The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Zhengqiu Yang - One of the best experts on this subject based on the ideXlab platform.
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a Decision Model of identifying user travel pattern based on the intelligent terminal sensor data
International Conference on Cloud Computing, 2016Co-Authors: Shuai Wang, Jiapeng Xiu, Chen Liu, Zhengqiu YangAbstract:The identification of user travel pattern has important research value for intelligent transportation. Intelligent terminal can supply GPS, acceleration sensors, pressure sensors data which can provide data base for the identification of user travel patterns. This paper research on a user travel pattern Decision Model based on the sensor data. The Decision algorithm adopts Decision tree algorithm based on ID3. Experiments data shows that this Decision Model is effective in identifying the pattern of user's travel.
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CCIS - A Decision Model of identifying user travel pattern based on the intelligent terminal sensor data
2016 4th International Conference on Cloud Computing and Intelligence Systems (CCIS), 2016Co-Authors: Shuai Wang, Jiapeng Xiu, Chen Liu, Zhengqiu YangAbstract:The identification of user travel pattern has important research value for intelligent transportation. Intelligent terminal can supply GPS, acceleration sensors, pressure sensors data which can provide data base for the identification of user travel patterns. This paper research on a user travel pattern Decision Model based on the sensor data. The Decision algorithm adopts Decision tree algorithm based on ID3. Experiments data shows that this Decision Model is effective in identifying the pattern of user's travel.
Schahram Dustdar - One of the best experts on this subject based on the ideXlab platform.
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reusable architectural Decision Model for Model and metadata repositories
Formal Methods, 2009Co-Authors: Christine Mayr, Uwe Zdun, Schahram DustdarAbstract:Models are gaining importance in software development, for instance in the MDD field, as well as in other disciplines such as biology and physics. Hence, tool support is needed to manage these Models and metadata about the Models. Model repositories support this trend by managing these Model artifacts. While setting up Model and metadata repositories, architects have to make several fundamental design Decisions and balance various forces. In this paper we describe reusable knowledge in form of reusable architectural Decisions for IT-architects in setting-up, planning, and developing Model and metadata repositories, as well as the main Decision drivers. Our Decisions are documented in a reusable architectural Decision Model that can be instantiated for a concrete system. It also supports a lightweight approach to architecture documentation. A case study illustrates the Decisions made when setting up our own data access object Model repository by walking through the reusable architectural Decision Model.
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FMCO - Reusable Architectural Decision Model for Model and Metadata Repositories
Formal Methods for Components and Objects, 2009Co-Authors: Christine Mayr, Uwe Zdun, Schahram DustdarAbstract:Models are gaining importance in software development, for instance in the MDD field, as well as in other disciplines such as biology and physics. Hence, tool support is needed to manage these Models and metadata about the Models. Model repositories support this trend by managing these Model artifacts. While setting up Model and metadata repositories, architects have to make several fundamental design Decisions and balance various forces. In this paper we describe reusable knowledge in form of reusable architectural Decisions for IT-architects in setting-up, planning, and developing Model and metadata repositories, as well as the main Decision drivers. Our Decisions are documented in a reusable architectural Decision Model that can be instantiated for a concrete system. It also supports a lightweight approach to architecture documentation. A case study illustrates the Decisions made when setting up our own data access object Model repository by walking through the reusable architectural Decision Model.
Eric Horvitz - One of the best experts on this subject based on the ideXlab platform.
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Problem Formulation as the Reduction of a Decision Model
arXiv: Artificial Intelligence, 2013Co-Authors: David Heckerman, Eric HorvitzAbstract:In this paper, we extend the QMRDT probabilistic Model for the domain of internal medicine to include Decisions about treatments. In addition, we describe how we can use the comprehensive Decision Model to construct a simpler Decision Model for a specific patient. In so doing, we transform the task of problem formulation to that of narrowing of a larger problem.
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Reasoning about the Value of Decision-Model Refinement: Methods and Application
arXiv: Artificial Intelligence, 2013Co-Authors: Kim-leng Poh, Eric HorvitzAbstract:We investigate the value of extending the completeness of a Decision Model along different dimensions of refinement. Specifically, we analyze the expected value of quantitative, conceptual, and structural refinement of Decision Models. We illustrate the key dimensions of refinement with examples. The analyses of value of Model refinement can be used to focus the attention of an analyst or an automated reasoning system on extensions of a Decision Model associated with the greatest expected value.
Shuai Wang - One of the best experts on this subject based on the ideXlab platform.
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a Decision Model of identifying user travel pattern based on the intelligent terminal sensor data
International Conference on Cloud Computing, 2016Co-Authors: Shuai Wang, Jiapeng Xiu, Chen Liu, Zhengqiu YangAbstract:The identification of user travel pattern has important research value for intelligent transportation. Intelligent terminal can supply GPS, acceleration sensors, pressure sensors data which can provide data base for the identification of user travel patterns. This paper research on a user travel pattern Decision Model based on the sensor data. The Decision algorithm adopts Decision tree algorithm based on ID3. Experiments data shows that this Decision Model is effective in identifying the pattern of user's travel.
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CCIS - A Decision Model of identifying user travel pattern based on the intelligent terminal sensor data
2016 4th International Conference on Cloud Computing and Intelligence Systems (CCIS), 2016Co-Authors: Shuai Wang, Jiapeng Xiu, Chen Liu, Zhengqiu YangAbstract:The identification of user travel pattern has important research value for intelligent transportation. Intelligent terminal can supply GPS, acceleration sensors, pressure sensors data which can provide data base for the identification of user travel patterns. This paper research on a user travel pattern Decision Model based on the sensor data. The Decision algorithm adopts Decision tree algorithm based on ID3. Experiments data shows that this Decision Model is effective in identifying the pattern of user's travel.
Christine Mayr - One of the best experts on this subject based on the ideXlab platform.
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reusable architectural Decision Model for Model and metadata repositories
Formal Methods, 2009Co-Authors: Christine Mayr, Uwe Zdun, Schahram DustdarAbstract:Models are gaining importance in software development, for instance in the MDD field, as well as in other disciplines such as biology and physics. Hence, tool support is needed to manage these Models and metadata about the Models. Model repositories support this trend by managing these Model artifacts. While setting up Model and metadata repositories, architects have to make several fundamental design Decisions and balance various forces. In this paper we describe reusable knowledge in form of reusable architectural Decisions for IT-architects in setting-up, planning, and developing Model and metadata repositories, as well as the main Decision drivers. Our Decisions are documented in a reusable architectural Decision Model that can be instantiated for a concrete system. It also supports a lightweight approach to architecture documentation. A case study illustrates the Decisions made when setting up our own data access object Model repository by walking through the reusable architectural Decision Model.
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FMCO - Reusable Architectural Decision Model for Model and Metadata Repositories
Formal Methods for Components and Objects, 2009Co-Authors: Christine Mayr, Uwe Zdun, Schahram DustdarAbstract:Models are gaining importance in software development, for instance in the MDD field, as well as in other disciplines such as biology and physics. Hence, tool support is needed to manage these Models and metadata about the Models. Model repositories support this trend by managing these Model artifacts. While setting up Model and metadata repositories, architects have to make several fundamental design Decisions and balance various forces. In this paper we describe reusable knowledge in form of reusable architectural Decisions for IT-architects in setting-up, planning, and developing Model and metadata repositories, as well as the main Decision drivers. Our Decisions are documented in a reusable architectural Decision Model that can be instantiated for a concrete system. It also supports a lightweight approach to architecture documentation. A case study illustrates the Decisions made when setting up our own data access object Model repository by walking through the reusable architectural Decision Model.
