The Experts below are selected from a list of 4095 Experts worldwide ranked by ideXlab platform

Mehmet Yesilbudak - One of the best experts on this subject based on the ideXlab platform.

  • ICMLA - Design of an Intelligent Decision Making System for a Travelling Wave Ultrasonic Motor
    2009 International Conference on Machine Learning and Applications, 2009
    Co-Authors: Ilhami Colak, Ramazan Bayindir, H. Tolga Kahraman, Mehmet Yesilbudak
    Abstract:

    In this study, an Intelligent Decision Making system which determines the compatibility of operating parameters has been designed for the travelling wave ultrasonic motor (TWUSM). The system designed converts input parameters and operating temperature into useful data by rule-based inference mechanism and these data are evaluated in Naive Bayes Classifier. The proposed Decision Making system gives effective results in the compatibility determination of operating parameters for speed stability of the TWUSM.

  • Design of an Intelligent Decision Making System for a Travelling Wave Ultrasonic Motor
    2009 International Conference on Machine Learning and Applications, 2009
    Co-Authors: Ilhami Colak, Ramazan Bayindir, Tolga H. Kahraman, Mehmet Yesilbudak
    Abstract:

    In this study, an Intelligent Decision Making system which determines the compatibility of operating parameters has been designed for the travelling wave ultrasonic motor (TWUSM). The system designed converts input parameters and operating temperature into useful data by rule-based inference mechanism and these data are evaluated in naive Bayes classifier. The proposed Decision Making system gives effective results in the compatibility determination of operating parameters for speed stability of the TWUSM.

Ilhami Colak - One of the best experts on this subject based on the ideXlab platform.

  • ICMLA - Design of an Intelligent Decision Making System for a Travelling Wave Ultrasonic Motor
    2009 International Conference on Machine Learning and Applications, 2009
    Co-Authors: Ilhami Colak, Ramazan Bayindir, H. Tolga Kahraman, Mehmet Yesilbudak
    Abstract:

    In this study, an Intelligent Decision Making system which determines the compatibility of operating parameters has been designed for the travelling wave ultrasonic motor (TWUSM). The system designed converts input parameters and operating temperature into useful data by rule-based inference mechanism and these data are evaluated in Naive Bayes Classifier. The proposed Decision Making system gives effective results in the compatibility determination of operating parameters for speed stability of the TWUSM.

  • Design of an Intelligent Decision Making System for a Travelling Wave Ultrasonic Motor
    2009 International Conference on Machine Learning and Applications, 2009
    Co-Authors: Ilhami Colak, Ramazan Bayindir, Tolga H. Kahraman, Mehmet Yesilbudak
    Abstract:

    In this study, an Intelligent Decision Making system which determines the compatibility of operating parameters has been designed for the travelling wave ultrasonic motor (TWUSM). The system designed converts input parameters and operating temperature into useful data by rule-based inference mechanism and these data are evaluated in naive Bayes classifier. The proposed Decision Making system gives effective results in the compatibility determination of operating parameters for speed stability of the TWUSM.

Juan Boubetapuig - One of the best experts on this subject based on the ideXlab platform.

  • collect collaborative context aware service oriented architecture for Intelligent Decision Making in the internet of things
    Expert Systems With Applications, 2017
    Co-Authors: Alfonso Garciadeprado, Guadalupe Ortiz, Juan Boubetapuig
    Abstract:

    Abstract Internet of Things (IoT) has radically transformed the world; currently, every device can be connected to the Internet and provide valuable information for Decision-Making. In spite of the fast evolution of technologies accompanying the grow of IoT, we are still faced with the challenge of providing a service oriented architecture, which facilitates the inclusion of data coming together from several IoT devices, data delivery among a system's agents, real-time data processing and service provision to users. Furthermore, context-aware data processing and architectures still pose a challenge, in spite of being key requirements in order to get stronger IoT architectures. To face this challenge, we propose a COLLaborative ConText Aware Service Oriented Architecture (COLLECT), which facilitates both the integration of IoT heterogeneous domain context data — through the use of a light message broker — and easy data delivery among several agents and collaborative participants in the system — Making use of an enterprise service bus —. In addition, this architecture provides real-time data processing thanks to the use of a complex event processing engine as well as services and Intelligent Decision-Making procedures to users according to the needs of the domain in question. As a result, COLLECT has a great impact on context-aware decentralized and collaborative reasoning for IoT, promoting context-aware Intelligent Decision Making in such scope. Since context-awareness is key for a wide range of recommender and Intelligent systems, the presented novel solution improves Decision Making in a large number of fields where such systems require to promptly process a variety of ubiquitous collaborative and context-aware data.

