …”
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    Thesis
  4. 4

    End-to-end DVB-S2X system design with deep learning-based channel estimation over satellite fading channels by Mfarej, Sumaya Dhari Awad

    Published 2021
    “…The Normalized Mean Square Error (NMSE) and the BER perfor�mances for different DVB-S2X system MODCODs are investigated and the results for these algorithms are compared with the conventional Minimum Mean Square Er�ror (MMSE) and Least Square (LS) channel estimation techniques. …”
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    Thesis
  5. 5

    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. …”
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    Proceeding Paper
  6. 6

    Improved Malware detection model with Apriori Association rule and particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2019
    “…Particle swarm optimization (PSO) is used to optimize the random generation of candidate detectors and parameters associated with apriori algorithm (AA) for features selection. …”
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    Article
  7. 7

    Development of two matheuristics for production-inventory-distribution routing problem / Dicky Lim Teik Kyee by Dicky Lim , Teik Kyee

    Published 2018
    “…Whilst in MatHeuristic2, we adopt a slightly different approach. The algorithm starts with the pre-processing stage where the routes are determined to act as input to the MIP in Phase 1. …”
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    Thesis
  8. 8

    A bit-serial sum of absolute difference accelerator for variable block size motion estimation of H.264 by Fatemi, M.R.H., Ates, H.F., Salleh, R.

    Published 2009
    “…In this paper, we propose the first least significant bit (LSB) bit-serial sum of absolute difference (SAD) hardware accelerator for integer variable block size motion estimation (VBSME) of H.264. …”
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    Conference or Workshop Item
  9. 9

    Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud by Shariff, S. Sarifah Radiah, Hud, Hady

    Published 2023
    “…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. Every algorithm makes its own respective prior assumptions about the relationships between the features and target variables, which create different types and levels of bias. …”
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    Book Section
  10. 10

    Designing substitution boxes based on chaotic map and globalized firefly algorithm by Ahmed, Hussam Alddin Shihab

    Published 2019
    “…This thesis aim to provide a new design for 8 × 8 S-boxes based on firefly algorithm (FA) optimization. The FA is a newly developed metaheuristic algorithm inspired by fireflies and their flash lighting process. …”
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    Thesis
  11. 11

    Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid by Abdul Hamid, Zulkiffli

    Published 2013
    “…At first, in producing a good optimization algorithm, a hybridization technique was proposed for adopting the finest features of two different algorithms; namely the Genetic Algorithm (GA) and continuous domain Ant Colony Optimization (ACOr). …”
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    Thesis
  12. 12

    Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid by Abdul Hamid, Zulkiffli

    Published 2013
    “…At first, in producing a good optimization algorithm, a hybridization technique was proposed for adopting the finest features of two different algorithms; namely the Genetic Algorithm (GA) and continuous domain Ant Colony Optimization (ACOr). …”
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    Thesis
  13. 13

    SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

    Published 2016
    “…Over the past short time, network security facing a lot of challenges. …”
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    Conference or Workshop Item
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    Temporal integration based factorization to improve prediction accuracy of collaborative filtering by Al-Qasem, Al-Hadi Ismail Ahmed

    Published 2016
    “…The TemporalMF++ approach relies on the k-means algorithm and the bacterial foraging optimization algorithm. …”
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    Thesis
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    Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data by Fanos, Ali Mutar, Pradhan, Biswajeet, Mansor, Shattri, Md Yusoff, Zainuddin, Abdullah, Ahmad Fikri, Jung, Hyung Sup

    Published 2019
    “…In addition, this technique has achieved excellent accuracies (ROC = 95%) over other methods used. Moreover, the proposed model has achieved the optimal prediction accuracies (92%) on the basis of testing data, thereby indicating that the model can be generalised and replicated in different regions, and the proposed method can be applied to various landslide studies.…”
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    Article
  17. 17

    The Impact of Starting Positions and Breathing Rhythms on Cardiopulmonary Stress and Post-Exercise Oxygen Consumption after High-Intensity Metabolic Training: A Randomized Crossove... by Li, Yuanyuan, Wang, Jiarong, Li, Yuanning, Li, Dandan

    Published 2024
    “…Results: Under free breathing, only the maximum POCR differed significantly between standing and prone positions, with prone positions showing higher stress (mean difference = 3.15, p < 0.001). …”
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    Article
  18. 18

    Control of polystyrene batch reactors using neural network based model predictive control (NNMPC): an experimental investigation by Hosen, M.A., Hussain, Mohd Azlan, Mjalli, F.S.

    Published 2011
    “…In this approach, a neural network model is trained to predict the future process response over the specified horizon. The predictions are passed to a numerical optimization routine which attempts to minimize a specified cost function to calculate a suitable control signal at each sample instant. …”
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    Article
  19. 19

    Multi-user beamforming, fairness and device-to-device channel state information sharing in downlink non-orthogonal multiple access systems by Abdulhussein, Mohanad Mohammed

    Published 2021
    “…Simulation results show that the proposed PF-SUS-SIR clustering algorithm significantly improves user fairness with at least 38.96% over conventional SUS-SIR clustering algorithm while maintaining the total system throughput (near maximum). …”
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    Thesis
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    Enhancing clustering algorithm with initial centroids in tool wear region recognition by Kasim, Nur Adilla, Nuawi, Mohd Zaki, Abdul Ghani, Jaharah, Ngatiman, Nor Azazi, Che Haron, Che Hassan, Muhammad Rizal

    Published 2020
    “…The analysis threshold represents a natural-sorted input vector as Z-rot coefficient (RZ) corresponds to the number of cutting accomplish a strong correlation (R2 = 0.8511) over wear evolution. The clustering system adopted a new calculation of initial centroids has successfully determined the three regions for only a single assignment and achieving the optimal distance squared through eight given data sets. …”
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    Article