Search Results - (( probable distribution learning algorithm ) OR ( protocol distributed learning algorithm ))
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Energy efficient cluster head distribution in wireless sensor networks
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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Incremental learning for large-scale stream data and its application to cybersecurity
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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Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing
Published 2023“…To overcome this limitation, the Q-Learning algorithm was proposed by several researchers to minimise randomness. …”
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Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions
Published 2022“…Furthermore, the proposed techniques based on the Q-Learning algorithm do not consider context-based actions. …”
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Mitigating Slow Hypertext Transfer Protocol Distributed Denial of Service Attacks in Software Defined Networks
Published 2021“…This study contributes to the ongoing research in detecting and mitigating slow HTTP DDoS attacks with emphasis on the use of machine learning classification and meta-heuristic algorithms.…”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
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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Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques
Published 2011“…In machine learning algorithm, choosing the most relevant features for each attack is a very important requirement, especially in mobile ad hoc networks where the network topology dynamically changes. …”
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A stable energy balancing based clustering routing protocol for IoUT using meta-heuristic technique
Published 2024“…The proposed method enable to optimization the IoUT energy efficiency by balancing strategy that uses the Q-learning algorithm to ensure more balanced distribution of tasks across UNs and CHs. …”
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Benchmarking Robust Machine Learning Models Under Data Imperfections in Real-World Data Science Scenarios
Published 2026“…Multiple classical machine learning algorithms and deep learning models were assessed across diverse benchmark datasets. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
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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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / 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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Review of energy conservation using duty cycling schemes for IEEE 802.15.4 wireless sensor network (WSN)
Published 2014“…This paper reviews several duty cycle mechanisms in WSN such as Duty Cycle Learning Algorithm, adaptive media access control (MAC) protocol for efficient IEEE 802.15.4 (AMPE), distributed duty cycle management (DDCM), distributed duty cycle management low power broadcast (DDCM + LPB) and distributed beacon only period. …”
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Predictive Framework for Imbalance Dataset
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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Comparative Analysis of Artificial Intelligence Methods for Streamflow Forecasting
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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Prediction of rice biomass using machine learning algorithms
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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