Using Swarm UAVs to collect feedback information from sensor nodes can greatly improve the coverage rate and energy efficiency of Wireless Sensor Networks (WSNs), especially for environmental monitoring in inaccessibl...
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ISBN:
(纸本)9781665436892
Using Swarm UAVs to collect feedback information from sensor nodes can greatly improve the coverage rate and energy efficiency of Wireless Sensor Networks (WSNs), especially for environmental monitoring in inaccessible areas. Based on a modular swarm UAV platform and randomly distributed sensor network, this paper devotes to design a clustering algorithm which considers the distance constraints of sensor communication. Then, relying on the cluster results, we propose an Ant Colony Optimization (ACO)-based cooperative path planning for modular UAVs, with multiple constraints brought by characters of separate/recombine modes. Simulation results indicate that the proposed clustering algorithm and cooperative path planning is capable of effectively realizing the adaptive clustering and improving the total information collected by the UAV-aided WSNs.
Most previous skeleton-based action recognition methods ignore weight information of joints and data features beyond labels, which is harmful to action recognition. In this paper, we propose a skeleton-based action re...
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ISBN:
(纸本)9783030866082;9783030866075
Most previous skeleton-based action recognition methods ignore weight information of joints and data features beyond labels, which is harmful to action recognition. In this paper, we propose a skeleton-based action recognition with improved Graph Convolution Network, which is based on Spatial Temporal Graph Convolutional Network (STGCN). And we add a predictive cluster network, weight generation networks on it. The model uses K-means algorithm to cluster and get the data information beyond the labels. Besides, each cluster traines weight generation networks independently. To find the best clusters, we propose a evaluation criterion with less computational effort. We perform extensive experiments on the Kinetics dataset and the NTU RGB+D dataset to verify the effectiveness of each network of our model. The comparison results show that our approach achieves satisfactory results.
Testing autonomous vehicles (AVs) in hazardous scenarios is a crucial technical approach to ensure their safety. A key aspect of this process is the generation of hazard scenarios. In general, such scenarios are gener...
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The International Maritime Organization (IMO) enforced stricter sulphur abatement regulations since shipping emission has become one of the most major cause of the atmospheric pollution. Experts from the industry and ...
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ISBN:
(纸本)9781665424639
The International Maritime Organization (IMO) enforced stricter sulphur abatement regulations since shipping emission has become one of the most major cause of the atmospheric pollution. Experts from the industry and academicians try to find the balanced solution among low-sulphur fuel, clean energy, and purposely fit scrubber by conventional statistical methods however failed to reach a satisfying conclusion. In addition, maritime datasets are usually massive, multi-source, and heterogeneous, it seems imperative for the maritime industry to adapt to the worldwide trend of intellectualisation and promote sustainable development. This work delineates and compares three main sulphur abatement solutions for ships through a thorough investigation of the current research state, and proposes a new framework based on a fusion model using modern big data and data mining algorithms. This work identifies and summarises major factors (with high impacts) in sulphur abatement solutions in the ocean shipping industry and integrate those high-level impacting factors to the proposed fusion model. The proposed framework can be optimised and utilised in determining suitable solutions for different ships, as well as shipping routes.
With the rapid development of city urbanization, the identification of urban functional zones and the exploration of life convenience in urban area becomes an important reference for urban problem analysis and urban d...
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ISBN:
(数字)9781510649767
ISBN:
(纸本)9781510649767;9781510649750
With the rapid development of city urbanization, the identification of urban functional zones and the exploration of life convenience in urban area becomes an important reference for urban problem analysis and urban decision-making Based on POI data, this paper uses kernel density analysis and clustering algorithm analysis method to obtain POI kernel density center and cluster center for all kinds of data. And the accuracy of the clustering center is verified by comparing with the kernel density center. In addition, the clustering center points are also verified by comparing with the current satellite image, which demonstrated that convenience center based on this study is reliable and authentic.
With the advancements in the maritime industry, which delivers almost 90 percent of the world trade, the frequency of maritime activities has drastically increased resulting a major concern in maritime safety. A signi...
