بدائل البحث:
modeling algorithm » scheduling algorithm (توسيع البحث)
learning algorithm » learning algorithms (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
data modeling » data models (توسيع البحث), spatial modeling (توسيع البحث)
modeling algorithm » scheduling algorithm (توسيع البحث)
learning algorithm » learning algorithms (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
data modeling » data models (توسيع البحث), spatial modeling (توسيع البحث)
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1
Using machine learning algorithm for detection of cyber-attacks in cyber physical systems
منشور في 2022"…Network integration is common in cyber-physical systems (CPS) to allow for remote access, surveillance, and analysis. They have been exposed to cyberattacks because of their integration with an insecure network. …"
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Bird’s Eye View feature selection for high-dimensional data
منشور في 2023"…However, high dimensional data often contains irrelevant features, outliers, and noise, which can negatively impact model performance and consume computational resources. …"
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5
Efficient Approximate Conformance Checking Using Trie Data Structures
منشور في 2021الموضوعات: "…Estimation error,Runtime,Computational modeling,Data structures,Approximation algorithms,Encoding,Computational efficiency…"
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Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms
منشور في 2022"…This was accomplished by (1) extracting reliable LULC information from Sentinel-2 and Landsat-8 s images, (2) generating remote sensing indices used to train ML algorithms, and (3) comparing the results with ground truth data. …"
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Development of an Optimization Algorithm for Internet Data Traffic
منشور في 2020"…In this paper, an optimization algorithm is proposed to reduce net data traffic, which works at Internet layer in the TCP/IP reference model. …"
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10
Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm
منشور في 2024"…This article outlines the input data and partial shading conditions employed in the replication model of Sequential Monte Carlo (SMC)-based tracking techniques for photovoltaic (PV) systems. …"
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11
A Tabu Search algorithm for mapping data to multicomputers. (c1997)
منشور في 1997احصل على النص الكامل
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masterThesis -
12
A neural networks algorithm for data path synthesis
منشور في 2003"…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …"
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13
Allocating data to distributed-memory multiprocessors by genetic algorithms
منشور في 2016"…We present three genetic algorithms (GAs) for allocating irregular data sets to multiprocessors. …"
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14
Variable Selection in Data Analysis: A Synthetic Data Toolkit
منشور في 2024"…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …"
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Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm
منشور في 2023"…Furthermore, a route management technique is combined with Artificial Intelligence (AI) algorithm to transmit the data to appropriate central servers. …"
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17
Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
منشور في 2016احصل على النص الكامل
doctoralThesis -
18
Parallel physical optimization algorithms for allocating data to multicomputer nodes
منشور في 1994"…Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. …"
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19
Physical optimization algorithms for mapping data to distributed-memory multiprocessors
منشور في 1992"…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …"
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masterThesis -
20
Enhancing Healthcare Systems With Deep Reinforcement Learning: Insights Into D2D Communications and Remote Monitoring
منشور في 2024"…The core of DRLLVT is its novel algorithm that leverages Deep Reinforcement Learning (DRL) to dynamically adapt to changing environmental conditions, facilitating real-time decisions that consider node capacities, latency, and the overall network dynamics. …"