Parallel Ant Colony Optimization Algorithm Based Neural Method for Determining Resonant Frequencies of Various Microstrip Antennas

Abstract Artificial neural networks and heuristic algorithms are popular intelligent techniques in solving complex engineering problems. This article presents new approaches based on feed-forward artificial neural networks trained with Levenberg-Marquardt, touring ant colony optimization, and parallel ant colony optimization algorithms to determine the resonant frequencies of the rectangular, circular, and triangular microstrip antennas. The results achieved from heuristic- and gradient-based algorithms were compared to that of the other methods in the literature. The results obtained from the neural models for the various microstrip antennas are in very good agreement with the experimental results in the literature. The proposed neural model trained with parallel ant colony optimization algorithm provides better accuracy than the other algorithms presented in this article and the literature.

[1]  Michael Georgiopoulos,et al.  Applications of Neural Networks in Electromagnetics , 2001 .

[2]  J. S. Dahele,et al.  On the resonant frequencies of the triangular patch antenna , 1987 .

[3]  S. Hyakin,et al.  Neural Networks: A Comprehensive Foundation , 1994 .

[4]  Seref Sagiroglu,et al.  Calculation of resonant frequency for an equilateral triangular microstrip antenna with the use of artificial neural networks , 1997 .

[5]  Luca Maria Gambardella,et al.  MACS-VRPTW: a multiple ant colony system for vehicle routing problems with time windows , 1999 .

[6]  I. J. Bahl,et al.  Microstrip Antennas , 1980 .

[7]  Seref Sagiroglu,et al.  Generalized neural method to determine resonant frequencies of various microstrip antennas , 2002 .

[8]  K. Gupta,et al.  Microstrip antenna design , 1988 .

[9]  Raj Mittra,et al.  Analysis of a Microstrip Disk Resonator , 1973 .

[10]  Yoshua Bengio,et al.  Learning long-term dependencies with gradient descent is difficult , 1994, IEEE Trans. Neural Networks.

[11]  Martin Middendorf,et al.  An Island Model Based Ant System with Lookahead for the Shortest Supersequence Problem , 1998, PPSN.

[12]  Patrick van der Smagt,et al.  Introduction to neural networks , 1995, The Lancet.

[13]  Nicolas Monmarché,et al.  On how Pachycondyla apicalis ants suggest a new search algorithm , 2000, Future Gener. Comput. Syst..

[14]  Juan Julián Merelo Guervós,et al.  SA-Prop: Optimization of Multilayer Perceptron Parameters Using Simulated Annealing , 1999, IWANN.

[15]  Qi-Jun Zhang,et al.  Neural Networks for RF and Microwave Design , 2000 .

[16]  Kai Fong Lee,et al.  Theory and experiment on microstrip antennas with airgaps , 1985 .

[17]  M. Dorigo,et al.  1 Positive Feedback as a Search Strategy , 1991 .

[18]  D. M. Pozar,et al.  Microstrip antennas , 1995, Proc. IEEE.

[19]  P. Bhartia,et al.  Millimeter-wave microstrip and printed circuit antennas , 1991 .

[20]  Roberto Battiti,et al.  Training neural nets with the reactive tabu search , 1995, IEEE Trans. Neural Networks.

[21]  Seref Sagiroglu,et al.  Determining Resonant Frequencies of Various Microstrip Antennas within a Single Neural Model Trained Using Parallel Tabu Search Algorithm , 2005 .

[22]  Jatinder N. D. Gupta,et al.  Comparative evaluation of genetic algorithm and backpropagation for training neural networks , 2000, Inf. Sci..

[23]  Hartmut Schmeck,et al.  Information Exchange in Multi Colony Ant Algorithms , 2000, IPDPS Workshops.

[24]  J. S. Dahele,et al.  Effect of substrate thickness on the performance of a circular-disk microstrip antenna , 1983 .

[25]  Wan-Chi Siu,et al.  Adding learning to cellular genetic algorithms for training recurrent neural networks , 1999, IEEE Trans. Neural Networks.

[26]  M. Kara.  The resonant frequency of rectangular microstrip antenna elements with various substrate thicknesses , 1996 .

[27]  Marco Dorigo,et al.  Mobile agents for adaptive routing , 1998, Proceedings of the Thirty-First Hawaii International Conference on System Sciences.

[28]  J. Dréo,et al.  Continuous interacting ant colony algorithm based on dense heterarchy , 2004, Future Gener. Comput. Syst..

