Suchergebnisse - "random tree algorithm"
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1
Autoren: YU, Ning
Quelle: Promet (Zagreb), Vol 36, Iss 6, Pp 1120-1132 (2024)
Promet-Traffic&Transportation
CODEN POMEEZ
Volume 36
Issue 6Schlagwörter: road network planning, shortest path, growth guidance function, Transportation engineering, TA1001-1280, microcirculation traffic, fast search random tree algorithm
Dateibeschreibung: application/pdf
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2
Autoren:
Quelle: Gong-kuang zidonghua, Vol 50, Iss 7, Pp 107-114 (2024)
Schlagwörter: coal mine inspection robot, path planning, rapidly-expanding random tree algorithm, combined potential field, dynamic step size, path smoothing, Mining engineering. Metallurgy, TN1-997
Dateibeschreibung: electronic resource
Relation: https://doaj.org/toc/1671-251X
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3
Path Planning Method for Hydraulic Heavy-duty Manipulators Considering Dynamic Overturning Stability
Autoren:
Quelle: Jixie chuandong, Vol 48, Pp 41-47 (2024)
Schlagwörter: Hydraulic heavy-duty manipulator, Dynamic overturning stability, Improved rapidly-exploring random tree algorithm, Path planning, Mechanical engineering and machinery, TJ1-1570
Dateibeschreibung: electronic resource
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4
Autoren: et al.
Weitere Verfasser: et al.
Quelle: Journal of Applied Artificial Intelligence. 3:1-12
Schlagwörter: predictive model, feature selection method, machine learning, 4. Education, student attrition, random forest, random tree algorithm
Dateibeschreibung: application/pdf
Zugangs-URL: https://erepo.uef.fi/handle/123456789/29111
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5
Autoren: et al.
Weitere Verfasser: et al.
Schlagwörter: machine learning, predictive model, random forest, random tree algorithm, student attrition, feature selection method
Dateibeschreibung: 1-12
Relation: Journal of Applied Artificial Intelligence; https://doi.org/10.48185/jaai.v3i2.601; https://erepo.uef.fi/handle/123456789/29111
Verfügbarkeit: https://erepo.uef.fi/handle/123456789/29111
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6
Autoren: et al.
Quelle: International Journal of Computer (IJC); Vol. 49 No. 1 (2023); 16-29 ; 2307-4523
Schlagwörter: Machine learning, Predictive model, Random Forest, Random Tree algorithm, Student Attrition, Feature selection method, (Java Virtual Machine (JVM), Netbeans Integrated Software Development Environment (IDE), Weka Tool, Weka Plugin
Dateibeschreibung: application/pdf
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7
Autoren:
Quelle: Mathematics ; Volume 10 ; Issue 15 ; Pages: 2555
Schlagwörter: driverless, artificial potential field method, rapidly exploring random tree algorithm, model predictive control
Dateibeschreibung: application/pdf
Relation: E1: Mathematics and Computer Science; https://dx.doi.org/10.3390/math10152555
Verfügbarkeit: https://doi.org/10.3390/math10152555
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8
Autoren: et al.
Quelle: Journal of Marine Science and Engineering, Vol 10, Iss 1460, p 1460 (2022)
Schlagwörter: ship path planning, inland waters, sampling-based algorithms, rapidly exploring random tree algorithm, obstacle avoidance, Naval architecture. Shipbuilding. Marine engineering, VM1-989, Oceanography, GC1-1581
Relation: https://www.mdpi.com/2077-1312/10/10/1460; https://doaj.org/toc/2077-1312; https://doaj.org/article/da4bfa9ceb6e41a180489b105e82d184
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9
Autoren:
Quelle: ETRI Journal, Vol 40, Iss 4, Pp 471-482 (2018)
Schlagwörter: 0209 industrial biotechnology, walking period, humanoid navigation, particle swarm optimization, TK7800-8360, modified rapidly‐exploring random tree algorithm, Telecommunication, 0202 electrical engineering, electronic engineering, information engineering, continuous footstep planning, TK5101-6720, 02 engineering and technology, Electronics
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10
Autoren: et al.
Quelle: Algorithms, Vol 14, Iss 321, p 321 (2021)
Schlagwörter: mechanical arm, path planning, artificial potential field method, rapid expansion random tree algorithm, virtual new node, Industrial engineering. Management engineering, T55.4-60.8, Electronic computers. Computer science, QA75.5-76.95
Relation: https://www.mdpi.com/1999-4893/14/11/321; https://doaj.org/toc/1999-4893; https://doaj.org/article/a063e29667c54b83a16b5ba3ad50386e
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11
Autoren: et al.
Quelle: Drones, Vol 7, Iss 2, p 145 (2023)
Schlagwörter: unmanned surface vessel, path planning, rapidly exploring random tree algorithm, path tracking, diagonal recurrent neural networks, PI controller, Motor vehicles. Aeronautics. Astronautics, TL1-4050
Dateibeschreibung: electronic resource
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12
Autoren: et al.
Quelle: Aerospace, Vol 2, Iss 2, Pp 171-188 (2015)
Aerospace
Volume 2
Issue 2
Pages 171-188Schlagwörter: A-star algorithm, 0209 industrial biotechnology, flight path planning, 0202 electrical engineering, electronic engineering, information engineering, TL1-4050, rapidly-exploring random tree algorithm, 02 engineering and technology, three-dimensional space, Motor vehicles. Aeronautics. Astronautics
Dateibeschreibung: application/pdf
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13
Autoren: et al.
Quelle: Structural Durability & Health Monitoring ; ISSN: 1930-2983 (Print) ; ISSN: 1930-2991 (Online) ; Volume 11 ; Issue 1
Schlagwörter: K-star, k-nearest neighborhood, k -NN, machine learning approach, condition monitoring, fault diagnosis, roller bearing, decision tree algorithm, J48, random tree algorithm, decision making, two layer feature selection, sound signal, statistical features
Dateibeschreibung: application/pdf
Verfügbarkeit: https://doi.org/10.3970/sdhm.2017.012.001
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14
Autoren:
Schlagwörter: MRI, Decision Tree, CART and Random tree Algorithm
Relation: https://zenodo.org/records/165011; oai:zenodo.org:165011; https://doi.org/10.5281/zenodo.165011
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15
Autoren:
Weitere Verfasser:
Schlagwörter: MATLAB, Robot, TECHNICAL SCIENCES. Computing, A-star, TEHNIČKE ZNANOSTI. Računarstvo, A, A-zvjezdica, Algoritam brzog pretraživanja slučajnih stabala, RRT, Rapidly exploring random tree algorithm
Dateibeschreibung: application/pdf
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