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ISBN:
(纸本)9780692935590
With the advancements in the maritime industry, which delivers almost 90 percent of the world trade, the frequency of maritime activities has drastically increased resulting a major concern in maritime safety. A significant 30 percent of maritime accidents are caused due to bad weather conditions, for instance sea storms and strong winds created due to high turbulence and waves. The deaths and casualties caused due to these accidents would have been minimized if there was a mechanism for efficient emergency response. Autonomous Surface Vessels (ASVs) have been used for several disaster mitigation and recovery operations in hurricanes, earthquakes and tsunami. ASVs are comparatively cheap and safe to be deployed on to hazardous zones in the deep sea due to their long term marine presence. A more efficient way for emergency response by the ASVs would be, the ability to predict a location where there is a possibility for an accident to take place and position itself such that it could effectively respond to the emergency. Hence the author is proposing an optimal solution using machine learning techniques to suggest waypoints to ASVs for effective emergency response on human operated surface vessels.
With China's rapid development of e-commerce and logistics, many large electronic business enterprises start to establish large volume warehouses. It takes a long time to distribute the goods every time, so the op...
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With China's rapid development of e-commerce and logistics, many large electronic business enterprises start to establish large volume warehouses. It takes a long time to distribute the goods every time, so the optimal distribution link can save a lot of time and it has important practical significance. In order to optimize goods inventory and delivery, the electronic commerce goods shopping cart stream data need to be analyzed. In this paper, a novel increment update clustering algorithm, named as IUCStream for commodity stream data analysis in e-commerce and logistics is proposed. In this algorithm, the correlation between goods is calculated and an efficient algorithm processing incremental updating of the data stream of goods is used to cluster different goods into groups. Finally, the algorithms' superiority and effectiveness are verifying by an example.
When facing clustering problems for hesitant fuzzy information, we normally solve them on sample space by using a certain hesitant fuzzy clustering algorithm, which is usually time-consuming or generates inaccurate cl...
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When facing clustering problems for hesitant fuzzy information, we normally solve them on sample space by using a certain hesitant fuzzy clustering algorithm, which is usually time-consuming or generates inaccurate clustering results. To overcome the issue, we propose a novel hesitant fuzzy clustering algorithm called hesitant fuzzy kernel C-means clustering (HFKCM) by means of kernel functions, which maps the data from the sample space to a high-dimensional feature space. As a result, the differences between different samples are expanded and thus make the clustering results much more accurate. By conducting simulation experiments on distributions of facilities and the twenty-first Century Maritime Silk Road, the results reveal the feasibility and availability of the proposed HFKCM algorithm.
With the construction of smart grid, a large number of user-side power data has been accumulated. This paper proposes a method for analyzing the user's power behavior based on clustering algorithm. Firstly, the us...
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ISBN:
(数字)9781510646131
ISBN:
(纸本)9781510646131;9781510646124
With the construction of smart grid, a large number of user-side power data has been accumulated. This paper proposes a method for analyzing the user's power behavior based on clustering algorithm. Firstly, the user load data is classified according to the season, and the user's seasonal power characteristics are analyzed according to the typical daily load curve of the season. Then the average temperature plus load data is used as the feature, and K-means clustering algorithm is used to explore the influence of temperature and holidays on users' electricity behavior in summer and winter respectively. This paper proposes a method of classifying and analyzing different power consumption modes of a single user, which provides data support for the subsequent load prediction model training for similar days, as well as the formulation of fine management and demand side management decisions for the power grid.
This paper presents a new risk-evaluation model for underway POL replenishment at sea, which is based on clustering algorithm. Although there are many studies on risks involved in POL replenishment at sea, the majorit...
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This paper presents a new risk-evaluation model for underway POL replenishment at sea, which is based on clustering algorithm. Although there are many studies on risks involved in POL replenishment at sea, the majority of them are mainly focused on the risks caused by sea conditions. In reality, there are many other influencing factors, such as thunder and lighting, dense fog, and so on. Thus, the results obtained in those previous studies are incomplete with many uncertainties still existing. By taking several major environment factors into consideration, this paper employs clustering algorithm to analyze data in simulated experiments, and puts forward a new risk-evaluation model for underway POL replenishment at sea.
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