In recent years,big data has become the new focus of attention from all walks of *** valuable information contained in big data becomes the driving force for people to process and analyze big *** data analytics helps ...
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In recent years,big data has become the new focus of attention from all walks of *** valuable information contained in big data becomes the driving force for people to process and analyze big *** data analytics helps enterprises to take better decisions to improve business *** a user description tool,user profile is widely used in various ***,it is difficult to deal with large-scale datasets using traditional methods since the established processes was not designed to handle large volumes of *** this paper,we propose a user profile analysis framework using machine learning approach which apply advanced machine learning programs to solve industrial scale *** this approach can be effective to speculate real and potential needs of various groups of users and precisely extract individual characteristics and group *** introducing high-level data parallel framework,the process of large-scale data processing can be executed *** use real-world data to validate the effectiveness of the proposed framework.
Ensuring safety and providing timely conflict alerts to small unmanned aircraft, commonly known as drones, is important to their integration into civil airspace. This paper proposes a short-term conflict avoidance alg...
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Ensuring safety and providing timely conflict alerts to small unmanned aircraft, commonly known as drones, is important to their integration into civil airspace. This paper proposes a short-term conflict avoidance algorithm for an automated low-altitude, small unmanned aircraft traffic management system. The goal is to balance between aircraft safety and efficiency subject to uncertainty in the environment, aircraft, and pilot response. The proposed algorithm generates advisories for each aircraft to follow, and is based on decomposing a large multiagent Markov decision process and fusing their solutions. As a result, the method scales well and resolves conflicts efficiently. Further, this paper presents a massively distributed architecture used to implement the conflict avoidance algorithm on a practical scale in which simultaneous conflicts can be solved in parallel in tens of milliseconds. Our controller significantly outperforms two baseline algorithms based on uncoordinated and closest-threat heuristics. In terms of conflict probability, our simulations demonstrate that our method is an order of magnitude better than the latter and about 10% better than the former.
Existing Volunteer computing environments are usually dedicated to one project/application and, what is very often unwelcome nowadays, require some software to be installed on each volunteer PC. Moreover, the environm...
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ISBN:
(纸本)9780956494467
Existing Volunteer computing environments are usually dedicated to one project/application and, what is very often unwelcome nowadays, require some software to be installed on each volunteer PC. Moreover, the environments are not completely platform-independent so it is not possible to use a fast growing mobiles computation potential. The idea of utilizing a web browser as an environment for executing a volunteer computational task addresses the last issue. The paper presents an extensible, component oriented volunteer computing platform that may be easily adapted to different problems. After reviewing existing solutions, the architecture and behavior of the platform is discussed, and simulation results are given.
This paper presents a recent history of progress both in disciplinary modeling and in optimization methods and frameworks for space transportation systems conceptual design and analysis. The disciplinary models and pr...
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This paper presents a recent history of progress both in disciplinary modeling and in optimization methods and frameworks for space transportation systems conceptual design and analysis. The disciplinary models and process typically used for space transportation analyses are identified, including physics-based and empirical models. The diverse characteristics of these disciplinary models require equally diverse integration and optimization approaches to enable implementation of automated, multidisciplinary design systems. Two general approaches are described for integrating these disciplinary models into computational frameworks for automated vehicle synthesis and optimization. Several optimization approaches are discussed including parameter, gradient-based, stochastic, and collaborative methods. Representative examples are given of multidisciplinary applications of optimization methods to the launch vehicle conceptual design problem. A primary goal for the future is to enable a space transportation design-to-cost capability.
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