In this paper, we propose a new optimized PID controller to stabilize the synchronous machine connected to an infinite bus. The model for the synchronous machine is 4-ordered linear Philips-Heffron synchronous machine. In this research, the parameters of the PID controller are optimally achieved by minimizing a definite fitness function to removes the unstable Eigen-value to the left side of im...

Basic decisions, such as judging a person as a friend or foe, involve categorizing novel stimuli. Recent work finds that people’s category judgments are guided by a small set of examples that are retrieved from memory at decision time. This limited and stochastic retrieval places limits on human performance for probabilistic classification decisions. In light of this capacity limitation, recent...

Abstract Adaptive systems—such as a biological organism gaining survival advantage, an autonomous robot executing functional task, or motor protein transporting intracellular nutrients—must somehow embody relevant regularities and stochasticity in their environments to take full advantage of thermodynamic resources. Analogously, but purely computational realm, machine learning algorithms estima...

The field of optimization and machine learning are increasingly interplayed and optimization in different problems leads to the use of machine learning approaches‎. ‎Machine learning algorithms work in reasonable computational time for specific classes of problems and have important role in extracting knowledge from large amount of data‎. ‎In this paper‎, ‎a methodology has been employed to opt...

There has recently been some interest in applying machine learning techniques to support the acquisition and adaptation of work-ow models. The diierent learning algorithms, that have been proposed, share some restrictions, which may prevent them from being used in practice. Approaches applying techniques from grammatical inference are restricted to sequential workkows. Other algorithms allowing...

Increasing the productivity of a knowledge worker via intelligent applications requires the identification of a user’s current work task, i.e. the current work context a user resides in. In this work we present and evaluate machine learning based work task detection methods. By viewing a work task as sequence of digital interaction patterns of mouse clicks and key strokes, we present (i) a meth...

Present study compares performance of proposed model [Hybrid Extended Kanban Control System (HEKCS)], with Extended Kanban Control System (EKCS) and Constant Work In Process (CONWIP) in a single line and multi stage manufacturing system with or without effect of machine breakdown. It was observed that, when demand rate increases, throughput, average WIP and utilization% also gradually increases...