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Journal Cover   International Journal of Fuzzy Computation and Modelling
  [1 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  [399 journals]
  • Performance analysis of neuro-fuzzy position controller for vector
           controlled induction motor drive
    • Authors: Lal Bahadur Prasad, Krishna Pratap Singh, Hema Latha Javvaji
      Pages: 131 - 150
      Abstract: This paper presents the modelling, simulation, and performance analysis of a hybrid neuro-fuzzy logic controller for position control of induction motor using vector control techniques. In this paper, the space vector pulse width modulated voltage source inverter fed induction motor drive has been considered. The adaptive neuro-fuzzy inference system (ANFIS) method is used to design the direct torque neuro-fuzzy controller (DTNFC). The ANFIS structure can be tuned automatically by least square estimation and back propagation algorithm. The MATLAB-SIMULINK models are developed for both cases of without and with neuro-fuzzy controller to simulate the position control scheme. The simulation results justify the comparative advantages of ANFIS based neuro-fuzzy position controller which achieves the desired performance.
      Keywords: adaptive neuro-fuzzy inference system; ANFIS; direct torque control; neuro-fuzzy control; DTNFC; induction motor drives; vector control; voltage source PWM; pulse width modulation; PWM inverters; fuzzy logic controllers; FLC; neural networks; position con
      Citation: International Journal of Fuzzy Computation and Modelling, Vol. 1, No. 2 (2014) pp. 131 - 150
      PubDate: 2015-01-27T23:20:50-05:00
      DOI: 10.1504/IJFCM.2014.067122
      Issue No: Vol. 1, No. 2 (2015)
  • Reliability analysis of object oriented systems using vague lambda-tau
    • Authors: Chandra Shekhar Yadav, Raghuraj Singh, Yaduvir Singh
      Pages: 151 - 168
      Abstract: In this paper, vague lambda-tau methodology has been applied for reliability analysis of object oriented systems (OOS). OOS composed of interacting objects residing in computer memory and containing the data and its associated methods which can be decomposed into a finite number of cooperative objects have been considered for this purpose. In this methodology, the vague set theory has coupled with conventional lambda-tau method to evaluate the vague expression for OR-transition of the Petri nets model. Using this methodology, reliability of OOS can be analysed in a more efficient and effective manner.
      Keywords: reliability analysis; vague set theory; object-oriented systems; vague lambda-tau modelling; Petri nets; modelling
      Citation: International Journal of Fuzzy Computation and Modelling, Vol. 1, No. 2 (2014) pp. 151 - 168
      PubDate: 2015-01-27T23:20:50-05:00
      DOI: 10.1504/IJFCM.2014.067123
      Issue No: Vol. 1, No. 2 (2015)
  • A new optimisation method for scheduling with ACO and GA
    • Authors: Seyed Nima Mirabedini, Hassan Mina, Seyed Hossein Iranmanesh
      Pages: 169 - 193
      Abstract: In this paper we consider project scheduling in critical condition and encountered project delays and defeat. Under such circumstances the project manager should make the best decision for the project to decrease incoming risks, costs, time and maintain the organisation reputation. So in order to deliver the project on time, the manager has to find the critical jobs among the tasks which are not scheduled yet. We have presented two new mathematical models for achieving minimum time and cost of the project and is implemented by ant colony optimisation (ACO) and genetic algorithm (GA). Project task duration is considered as fuzzy-stochastic variable under uncertainty model. We test these models with an information technology (IT) project in real world and illustrate our how model reduce completion time and cost of the project and they can be implemented as a good trade-off for the main goal of the project.
      Keywords: project scheduling; fuzzy theory; elected tasks; time windows; ant colony optimisation; ACO; genetic algorithms; GAs; project time; project costs; mathematical modelling; uncertainty modelling; project completion time
      Citation: International Journal of Fuzzy Computation and Modelling, Vol. 1, No. 2 (2014) pp. 169 - 193
      PubDate: 2015-01-27T23:20:50-05:00
      DOI: 10.1504/IJFCM.2014.067125
      Issue No: Vol. 1, No. 2 (2015)
  • Using a fuzzy approach for a new bi-objective model for a
           multi-modal tree p-hub median location problem
    • Authors: Samaneh Sedehzadeh, Reza Tavakkoli-Moghaddam
      Pages: 194 - 211
      Abstract: One main group of transportation networks is a hub location problem that deals with finding the location of hub nodes and allocation of non-hub nodes to located hubs. This paper presents a capacitated multi-modal p-hub median location problem with a single assignment, in which different transportation modes can be established between hub nodes. This problem makes a decision on how the hub networks with different possible transportation modes should be designed. Moreover, high setup costs for links lead to use incomplete hub network; so we allow the connected hubs by means of a tree and consider a fixed cost for establishing hub links. The objectives of this model are to minimise the total cost and minimise the total transportation time (including the transportation time between nodes and the operation time at hub nodes). As the real values of parameters are not precisely known in advance, a fuzzy approach is proposed to cope with the uncertain parameters. The multi-objective model is also converted into a single objective one by the TH method. Furthermore, some numerical examples are provided to illustrate the correctness of the proposed model. Finally, the conclusion is provided.
      Keywords: capacitated hub median location; multi-objective optimisation; transport modes; fuzzy logic; uncertainty; transport networks; transport hub location; multi-modal transport
      Citation: International Journal of Fuzzy Computation and Modelling, Vol. 1, No. 2 (2014) pp. 194 - 211
      PubDate: 2015-01-27T23:20:50-05:00
      DOI: 10.1504/IJFCM.2014.067127
      Issue No: Vol. 1, No. 2 (2015)
  • Computation of a multi-objective fuzzy stochastic transportation
    • Authors: Srikumar Acharya, Narmada Ranarahu, Jayanta Kumar Dash, Mitali Madhumita Acharya
      Pages: 212 - 233
      Abstract: This paper is concerned with the solution methodology of a multi-objective transportation problem where fuzziness and randomness occur under one roof. In the present transportation problem, supplies and demands are considered as fuzzy random variable. In the first step of the solution procedure, fuzziness is removed by using alpha-cut technique to obtain multi-objective stochastic transportation problem. By using the chance constrained technique, the multi-objective stochastic transportation problem is transformed to equivalent crisp multi-objective transportation problem. Then, introducing the concept of membership function, multi-objective deterministic transportation problem is converted into single objective mathematical programming problem. Finally, it is solved with the help of existing technique. A numerical example and a case study are provided in order to illustrate the methodology.
      Keywords: stochastic programming; multi-objective programming; fuzzy programming; normal random variables; optimisation techniques; multi-objective transport problems; fuzzy random variables
      Citation: International Journal of Fuzzy Computation and Modelling, Vol. 1, No. 2 (2014) pp. 212 - 233
      PubDate: 2015-01-27T23:20:50-05:00
      DOI: 10.1504/IJFCM.2014.067129
      Issue No: Vol. 1, No. 2 (2015)
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