Hybrid Adaptive Systems of Computational Intelligence and Their On-line Learning for Green IT in Energy Management Tasks-Reference-Cited by-同舟云学术

Hybrid Adaptive Systems of Computational Intelligence and Their On-line Learning for Green IT in Energy Management Tasks

Published:2016-09-22 Issue: Volume: Page:229-244
ISSN:2198-4182
Container-title:Green IT Engineering: Concepts, Models, Complex Systems Architectures
language:
Short-container-title:

Author:

Bodyanskiy Yevgeniy,Vynokurova Olena,Pliss Iryna,Peleshko Dmytro

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-44162-7_12

Reference40 articles.

1. Abraham, A., Khan, M.R.: Neuro-fuzzy paradigms for intelligent energy management. In: Abraham, A., Jain, L., Zwaag, B.J. (eds.) Innovations in Intelligent Systems, Part 2, pp. 285–314. Springer, Berlin (2004)

2. Khotanzad, A., Hwang, R.C., Abaye, A., Maratukulam, D.: An adaptive modular artificial neural network hourly load forecaster and its implementation at electric utilities. IEEE Trans. Power Syst. 10(3), 1716–1722 (1995)

3. Kiartzis, S.J., Zoumas, C.E., Theocharis, J.B., Bakirtzis, A.G., Petridis, V.: Short-term load forecasting in an autonomous power system using artificial Neural Networks. IEEE Trans. Power Syst. 12(4), 1591–1596 (1997)

4. Khotanzad, A., Afkhami-Rohani, R., Maratukulam, D.: ANNSTLF-artificial neural network short-term load forecaster-generation tree. IEEE Trans. Power Syst. 13(4), 1413–1422 (1998)

5. Abraham, A.: An evolving fuzzy neural network model based reactive power control. In: Proceedings of the Second International Conference on Computers in Industry, pp. 247–253, Bahrain (2000)

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Cooperative Ecology Human–Machine Interfaces for Safe Intelligent Transport Systems: Cloud-Based Software Case;Green IT Engineering: Social, Business and Industrial Applications;2018-09-30

2. Deep Evolving Stacking Convex Cascade Neo-Fuzzy Network and Its Rapid Learning;Proceedings of the 2018 Federated Conference on Computer Science and Information Systems;2018-09-26