Journal
APPLIED SOFT COMPUTING
Volume 13, Issue 1, Pages 743-754Publisher
ELSEVIER
DOI: 10.1016/j.asoc.2012.08.025
Keywords
Artificial Neural Network (ANN); Criminal law; Fuzzy neural network (FNN); Genetic Algorithm (GA); Lagrange Interpolation and Trapezoidal; Membership Functions; Pattern classification
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This paper describes the construction of a decision system to be used by judges who is about to pass sentence in murder cases. Classification models of murder cases based on fuzzy neural network with random weights and fuzzy neural network with Genetic Algorithm based weights are designed. A simulation program in C++ has been deliberated and developed for analyzing the consequences. Results show that the fuzzy neural networks increase the rate of convergence in comparison with conventional neural networks with backpropagation algorithm. That the fuzzy neural networks for classification of murder cases using Trapezoidal Membership Function outperform Lagrange Interpolation and Gaussian Membership Function is also reported. Comparative studies are carried out for a number of networks and configurations. (C) 2012 Elsevier B.V. All rights reserved.
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