Publisher
Springer Nature Switzerland
Reference19 articles.
1. Abdelhafez, A., Alba, E., Luque, G.: A component-based study of energy consumption for sequential and parallel genetic algorithms. J. Supercomput. 75, 6194–6219 (2019)
2. Cruz, L.: Tools to measure software energy consumption from your computer (2021). https://luiscruz.github.io/2021/07/20/measuring-energy.html
3. Demaine, E.D., Lynch, J., Mirano, G.J., Tyagi, N.: Energy-efficient algorithms. In: Proceedings of the 2016 ACM Conference on Innovations in Theoretical Computer Science, pp. 321–332 (2016)
4. Díaz-Álvarez, J., Castillo, P.A., Fernandez de Vega, F., Chávez, F., Alvarado, J.: Population size influence on the energy consumption of genetic programming. Measur. Control 55(1–2), 102–115 (2022)
5. Diaz Alvarez, J., Castillo Martínez, P.A., Rodríguez Díaz, F.J., Fernández de Vega, F., et al.: A fuzzy rule-based system to predict energy consumption of genetic programming algorithms (2018)