Search Results - probable distribution ((matching algorithm) OR (learning algorithm))

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  1. 1

    Novel distributed algorithm for coalition formation for enhanced spectrum sensing in cognitive radio networks by Tahir, Mohammad, Habaebi, Mohamed Hadi, Islam, Md Rafiqul

    Published 2017
    “…We use concepts from matching theory, specifically the stable marriage problem, to formulate the interactions among the cogni- tive radio users as a matching game for collaborative distributed spectrum sensing under target detection probability constraint. …”
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    Article
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    Throughput enhancement in cognitive radio network via coalition formation using matching theory by Tahir, Mohammad, Habaebi, Mohamed Hadi, Islam, Md. Rafiqul

    Published 2015
    “…Index Terms—cognitive radio; spectrum sensing; distributed algorithms; stable matching, matching theory.…”
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    Proceeding Paper
  4. 4

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

    Published 2023
    “…To overcome this limitation, the Q-Learning algorithm was proposed by several researchers to minimise randomness. …”
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    Thesis
  5. 5

    Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions by Goh, Kwang Yi, Baharom, Salmi, Din, Jamilah

    Published 2022
    “…Furthermore, the proposed techniques based on the Q-Learning algorithm do not consider context-based actions. …”
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    Article
  6. 6

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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    Thesis
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    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…These kind of activities highly sparsely distributed in the input space which is problematic to be distinguish using traditional classifier model. …”
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    Thesis
  10. 10

    Adaptive and optimized radio resource allocation algorithms for OFDMA based networks by Saadat, Md. Nazmus

    Published 2015
    “…AORAA contains an adaptive and optimized subcarrier allocation algorithm which uses graph theoretic techniques to do the best probable matching of subcarrier and users’ channel information. …”
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    Thesis
  11. 11

    Energy efficient cluster head distribution in wireless sensor networks by Siew, Zhan Wei

    Published 2013
    “…PSO is lightweight heuristic optimization algorithm with each CH will move towards the best solutions by individual interaction with one another while learning from their own experience. …”
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    Thesis
  12. 12

    Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

    Published 2021
    “…The results indicated that the hydropower generated by the proposed algorithm could produce an evenly distributed high amount of energy increases the reliability of the reservoir system. …”
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    Thesis
  13. 13

    Predictive Framework for Imbalance Dataset by Megat Norulazmi, Megat Mohamed Noor

    Published 2012
    “…Experimental results suggested that the class probability distribution function of a prediction model has to be closer to a training dataset; less skewed environment enable learning schemes to discover better function F in a bigger Fall space within a higher dimensional feature space, data sampling and partition size is appear to proportionally improve the precision and recall if class distribution ratios are balanced. …”
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    Thesis
  14. 14

    Comparative Analysis of Artificial Intelligence Methods for Streamflow Forecasting by YAXING, WEI, HUZAIFA, HASHIM, Lai, Sai Hin, CHONG, KAI LUN, HUANG, YUK FENG, ALI NAJAH, AHMED, MOHSEN, SHERIF, AHMED, EL-SHAFIE

    Published 2024
    “…Deep learning excels at managing spatial and temporal time series with variable patterns for streamflow forecasting, but traditional machine learning algorithms may struggle with complicated data, including non-linear and multidimensional complexity. …”
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    Article
  15. 15

    Prediction of rice biomass using machine learning algorithms by Radhwane, Derraz

    Published 2022
    “…Unmanned aerial vehicles (UAVs) may address these issues. Machine learning algorithms (MLs) can predict rice biomass from UAV-based vegetation indices (VIs). …”
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    Thesis
  16. 16

    Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

    Published 2015
    “…To process large-scale data sequences, it is important to choose a suitable learning algorithm that is capable to learn in real time. …”
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    Thesis
  17. 17

    Development of a hybrid machine learning model for rockfall source and hazard assessment using laser scanning data and GIS by Fanos, Ali Mutar

    Published 2019
    “…This is based on highresolution Light Detection and Ranging (LiDAR) techniques both airborne and terrestrial (ALS and TLS). Different machine learning algorithms (Artificial Neural Network [ANN], K Nearest Neighbor [KNN] and Support Vector Machine [SVM]) were tested individually and with various ensemble models (bagging, voting, and boosting) to detect the probability of the landslide and rockfall occurrences. …”
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    Thesis