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Wyświetlanie 1-5 z 5
Tytuł:
Multi-population-based algorithm with an exchange of training plans based on population evaluation
Autorzy:
Łapa, Krystian
Cpałka, Krzysztof
Kisiel-Dorohinicki, Marek
Paszkowski, Józef
Dębski, Maciej
Le, Van-Hung
Powiązania:
https://bibliotekanauki.pl/articles/2147148.pdf
Data publikacji:
2022
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
population-based algorithm
multi-population algorithm
hybrid algorithm
island algorithm
subpopulation evaluation
training plan
Opis:
Population Based Algorithms (PBAs) are excellent search tools that allow searching space of parameters defined by problems under consideration. They are especially useful when it is difficult to define a differentiable evaluation criterion. This applies, for example, to problems that are a combination of continuous and discrete (combinatorial) problems. In such problems, it is often necessary to select a certain structure of the solution (e.g. a neural network or other systems with a structure usually selected by the trial and error method) and to determine the parameters of such structure. As PBAs have great application possibilities, the aim is to develop more and more effective search formulas used in them. An interesting approach is to use multiple populations and process them with separate PBAs (in a different way). In this paper, we propose a new multi-population-based algorithm with: (a) subpopulation evaluation and (b) replacement of the associated PBAs subpopulation formulas used for their processing. In the simulations, we used a set of typical CEC2013 benchmark functions. The obtained results confirm the validity of the proposed concept.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 4; 239--253
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Combined YOLOv5 and HRNet for high accuracy 2D keypoint and human pose estimation
Autorzy:
Nguyen, Hung-Cuong
Nguyen, Thi-Hao
Nowak, Jakub
Byrski, Aleksander
Siwocha, Agnieszka
Le, Van-Hung
Powiązania:
https://bibliotekanauki.pl/articles/2147147.pdf
Data publikacji:
2022
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
YOLOv5
HRNet
2D key points estimation
2D human pose estimation
Opis:
Two-dimensional human pose estimation has been widely applied in real-world applications such as sports analysis, medical fall detection, human-robot interaction, with many positive results obtained utilizing Convolutional Neural Networks (CNNs). Li et al. at CVPR 2020 proposed a study in which they achieved high accuracy in estimating 2D keypoints estimation/2D human pose estimation. However, the study performed estimation only on the cropped human image data. In this research, we propose a method for automatically detecting and estimating human poses in photos using a combination of YOLOv5 + CC (Contextual Constraints) and HRNet. Our approach inherits the speed of the YOLOv5 for detecting humans and the efficiency of the HRNet for estimating 2D keypoints/2D human pose on the images. We also performed human marking on the images by bounding boxes of the Human 3.6M dataset (Protocol #1) for human detection evaluation. Our approach obtained high detection results in the image and the processing time is 55 FPS on the Human 3.6M dataset (Protocol #1). The mean error distance is 5.14 pixels on the full size of the image (1000×1002). In particular, the average results of 2D human pose estimation/2D keypoints estimation are 94.8% of PCK and 99.2% of PDJ@0.4 (head joint). The results are available.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 4; 281--298
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Monitoring Vegetation Cover Changes by Sentinel-1 Radar Images Using Random Forest Classification Method
Autorzy:
Tran, Van Anh
Le, Thi Le
Nguyen, Nhu Hung
Le, Thanh Nghi
Tran, Hong Hanh
Powiązania:
https://bibliotekanauki.pl/articles/2020227.pdf
Data publikacji:
2021
Wydawca:
Polskie Towarzystwo Przeróbki Kopalin
Tematy:
vegetation cover change,
Sentinel-1
Random Forest
Binh Duong
Vietnam
Wietnam
wegetacja
Opis:
Vietnam is an Asian country with hot and humid tropical climate throughout the year. Forests account for more than 40% of the total land area and have a very rich and diverse vegetation. Monitoring the changes in the vegetation cover is obviously important yet challenging, considering such large varying areas and climatic conditions. A traditional remote sensing technique to monitor the vegetation cover involves the use of optical satellite images. However, in presence of the cloud cover, the analyses done using optical satellite image are not reliable. In such a scenario, radar images are a useful alternative due to the ability of radar pulses in penetrating through the clouds, regardless of day or night. In this study, we have used multi temporal C band satellite images to monitor vegetation cover changes for an area in Dau Tieng and Ben Cat districts of Binh Duong province, Mekong Delta, Vietnam. With a collection of 46 images between March 2015 and February 2017, the changes of five land cover types including vegetation loss and replanting in 2017 were analyzed by selecting two cases, using 9 images in the dry season of 3 years 2015, 2016 and 2017 and using all of 46 images to conduct Random Forest classifier with 100, 200, 300 and 500 trees respectively. The result in which the model with nine images and 300 trees gave the best accuracy with an overall accuracy of 98.4% and a Kappa of 0.97. The results demonstrated that using VH polarization, Sentinel-1 gives quite a good accuracy for vegetation cover change. Therefore, Sentinel-1 can also be used to generate reliable land cover maps suitable for different applications.
