Bounding the solution of interval linear equations
SIAM Journal on Numerical Analysis
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
A Comparison of some Methods for Solving Linear Interval Equations
SIAM Journal on Numerical Analysis
An iterative method for algebraic solution to interval equations
IMACS'97 Proceedings on the on Iterative methods and preconditioners
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Statistical Modeling, Analysis and Management of Fuzzy Data
Statistical Modeling, Analysis and Management of Fuzzy Data
On the solution sets of particular classes of linear interval systems
Journal of Computational and Applied Mathematics - Proceedings of the international conference on recent advances in computational mathematics
An Evolutionary Approach for Approximating the Solutions of Systems of Linear Fuzzy Equations
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
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The problem of solving systems of interval linear equations with use of AI based approaches is studied in this paper. First, this problem is viewed in terms of an optimization task. A cost function with interval variables is defined. Next, for a given system of equations, instead of the exact algebraic solution its approximation is determined by minimizing the cost function. This is done by use of two different approaches: the NN based approach and the GA based one. A number of numerical evaluations are provided in order to verify the proposed techniques. The results are compared, discussed and some final conclusions are drawn.