In a de-regulated open access environment, reactive power is one of the ancillary services which must be provided by an Independent System Operator (ISO). In this paper, a new algorithm is proposed in which reactive power resources are initially so tuned that optimum security in terms of voltage profile and voltage stability are achieved while at the same time, the system losses are minimized. ...

Absfmcf. In this paper we propose an analyical method for the design of two-channel optimum FIR compaction filters which determine optimum orthonormal filter banks. The method is applicable for a fairly large class of random processes. Under some conditions, the method successfully constructs the theoretically optimum solution. Whenever this is the case, the magnitude-squared responses of the f...

Policy gradient methods have been widely applied in reinforcement learning. For reasons of safety and cost, learning is often conducted using a simulator. However, learning in simulation does not traditionally utilise the opportunity to improve learning by adjusting certain environment variables – state features that are randomly determined by the environment in a physical setting but controlla...

Minimum error rate training (MERT) is a widely used training procedure for statistical machine translation. A general problem of this approach is that the search space is easy to converge to a local optimum and the acquired weight set is not in accord with the real distribution of feature functions. This paper introduces coordinate system selection (RSS) into the search algorithm for MERT. Cont...

Novel environments often impose directional selection for a new phenotypic optimum. Novel environments, however, can also change the distribution of phenotypes exposed to selection by inducing phenotypic plasticity. Plasticity can produce phenotypes that either align with or oppose the direction of selection. When plasticity and selection are parallel, plasticity is considered adaptive because ...