The representation of large numbers in neural networks and its application to economical load dispatching of electric power
- 1 January 1989
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 587-592 vol.1
- https://doi.org/10.1109/ijcnn.1989.118637
Abstract
The fundamentals of electric power load dispatching and Hopfield networks are briefly reviewed. A method for representing large numbers in Hopfield networks is theoretically examined and then applied to the problem of economical load dispatching. Simulation of stationary and time-varying loads is discussed, and results are given. The approach is found to be superior in the ease of formalization of the problem and in its memory and computation time efficiency. It is applicable to many problems other than economical load dispatching.<>Keywords
This publication has 6 references indexed in Scilit:
- Neural computation by concentrating information in time.Proceedings of the National Academy of Sciences, 1987
- Neural networks for computation: number representations and programming complexityApplied Optics, 1986
- Simple 'neural' optimization networks: An A/D converter, signal decision circuit, and a linear programming circuitIEEE Transactions on Circuits and Systems, 1986
- “Neural” computation of decisions in optimization problemsBiological Cybernetics, 1985
- Neurons with graded response have collective computational properties like those of two-state neurons.Proceedings of the National Academy of Sciences, 1984
- Neural networks and physical systems with emergent collective computational abilities.Proceedings of the National Academy of Sciences, 1982