International Journal of Intelligent Information Systems

Volume 5, Issue 5, October 2016

  • Nature Inspired Algorithms in Cloud Computing: A Survey

    Gamal Abd El-Nasser A. Said

    Issue: Volume 5, Issue 5, October 2016
    Pages: 60-64
    Received: Sep. 05, 2016
    Accepted: Sep. 23, 2016
    Published: Oct. 11, 2016
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    Abstract: Cloud Computing consists of many resources, the problem of mapping tasks on unlimited computing resources in cloud computing is NP-hard optimization problem. In this paper, we provide a survey of popular nature inspired algorithms: Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) for solving NP-hard probl... Show More
  • Tracking Algorithm Based on Channel Propagating Characteristic in Wireless Sensor Network

    Ying Li, Yiliang Wu, Nina Hu, Guangsong Yang

    Issue: Volume 5, Issue 5, October 2016
    Pages: 65-70
    Received: Oct. 16, 2016
    Accepted:
    Published: Oct. 17, 2016
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    Abstract: In order to improve the mobile node tracking accuracy of indoor environment, a mobile node tracking algorithm based on channel propagating characteristic is proposed. Channel propagation model is established by actual measurement and fitting analysis in three different scenarios, which included closed corridor, open corridor and laboratory. The anc... Show More
  • Phase Matching Denoising Algorithm and IP Design

    Wu Peng, Xia Hui, Wang Chen

    Issue: Volume 5, Issue 5, October 2016
    Pages: 71-74
    Received: Oct. 16, 2016
    Accepted:
    Published: Oct. 17, 2016
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    Abstract: At present, there are many kinds of denoising algorithms, but the hardware of these algorithms IP design is very lacked. In this paper, a phase matching denoising algorithm is proposed to remove the noise, and the IP design of this method is realized. Phase matching denoising algorithm is based on the signal phase matching method to obtain the actu... Show More
  • An Evolutionary Method of Neural Network in System Identification

    Shuming T. Wang, Chi-Yen Shen, Yu-Ju Chen, Chuo-Yean Chang, Rey-Chue Hwang

    Issue: Volume 5, Issue 5, October 2016
    Pages: 75-81
    Received: Oct. 20, 2016
    Accepted:
    Published: Oct. 20, 2016
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    Abstract: This paper presents an evolutionary method for calculating the important degree (ID) of individual input variable of well-trained neural network (NN). The importance of each input variable of neural network could be distinguished in accordance with ID value obtained. In this research, several linear and nonlinear systems’ identifications were first... Show More