[29]  Dervis Karaboga,et al.  Training recurrent neural networks by using parallel tabu search algorithm based on crossover operation , 2004, Eng. Appl. Artif. Intell..

[30]  Armando Blanco,et al.  A genetic algorithm to obtain the optimal recurrent neural network , 2000, Int. J. Approx. Reason..

[31]  P. Hall,et al.  Handbook of microstrip antennas , 1989 .

[32]  K. Guney,et al.  A Hybrid Method Based on Combining Artificial Neural Network and Fuzzy Inference System for Simultaneous Computation of Resonant Frequencies of Rectangular, Circular, and Triangular Microstrip Antennas , 2009, IEEE Transactions on Antennas and Propagation.

[33]  Seref Sagiroglu,et al.  Neural computation of resonant frequency of electrically thin and thick rectangular microstrip antennas , 1999 .

[34]  Mehmet Kara.  CLOSED-FORM EXPRESSIONS FOR THE RESONANT FREQUENCY OF RECTANGULAR MICROSTRIP ANTENNA ELEMENTS WITH THICK SUBSTRATES , 1996 .

[35]  Fred E. Gardiol,et al.  Broadband Patch Antennas , 1995 .

[36]  Riccardo Poli,et al.  New ideas in optimization , 1999 .

[37]  Marc Gravel,et al.  PARALLEL IMPLEMENTATION OF AN ANT COLONY OPTIMIZATION METAHEURISTIC WITH OPENMP , 2001 .

[38]  Seref Sagiroglu,et al.  Artificial Neural Networks for the Resonant Resistance Calculation of Electrically Thin and Thick Rectangular Microstrip Antennas , 2000 .

[39]  Armando Blanco,et al.  A real-coded genetic algorithm for training recurrent neural networks , 2001, Neural Networks.

[40]  Kerim Guney,et al.  RESONANT FREQUENCY CALCULATION FOR CIRCULAR MICROSTRIP ANTENNAS WITH A DIELECTRIC COVER USING ADAPTIVE NETWORK-BASED FUZZY INFERENCE SYSTEM OPTIMIZED BY VARIOUS ALGORITHMS , 2007 .

[41]  M. N. Shanmukha Swamy,et al.  Neural methods for antenna array signal processing: a review , 2002, Signal Process..

[42]  Cyril Fonlupt,et al.  Parallel Ant Colonies for Combinatorial Optimization Problems , 1999, IPPS/SPDP Workshops.

[43]  Kai Fong Lee,et al.  Advances in microstrip and printed antennas , 1997 .

[44]  L. Shafai,et al.  Impedance characteristics of circular microstrip patches , 1988, 1988 Symposium on Antenna Technology and Applied Electromagnetics.

[45]  Thomas Stützle,et al.  ACO algorithms for the quadratic assignment problem , 1999 .

[46]  Wei Chen,et al.  Theoretical and experimental studies of the resonant frequencies of the equilateral triangular microstrip antenna , 1992 .

[47]  Adem Kalinli,et al.  A Parallel Ant Colony Optimization Algorithm Based on Crossover Operation , 2008, Advances in Metaheuristics for Hard Optimization.

[48]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[49]  Ian C. Parmee,et al.  The Ant Colony Metaphor for Searching Continuous Design Spaces , 1995, Evolutionary Computing, AISB Workshop.

[50]  Thomas Stützle,et al.  Parallelization Strategies for Ant Colony Optimization , 1998, PPSN.

[51]  B. Bullnheimer,et al.  A NEW RANK BASED VERSION OF THE ANT SYSTEM: A COMPUTATIONAL STUDY , 1997 .

[52]  Juan Julián Merelo Guervós,et al.  G-Prop: Global optimization of multilayer perceptrons using GAs , 2000, Neurocomputing.

[53]  Bahram Alidaee,et al.  Global optimization for artificial neural networks: A tabu search application , 1998, Eur. J. Oper. Res..

[54]  Jasmina Arifovic,et al.  Using genetic algorithms to select architecture of a feedforward artificial neural network , 2001 .

[55]  Luca Maria Gambardella,et al.  Solving symmetric and asymmetric TSPs by ant colonies , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[56]  T. Stützle,et al.  MAX-MIN Ant System and local search for the traveling salesman problem , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[57]  Jean-Pierre Damiano,et al.  New determination of resonant frequency of circular disc microstrip antenna: application to thick substrate , 1988 .