A Robust Method for Solving Transcendental Equations
This paper provides a robust method for solving transcendental equations. The approach, based on the Genetic Algorithm, is commenced with the evaluation of the mathematical equations by their fitness ratio. As the genetic algorithm is a computationally expensive process, the searching space for possible solutions is limited to possible chromosomes for which the function values are closest to zero. These chromosomes are then selected for the next generation using roulette wheel strategy. Thus, the required processing timing is greatly reduced. Experimental results demonstrate that this process works reliably and gives better results than the well-known False Position method and the Bisection method for the numerical solution of transcendental equations.
Keywords: Genetic Algorithm, False Position, Bisection, Transcendental Equation, Cross-over, Mutation, Roulette Wheel Selection.
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ABOUT THE AUTHORS
Md. Golam Moazzam
Md. Golam Moazzam completed his B.Sc (Hons) in Electronics and Computer Science from Jahangirnagar University in 1997 and M.S. in Computer Science and Engineering from the same University in 2001, respectively. He is now an Associate Professor in the Dept. of Computer Science and Engineering, Jahangirnagar University, Dhaka, Bangladesh. His research interests include Digital Image Processing, Artificial Intelligence, Computer Graphics, Neural Networks, Computer Vision and so on.
Amita Chakraborty
Amita Chakraborty received her B.Sc. (Hons) in Electronics and Computer Science and MS in Computer Science and Engineering from Jahangirnagar University in 1997 and 2002 respectively. She is now an Assistant Professor in the Dept. of Computer Science and Engineering, Shaikh Burhanuddin College, Dhaka, Bangladesh. Her research interests include Artificial Intelligence, Object-Oriented Programming, Computer Graphics, Image processing and so on.
Md. Al-Amin Bhuiyan
Md. Al-Amin Bhuiyan received his B.Sc (Hons) and M.Sc. in Applied Physics and Electronics from University of Dhaka, Dhaka, Bangladesh in 1987 and 1988, respectively. He got the Dr. Eng. degree in Electrical Engineering from Osaka City University, Japan, in 2001. He has completed his Postdoctoral in the Intelligent Systems from National Informatics Institute, Japan. He is now a Professor in the Dept. of CSE, Jahangirnagar University, Savar, Dhaka, Bangladesh. His main research interests include Image Face Recognition, Cognitive Science, Image Processing, Computer Graphics, Pattern Recognition, Neural Networks, Human-machine Interface, Artificial Intelligence, Robotics and so on.
Md. Golam Moazzam
Md. Golam Moazzam completed his B.Sc (Hons) in Electronics and Computer Science from Jahangirnagar University in 1997 and M.S. in Computer Science and Engineering from the same University in 2001, respectively. He is now an Associate Professor in the Dept. of Computer Science and Engineering, Jahangirnagar University, Dhaka, Bangladesh. His research interests include Digital Image Processing, Artificial Intelligence, Computer Graphics, Neural Networks, Computer Vision and so on.
Amita Chakraborty
Amita Chakraborty received her B.Sc. (Hons) in Electronics and Computer Science and MS in Computer Science and Engineering from Jahangirnagar University in 1997 and 2002 respectively. She is now an Assistant Professor in the Dept. of Computer Science and Engineering, Shaikh Burhanuddin College, Dhaka, Bangladesh. Her research interests include Artificial Intelligence, Object-Oriented Programming, Computer Graphics, Image processing and so on.
Md. Al-Amin Bhuiyan
Md. Al-Amin Bhuiyan received his B.Sc (Hons) and M.Sc. in Applied Physics and Electronics from University of Dhaka, Dhaka, Bangladesh in 1987 and 1988, respectively. He got the Dr. Eng. degree in Electrical Engineering from Osaka City University, Japan, in 2001. He has completed his Postdoctoral in the Intelligent Systems from National Informatics Institute, Japan. He is now a Professor in the Dept. of CSE, Jahangirnagar University, Savar, Dhaka, Bangladesh. His main research interests include Image Face Recognition, Cognitive Science, Image Processing, Computer Graphics, Pattern Recognition, Neural Networks, Human-machine Interface, Artificial Intelligence, Robotics and so on.
