A. Rasedee, M. Suleiman, A. Ahmadian, Z. Ibrahim, K. I. Othman, A. Rakhimov
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The solution of Riccati type differential equation by means of variable order variable stepsize backward difference method
In this article a variable order variable step size technique in backwards difference form is used to solve nonlinear Riccati differential equations directly. The method proposed requires calculating the integration coefficients only once at the beginning, in contrast to current divided difference methods which calculate integration coefficients at every step change. Numerical results will show that the variable order variable step size technique reduces computational cost in terms of total steps without effecting accuracy.
期刊介绍:
The aim of this journal is to provide a lively forum for the communication of original research papers and timely review articles on Advances in Soft Computing and Its Applications. IJASCA will publish only articles of the highest quality. Submissions will be evaluated on their originality and significance. IJASCA invites submissions in all areas of Soft Computing and Its Applications. The scope of the journal includes, but is not limited to: √ Soft Computing Fundamental and Optimization √ Soft Computing for Big Data Era √ GPU Computing for Machine Learning √ Soft Computing Modeling for Perception and Spiritual Intelligence √ Soft Computing and Agents Technology √ Soft Computing in Computer Graphics √ Soft Computing and Pattern Recognition √ Soft Computing in Biomimetic Pattern Recognition √ Data mining for Social Network Data √ Spatial Data Mining & Information Retrieval √ Intelligent Software Agent Systems and Architectures √ Advanced Soft Computing and Multi-Objective Evolutionary Computation √ Perception-Based Intelligent Decision Systems √ Spiritual-Based Intelligent Systems √ Soft Computing in Industry ApplicationsOther issues related to the Advances of Soft Computing in various applications.