Suchergebnisse - Parallel machine learning algorithm

Application of genetic algorithm in optimization parallel ensemble-based machine learning algorithms to flood susceptibility mapping using radar satellite imagery von Razavi-Termeh, Seyed Vahid, Sadeghi-Niaraki, Abolghasem, Seo, MyoungBae, Choi, Soo-Mi

“… This study employed a genetic algorithm (GA) to fine-tune parallel ensemble-based machine learning algorithms (random forest (RF …”
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A Genetic Algorithm Approach to Parallel Machine Scheduling Problems Under Effects of Position-Dependent Learning and Linear Deterioration: Genetic Algorithm to Parallel Machine Scheduling Problems von Arık, Oğuzhan Ahmet, Toksarı, Mehmet Duran

“… This paper investigates parallel machine scheduling problems where the objectives are to minimize total completion times under effects of learning and deterioration …”
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Why Dataset Properties Bound the Scalability of Parallel Machine Learning Training Algorithms von Cheng, Daning, Li, Shigang, Zhang, Hanping, Xia, Fen, Zhang, Yunquan

“… However, the scalability and performance reproducibility of parallel machine learning training, which mainly uses stochastic optimization algorithms, are limited …”
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High-performance medical data processing technology based on distributed parallel machine learning algorithm von Liu, Ji, Liang, Xiao, Ruan, Wenxi, Zhang, Bo

“… Here, a Bilayer Parallel Training-Convolutional Neural Network (BPT-CNN) model based on distributed computing is proposed to detect and classify colon cancer nuclei more accurately through the large-scale parallel deep learning (DL) algorithm …”
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Parallel Machine Learning Algorithm Using Fine-Grained-Mode Spark on a Mesos Big Data Cloud Computing Software Framework for Mobile Robotic Intelligent Fault Recognition von Xian, Guangming

“… To improve the efficiency of intelligent fault classification of mobile robotic roller bearings, this paper proposes a parallel machine learning algorithm using fine-grained-mode Spark on a Mesos big …”
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A revised deep reinforcement learning algorithm for parallel machine scheduling problem under multi-scenario due date constraints von Zhang, Weijian, Kong, Min, Zhang, Yajing, Fathollahi-Fard, Amir M., Tian, Guangdong

“… •Proposing parallel machine scheduling problem in storage chip manufacturing under strong and weak due date constraints …”
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A K-means-Teaching Learning based optimization algorithm for parallel machine scheduling problem von Li, Yibing, Liu, Jie, Wang, Lei, Liu, Jinfu, Tang, Hongtao, Guo, Jun, Xu, Wenxiang

“… A data mining method was proposed for industrial big data to solve the problem of large-scale parallel machines scheduling …”
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Dynamic Distributed and Parallel Machine Learning algorithms for big data mining processing von Djafri, Laouni

“… PurposeThis work can be used as a building block in other settings such as GPU, Map-Reduce, Spark or any other. Also, DDPML can be deployed on other …”
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Exact and heuristic algorithms for parallel-machine scheduling with DeJong’s learning effect von Okołowski, Dariusz, Gawiejnowicz, Stanisław

“… We consider a parallel-machine scheduling problem with a learning effect and the makespan objective …”
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Advanced Analytics in Smart Manufacturing: Anomaly Detection Using Machine Learning Algorithms and Parallel Machine Scheduling Using a Genetic Algorithm von He, Meiling

“… Making good use of data processing technologies, such as machine learning and optimization algorithms, will significantly contribute to better quality control, automation, and job scheduling in Smart Manufacturing …”
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Hadoop based Parallel Machine Learning Algorithms for Intrusion Detection System von Eswaran, Malathi, Balasubramanie, P., Jotheeswari, M.

“… Choice Tree is another Machine Learning classifier which is likewise an administered learning model …”
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Machine-Learning-Based Parallel Genetic Algorithms for Multi-Objective Optimization in Ultra-Reliable Low-Latency WSNs von Chang, Yuchao, Yuan, Xiaobing, LI, Baoqing, Niyato, Dusit, Al-Dhahir, Naofal

“… by applying machine learning techniques and genetic algorithms. Using the <inline-formula> <tex-math notation="LaTeX">K </tex-math></inline-formula>-means clustering …”
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Incremental and Parallel Machine Learning Algorithms With Automated Learning Rate Adjustments von Hishinuma, Kazuhiro, Iiduka, Hideaki

“… The existing machine learning algorithms for minimizing the convex function over a closed convex set suffer from slow convergence because their learning rates must be determined before running …”
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A Parallel Multiclassification Algorithm for Big Data Using an Extreme Learning Machine von Duan, Mingxing, Li, Kenli, Liao, Xiangke, Li, Keqin

“… Although a parallel ELM (PELM) based on MapReduce to process large-scale data shows more efficient learning speed than identical ELM algorithms in a serial environment, some operations, such as intermediate results stored on disks …”
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Reducing Execution Time of Pixel-Based Machine Learning Classification Algorithms Using Parallel Processing Concept von Aliaa Shaker Mahmoud, Mohammed Chachan Younis

“… Parallel processing is essential in machine learning to meet the computational requirements resulting from the complexity of algorithms and the size of the dataset, by taking advantage …”
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Parallel Implementation of a Machine Learning Algorithm on GPU von Cuomo, Salvatore, De Michele, Pasquale, Di Nardo, Emanuel, Marcellino, Livia

“… of the information itself and its potential. Machine learning explores the study and construction of algorithms that can learn from and make predictions on data …”
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An evolution strategies-based reinforcement learning algorithm for multi-objective dynamic parallel machine scheduling problems von Chen, Yarong, Zhang, Junjie, Mumtaz, Jabir, Huang, Shenquan, Zhou, Shengwei

“… •Proposed evolution strategies-based reinforcement learning algorithm.•A multi-agent system to generate scheduling policy for parallel machines …”
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Parallel and Distributed Machine Learning Algorithms for Scalable Big Data Analytics von Bal, Henri, Pal, Arindam

“… for Large Scale Machine Learning and Big Data Analytics (ParLearning 2017). In this editorial, we have given a high-level overview of the 4 papers contained …”
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Novel decoupling algorithm based on parallel voltage extreme learning machine (PV-ELM) for six-axis F/M sensors von Liang, Qiaokang, Long, Jianyong, Coppola, Gianmarc, Zhang, Dan, Sun, Wei

“… ), Support Vector Regression (SVR), BP Neural Network (BPNN), and Extreme Learning Machine (ELM) methods …”
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Study on micro-parameters of parallel bond model based on machine learning algorithm von Du, Xiaotong, Liu, Wanrong, Peng, Chao, Huang, Bin, Xu, Congmin, Sun, Yulin, Cheng, Yudi

“… This paper employs the discrete element software PFC 2D in combination with four machine learning algorithms …”
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