Revival of Classical Algorithms: A Bibliometric Study on the Trends of Neural Networks and Genetic Algorithms

The purpose of our bibliometric research was to capture and analyze the trends two types well-known classical artificial intelligence (AI) algorithms: neural networks (NNs) genetic algorithms (GAs). Symmetry is a very popular international interdisciplinary scientific journal that cover six major subjects mathematics, computer science, engineering physics, biology, chemistry which are all related on AI algorithms; therefore, we referred most innovative articles have been published in Symmetry, also introduced new advanced applications for NNs Gas. Furthermore, used keywords “neural network algorithm” or “artificial network” search SSCI database from 2002 2021 obtained 951 NN publications. For comparison purposes, analyzed GA by using “genetic over same period 878 All publication results were categorized into eight groups deep analyses so as investigate their current forecasts. applied Kolmogorov–Smirnov test (K–S test) check whether complied with Lotka’s law. In summary, found number both GAs continuing grow but use increasing more sharply than due boom learning development. We hope can serve roadmap other researchers help them save time stay at cutting edge trends.