@article{(Open Science Index):https://publications.waset.org/pdf/4025,
	  title     = {Neural Network Optimal Power Flow(NN-OPF) based on IPSO with Developed Load Cluster Method},
	  author    = {Mat Syai'in and  Adi Soeprijanto},
	  country	= {},
	  institution	= {},
	  abstract     = {An Optimal Power Flow based on Improved Particle
Swarm Optimization (OPF-IPSO) with Generator Capability Curve
Constraint is used by NN-OPF as a reference to get pattern of
generator scheduling. There are three stages in Designing NN-OPF.
The first stage is design of OPF-IPSO with generator capability curve
constraint. The second stage is clustering load to specific range and
calculating its index. The third stage is training NN-OPF using
constructive back propagation method. In training process total load
and load index used as input, and pattern of generator scheduling
used as output. Data used in this paper is power system of Java-Bali.
Software used in this simulation is MATLAB.},
	    journal   = {International Journal of Electrical and Computer Engineering},
	  volume    = {4},
	  number    = {12},
	  year      = {2010},
	  pages     = {1701 - 1706},
	  ee        = {https://publications.waset.org/pdf/4025},
	  url   	= {https://publications.waset.org/vol/48},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 48, 2010},
	}