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- Title
Analysis of the Corneal Geometry of the Human Eye with an Artificial Neural Network.
- Authors
Waseem; Ullah, Asad; Awwad, Fuad A.; Ismail, Emad A. A.
- Abstract
In this paper, a hybrid cuckoo search technique is combined with a single-layer neural network (BHCS-ANN) to approximate the solution to a differential equation describing the curvature shape of the cornea of the human eye. The proposed problem is transformed into an optimization problem such that the L 2 – error remains minimal. A single hidden layer is chosen to reduce the sink of the local minimum values. The weights in the neural network are trained with a hybrid cuckoo search algorithm to refine them so that we obtain a better approximate solution for the given problem. To show the efficacy of our method, we considered six different corneal models. For validation, the solution with Adam's method is taken as a reference solution. The results are presented in the form of figures and tables. The obtained results are compared with the fractional order Darwinian particle swarm optimization (FO-DPSO). We determined that results obtained with BHCS-ANN outperformed the ones acquired with other numerical routines. Our findings suggest that BHCS-ANN is a better methodology for solving real-world problems.
- Subjects
ARTIFICIAL eyes; PARTICLE swarm optimization; GEOMETRY; DIFFERENTIAL equations; CORNEA
- Publication
Fractal & Fractional, 2023, Vol 7, Issue 10, p764
- ISSN
2504-3110
- Publication type
Article
- DOI
10.3390/fractalfract7100764