Search Results - (( parallel distribution factor algorithm ) OR ( protocol directed learning algorithm ))

Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

“…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. …”

Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes by Mohammad Sigit Arifianto, Tze, Kenneth Kin Teo, Liau, Chung Fan, Liawas Barukang, Zaturrawiah Ali Omar

“…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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Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design by Haohao, Ma, As’arry, Azizan, Yanwei, Feng, Lulu, Cheng, Delgoshaei, Aidin, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi

“…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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Spatio-temporal event association using reward-modulated spike-time-dependent plasticity by Yusoff, Nooraini, Ibrahim, Mohammed Fadhil

“…For goal-directed learning in spiking neural networks, target spike templates are usually required.Optimal performance is achieved by minimising the error between the desired and output spike timings.However, in some dynamic environments, a set of learning targets with precise encoding is not always available.For this study, we associate a pair of spatio-temporal events with a target response using a reinforcement learning approach.The learning is implemented in a recurrent spiking neural network using reward-modulated spike-time-dependent plasticity.The learning protocol is simple and inspired by a behavioural experiment from a neuropsychology study.For a goal-directed application, learning does not require a target spike template.In this study, convergence is measured by synchronicity of activities in associated neuronal groups.As a result of learning, a network is able to associate a pair of events with a temporal delay in a dynamic setting. …”
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Design and analysis of management platform based on financial big data by Chen, Yuhua, Mustafa, Hasri, Zhang, Xuandong, Liu, Jing

“…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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Distributed denial of service attack in HTTP/2: review on security issues and future challenges by Liang Ming, Leau, Yu-Beng, Ying Xie

“…Additionally, it highlights the potential applicability of deep learning algorithms in the context of the HTTP/2 protocol. …”
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Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

“…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 review of deep learning-based defect detection and panel localization for photovoltaic panel surveillance system by Mohamed Ameerdin, Muhammad Irshat, Jamaluddin, Muhammad Herman, Shukor, Ahmad Zaki, Mohamad, Syazwani

“…This review introduces an integrated deep learning framework that leverages Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and You Only Look Once (YOLO) algorithms to enhance defect detection in solar panels. …”
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Energy efficient cluster head distribution in wireless sensor networks by Siew, Zhan Wei

“…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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Conjunctions in biological neural architectures for visual pose estimation / Tom´As Maul by Tom´As, Maul

“…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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Artificial neural network algorithm for predicting the surface roughness in end milling of Inconel 718 alloy by Hossain, Mohammad Ishtiyaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

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Comparative evaluation of anomaly-based controller area network IDS by Sharmin, Shaila, Mansor, Hafizah, Abdul Kadir, Andi Fitriah, Abdul Aziz, Normaziah

“…This work contributes to these efforts by reporting results of the comparative evaluation of four statistical and two machine learning-based CAN intrusion detection algorithm, against the Real ORNL Automotive Dynamometer (ROAD) CAN intrusion dataset. …”
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Two-stage strategic optimal planning of distributed generators and energy storage systems considering demand response program and network reconfiguration by Ba-swaimi S., Verayiah R., Ramachandaramurthy V.K., ALAhmad A.K., Padmanaban S.

Advancements in battery technologies and management systems for electric vehicles A mini-review by Shanmuganathan, Elengespwaran, Norazlianie, Sazali, Kettner, Maurice, Salim, Naqib, Ismayuzri, Ishak

“…Additionally, the role of simulation tools such as Simulink in evaluating various charging methodologies is discussed, highlighting their significance in optimizing charging protocols. The review also examines developments in direct current (DC) fast charging infrastructure, including technologies such as Tesla’s Superchargers and AVL’s advanced charging solutions, which aim to provide rapid and efficient charging while addressing thermal and electrochemical challenges. …”
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Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

“…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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Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

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