N. Ranganathan - One of the best experts on this subject based on the ideXlab platform.

  • ASAP - A VLSI system architecture for real-time Intelligent Decision Making
    Proceedings of International Conference on Application Specific Systems Architectures and Processors: ASAP '96, 1996
    Co-Authors: M.i. Patel, N. Ranganathan
    Abstract:

    In this paper, we describe a VLSI system architecture for real-time Intelligent Decision Making. The architecture integrates the adaptability of a backpropagation based neural network and the Decision Making ability of a rule based fuzzy expert system on a chip. The Intelligent Decision Making system consists of a back-propagation based neural network for adaptive learning and a rule-based fuzzy expert system for Decision Making. Both the neural network and the expert system are realized as linear systolic arrays. Thus, the entire system can be implemented in VLSI with a few basic cells. The architecture exploits the principles of pipelining and parallelism to the maximum possible extent in order to achieve high speed and throughput. The proposed hardware can yield a real-time Decision every 5ns based on a 200 MHz clock. Currently, a prototype CMOS VLSI chip implementing the proposed architecture is being built and verified.

  • A VLSI system architecture for real-time Intelligent Decision Making
    Proceedings of International Conference on Application Specific Systems Architectures and Processors: ASAP '96, 1996
    Co-Authors: M.i. Patel, N. Ranganathan
    Abstract:

    In this paper, we describe a VLSI system architecture for real-time Intelligent Decision Making. The architecture integrates the adaptability of a backpropagation based neural network and the Decision Making ability of a rule based fuzzy expert system on a chip. The Intelligent Decision Making system consists of a back-propagation based neural network for adaptive learning and a rule-based fuzzy expert system for Decision Making. Both the neural network and the expert system are realized as linear systolic arrays. Thus, the entire system can be implemented in VLSI with a few basic cells. The architecture exploits the principles of pipelining and parallelism to the maximum possible extent in order to achieve high speed and throughput. The proposed hardware can yield a real-time Decision every 5ns based on a 200 MHz clock. Currently, a prototype CMOS VLSI chip implementing the proposed architecture is being built and verified.

Ramazan Bayindir - One of the best experts on this subject based on the ideXlab platform.

  • ICMLA - Design of an Intelligent Decision Making System for a Travelling Wave Ultrasonic Motor
    2009 International Conference on Machine Learning and Applications, 2009
    Co-Authors: Ilhami Colak, Ramazan Bayindir, H. Tolga Kahraman, Mehmet Yesilbudak
    Abstract:

    In this study, an Intelligent Decision Making system which determines the compatibility of operating parameters has been designed for the travelling wave ultrasonic motor (TWUSM). The system designed converts input parameters and operating temperature into useful data by rule-based inference mechanism and these data are evaluated in Naive Bayes Classifier. The proposed Decision Making system gives effective results in the compatibility determination of operating parameters for speed stability of the TWUSM.

  • Design of an Intelligent Decision Making System for a Travelling Wave Ultrasonic Motor
    2009 International Conference on Machine Learning and Applications, 2009
    Co-Authors: Ilhami Colak, Ramazan Bayindir, Tolga H. Kahraman, Mehmet Yesilbudak
    Abstract:

    In this study, an Intelligent Decision Making system which determines the compatibility of operating parameters has been designed for the travelling wave ultrasonic motor (TWUSM). The system designed converts input parameters and operating temperature into useful data by rule-based inference mechanism and these data are evaluated in naive Bayes classifier. The proposed Decision Making system gives effective results in the compatibility determination of operating parameters for speed stability of the TWUSM.