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Journal Cover International Journal of Fuzzy Computation and Modelling
  [2 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 2052-353X - ISSN (Online) 2052-3548
   Published by Inderscience Publishers Homepage  [427 journals]
  • A novel routing strategy for cognitive radio ad hoc network based on
           Sugeno fuzzy logic
    • Authors: Poonam, C.K. Nagpal, Shailender Gupta
      Pages: 87 - 115
      Abstract: In cognitive radio networks, a secondary user (SU) is dependent upon the spectrum, of varied frequency, temporarily vacated by primary users (PU) thereby making it quite a challenging task to design a protocol for finding a reliable and efficient routing path. To address the issue many routing schemes have been proposed based upon Mamdani type fuzzy inference system (FIS) to create a human intelligence analogy. The Mamdani type fuzzy inference mechanism is unable to simultaneously optimise multiple quality of service (QoS) parameters. This paper proposes a routing scheme based upon the Sugeno type fuzzy inference system (SFIS) that handles the continuously changing input parameters in quite effective manner and provides an effective performance with respect to multiple QoS parameters. The proposed routing scheme has been implemented using Matlab-9.0 and simulation results showed that the paths selected using this scheme are much more efficient than the paths selected by other routing schemes.
      Keywords: cognitive radios; fuzzy expert system; FES; ad hoc network; quality of service; QoS; Mamdani-type inference; Sugeno-type inference; shortest spectrum aware routing; single path routing; multiple path routing; cognitive radio network
      Citation: International Journal of Fuzzy Computation and Modelling, Vol. 2, No. 2 (2017) pp. 87 - 115
      PubDate: 2017-05-22T23:20:50-05:00
      DOI: 10.1504/IJFCM.2017.084255
      Issue No: Vol. 2, No. 2 (2017)
       
  • Decentralised quantised fuzzy control for large-scale T-S discrete
           delay systems
    • Authors: Poonam, C.K. Nagpal, Shailender Gupta
      Pages: 116 - 148
      Abstract: A class of fuzzy large-scale nonlinear discrete systems with local quantisers is examined. This fuzzy system has unknown-but-bounded couplings and delays. Of interest are the issues of analysis and design related to decentralised fuzzy feedback structure with <i>H</i><SUB align="right">∞ measure. It is established that the resulting closed-loop fuzzy system exhibits delay-dependent asymptotic stability with disturbance-attenuation level. In addition, all the computations are performed at the subsystem level using a fuzzy-basis-dependent Lyapunov-Krasovskii functional. Using quantised output measurements, a local procedure is constructed for tuning the quantiser parameters to achieve similar asymptotic stability and guaranteed performance. Special cases of interest are derived and simulation results on typical applications are provided.
      Keywords: large-scale H&infin; control; fuzzy feedback scheme; output quantiser; delay-dependent stabilisation; LMIs
      Citation: International Journal of Fuzzy Computation and Modelling, Vol. 2, No. 2 (2017) pp. 116 - 148
      PubDate: 2017-05-22T23:20:50-05:00
      DOI: 10.1504/IJFCM.2017.084259
      Issue No: Vol. 2, No. 2 (2017)
       
  • Designing of optimised rescue robot using fuzzy inference system
    • Authors: Kiran Gill, Supriya Raheja
      Pages: 149 - 166
      Abstract: The objective of this work is two-fold. First, this work focuses on detection of alive Homo sapiens. Second, it focuses on obstacle detection and collision avoidance. The main aim of this work is to maintain both needs simultaneously. To define the path more precisely, fuzzy set theory is used which tackle with the intermediate values of direction. A Sugeno fuzzy controller algorithm is used which takes three inputs labelled as obstacle position obtained through ultrasonic sensor, obstacle distance through IR sensor and CO<SUB align="right">2 sensor for finding presence of carbon-dioxide. The work is evaluated on different parameters. As compare to other rescue robots, the number of passes used by our proposed rescue robot is comparatively lesser. The other parameter is wheel computation which is used for measuring the motion. The proposed rescue robot is more flexible while determining its optimising path.
      Keywords: rescue robot; fuzzy inference system module; FIS module; ultrasonic sensor; CO2 sensor; IR distance sensor
      Citation: International Journal of Fuzzy Computation and Modelling, Vol. 2, No. 2 (2017) pp. 149 - 166
      PubDate: 2017-05-22T23:20:50-05:00
      DOI: 10.1504/IJFCM.2017.084256
      Issue No: Vol. 2, No. 2 (2017)
       
  • Fuzzy EPQ model with ramp type demand, linear deterioration and shortage
           using trapezoidal fuzzy number and signed distance method
    • Authors: Nirmal Kumar Duari, Tripti Chakrabarti
      Pages: 167 - 186
      Abstract: In the present paper, an inventory production model with Ramp type demand linear deterioration and shortages has been considered in a fuzzy environment. Our goal is to determine the optimal total cost and the optimal order quantity for the proposed inventory model. The trapezoidal fuzzy numbers have been introduced in order to achieve this goal. The computation of economic production quantity (EPQ) is carried out through defuzzification process by using signed distance method. The signed distance method is more applicable than the other methods of defuzzification. To illustrate the results of the proposed model, we have given an example for both crisp and fuzzy environment and presented the computational results. Sensitivity for this model is also studied, which shows a relation between demand, order quantity and total cost. The advantage of the proposed approach is that it is simple, gives a better result in relatively less computational work.
      Keywords: ramp type demand; deterioration; trapezoidal fuzzy numbers; fuzzy inventory model; defuzzification; signed distance method
      Citation: International Journal of Fuzzy Computation and Modelling, Vol. 2, No. 2 (2017) pp. 167 - 186
      PubDate: 2017-05-22T23:20:50-05:00
      DOI: 10.1504/IJFCM.2017.084258
      Issue No: Vol. 2, No. 2 (2017)
       
 
 
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