Work

Improving the Generalization Abilities of Constructed Neural Networks with the Addition of Local Optimization Techniques

Year: 2024

Type: article

Abstract: Constructed neural networks with the assistance of grammatical evolution have been widely used in a series of classification and data-fitting problems recently. Application areas of this innovative machine learning technique include solving differential equations, autism screening, and measuring motor function in Parkinson’s disease. Although this technique has given excellent results, in many cases, it is trapped in local minimum and cannot perform satisfactorily in many problems. For this purpose, it is considered necessary to find techniques to avoid local minima, and one technique is the periodic application of local minimization techniques that will adjust the parameters of the constructed artificial neural network while maintaining the already existing architecture created by grammatical evolution. The periodic application of local minimization techniques has shown a significant reduction in both classification and data-fitting problems found in the relevant literature.

Source: Algorithms

DOI: 10.3390/a17100446

Authors: Ioannis G. Tsoulos, Vasileios Charilogis, Dimitrios Tsalikakis, Alexandros Tzallas

Institutions: University of Ioannina, University of Western Macedonia

Language: English

Topic: Evolutionary Algorithms and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,819

Funder: European Commission