Źródło:
Inżynieria Mineralna; 2021, 2; 441--451
1640-4920
Pojawia się w:
Inżynieria Mineralna
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Flight Height of UAV and Its Influence on the Precise Digital Elevation Model of Complex Terrain
Wysokość lotu UAV i jego wpływ na precyzyjny cyfrowy model wysokości złożonego terenu
Autorzy:
Bui, Xuan Nam
Nguyen, Quoc Long
Le, Thi Thu Ha
Bui, Ngoc Quy
Goyal, Ropesh
Vo, Trong Hung
Pham, Van Chung
Cao, Xuan Cuong
Le, Van Canh
Le, Hong Viet
Powiązania:
https://bibliotekanauki.pl/articles/319327.pdf
Data publikacji:
2020
Wydawca:
Polskie Towarzystwo Przeróbki Kopalin
Tematy:
UAV
DEM
accuracy
complex terrain
open-pit mines
dokładność
złożony teren
kopalnie odkrywkowe
Opis:
The application of lightweight Unmanned Aerial Vehicle (UAV) has been increasingly common in 3D topographic surveys. Especially in the complex terrains such as open-pit mines, where the elevation is rapidly undulating, the UAV based mapping is more efficient, economic and safe compared to the conventional methods. However, one of the most important factors in UAV mapping of complex terrain is the flight altitude which needs to be seriously considered because of the safety and accuracy of generated DEMs. This paper aims to evaluate the influence of flight height on accuracy of DEMs generated for open-pit mines. For this purpose, the selected study area is a quarry with complex terrain located in the Northern Vietnam. The investigation was conducted with five flight heights of 50 m, 100 m, 150 m, 200 m, and 250 m. To assess the accuracy of resulting DEMs, 10 ground control points and 385 checkpoints measured by both GNSS/RTK and total station methods were used. The accuracy of DEM was assessed by using root-mean-square error (RMSE) in X, Y, Z, XY, and XYZ components. The result showed that the DEM models generated at the flight heights of less than 150 m have high accuracy, RMSEs on the 10 GCPs increased from 1.8 cm to 6.2 cm for vertical (Z), and from 2.6 cm to 6.3 cm for horizontal (XY), whereas RMSE on 385 checkpoints increases gradually from 0.05 m to 0.15 m for vertical (Z) when the height flight increased from 50 m to 250 m.
Zastosowanie lekkich bezzałogowych statków powietrznych (UAV) jest coraz bardziej powszechne w badaniach topograficznych 3D. Zwłaszcza w skomplikowanych terenach, takich jak kopalnie odkrywkowe, w których wzniesienie gwałtownie faluje, mapowanie oparte na UAV jest bardziej wydajne, ekonomiczne i bezpieczne w porównaniu z metodami konwencjonalnymi. Jednak jednym z najważniejszych czynników w mapowaniu UAV złożonego terenu jest wysokość lotu, którą należy poważnie rozważyć ze względu na bezpieczeństwo i dokładność generowanych DEM. Niniejszy artykuł ma na celu ocenę wpływu wysokości lotu na dokładność DEM generowanych dla kopalni odkrywkowych. W tym celu wybranym obszarem badawczym jest kamieniołom o złożonym terenie położony w północnym Wietnamie. Badanie przeprowadzono przy pięciu wysokościach lotu 50 m, 100 m, 150 m, 200 m i 250 m. Aby ocenić dokładność uzyskanych DEM, wykorzystano 10 naziemnych punktów kontrolnych i 385 punktów kontrolnych mierzonych zarówno metodami GNSS/RTK, jak i metodami stacji całkowitej. Dokładność DEM oceniono za pomocą błędu pierwiastkowego średniego kwadratu (RMSE) w komponentach X, Y, Z, XY i XYZ. Wynik pokazał, że modele DEM generowane na wysokościach lotu poniżej 150 m mają wysoką dokładność, RMSE na 10 GCP wzrosły z 1,8 cm do 6,2 cm dla pionu (Z) i od 2,6 cm do 6,3 cm dla poziomu (XY), podczas gdy RMSE na 385 punktach kontrolnych wzrasta stopniowo z 0,05 m do 0,15 m dla pionu (Z), gdy lot na wysokości wzrósł z 50 m do 250 m.
Źródło:
Inżynieria Mineralna; 2020, 1, 1; 179-186
1640-4920
Pojawia się w:
Inżynieria Mineralna
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fracture Mechanism of Hard Main Roof and Determining the Width of Coal Pillars when Extracting Flat-lying Coal Seams
Autorzy:
Le, Quang Phuc
Dao, Van Chi
Nguyen, Phi Hung
Vu, Thai Tien Dung
Powiązania:
https://bibliotekanauki.pl/articles/27323252.pdf
Data publikacji:
2023
Wydawca:
Polskie Towarzystwo Przeróbki Kopalin
Tematy:
failure mechanism
coal pillar
stress distribution
roadway deformation
retained roadway
hard main roof
gob-side entry
węgiel
filary
stabilność
Wietnam
Opis:
In underground coal mining, the stability of roadways and gob-side entry depends on the coal pillar width. An unreasonable width of the coal pillar will cause the roadway to be in a dangerous zone of influence of the abutment pressure, leading to severe roadway deformation. This paper studies the fracture mechanism of the hard main roof and reasonable coal pillar width to protect the stability of gob-side entry driving. The research results show that when mining a coal seam under a hard main roof, the console of the main roof on the edge of the coal seam has the form of hinge structure. The great load of the roof layers and the rotation of the console are the main causes leading to the variation of the stress field in the coal seam. According to the development law of the stress field, after the main roof completes the collapse process, the peak of the maximum stress will move deep into the solid coal seam, and on the edge of the coal seam it will form a low-stress zone. Research results from the case of Seam #11 of Khe Cham coal mine, Vietnam show that the gob-side entry will be well stabilized when the narrow coal pillar between it and the boundary of the gob is 4–5 m.
Źródło:
Inżynieria Mineralna; 2023, 2; 271--280
1640-4920
Pojawia się w:
Inżynieria Mineralna
Dostawca treści:
Biblioteka Nauki
Artykuł
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