An efficient load scheduling method to meet varying power supply needs is presented in this paper. At peak load times, the power generation system fails due to its instability. Traditionally we use load shedding process. In load shedding process disconnect the unnecessary and extra loads. The proposed method overcomes this problem by scheduling the load based on the requirement. Artificial neur...

The load shedding problem is vital to a Data Stream Management System (DSMS). This paper presents the design, implementation, and evaluation of a load shedding method under the guide of the feedback control theory, in order to solve practical problems in medical environment. Thus, the using of operator selectivity, which has been proven not stable enough, is avoided. This paper focuses on the r...

Load shedding is a cheap and eco-friendly way to maintain balance on the power grid, by matching consumption on production. In this context, the main problem is to coordinate smart buildings in order for them to be able to anticipate their need and also to collectively adjust their load shedding. We present a bottom-up approach on distributed loadshedding and propose a decentralized model based...

As a perspective to ensure the power system stability and to avoid the vulnerability leading to the blackouts, several preventive and curative means are adopted. In order to avoid the voltage collapse, load shedding schemes represent a suitable action to maintain the power system service quality and to control its vulnerability. In this paper, we try to propose an intelligent load shedding stra...

nonlinear static procedure (nsp) is a common technique to predict seismic demands on various building structures by subjecting a monotonically increasing horizontal loading (pushover) to the structure. therefore, the pushover analysis is an important part of each nsp. accordingly, the current paper aims at investigating the efficiencyof various algorithms of lateral load patterns applied to the...

We consider approximate join processing over data streams when memory limitations cause incoming tuples to overflow the available space, precluding exact processing. Selective eviction of tuples (loadshedding) is needed, but is challenging since data distributions and arrival rates are unknown a priori. Also, in many real-world applications such as for the stock market and sensor-data, differen...