Search Results - (( parallel distribution factor algorithm ) OR ( protocol distributed learning algorithm ))
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes
Published 2007“…Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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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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Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design
Published 2024“…The Good Point Set (GPS), nonlinear convergence factor, and adaptive t-distribution method improve BKA, which enhances exploration and exploitation performance, convergence speed, and solution quality. …”
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Design and analysis of management platform based on financial big data
Published 2023“…In addition, a financial data management platform based on distributed Hadoop architecture is designed, which combines MapReduce framework with the fuzzy clustering algorithm and the local outlier factor (LOF) algorithm, and uses MapReduce to operate in parallel with the two algorithms, thus improving the performance of the algorithm and the accuracy of the algorithm, and helping to improve the operational efficiency of enterprise financial data processing. …”
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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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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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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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Conjunctions in biological neural architectures for visual pose estimation / Tom´As Maul
Published 2006“…A highly parallel approach based on simple inter-map conjunctions, or correspondence distributions, is chosen and tested on synthetic and real patterns. …”
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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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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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Software agent as an effective tool for managing the Internet of thing data complexity
Published 2017“…On top of that, the existing analysis tools and algorithms did not consider the data generated by sensory devices connected to the Internet. …”
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