At the current state of a airs it is hard to obtain a predictable performance from wireless sensor networks, not to mention performance guarantees. In particular, a widely accepted and established methodology for modeling the performance of wireless sensor networks is missing. In the last two years we have tried to make a step into the direction of an analytical framework for the performance mo...

In this paper, polynomial prediction of Rayleigh fading power signal produced by noise shaping is investigated. We focus on the processing of the measured input signal for power control purposes of a Code Division Multiple Access (CDMA) mobile station receiver. Predictive filtering based on a polynomial signal model is proposed, and a class of FIR-type polynomial predictors is investigated with...

Control Agent Prediction Agent Abstract-This paper proposes transient angle stability agents to enhance power system stability. The proposed transient angle stability agents divided into two strategy agents. The first strategy agent is a prediction agent that will predict power system instability. According to the prediction agent’s output, the second strategy agent, which is a control agent, i...

Control Agent Prediction Agent Abstract-This paper proposes transient angle stability agents to enhance power system stability. The proposed transient angle stability agents divided into two strategy agents. The first strategy agent is a prediction agent that will predict power system instability. According to the prediction agent’s output, the second strategy agent, which is a control agent, i...

Wang et al. (Reports, 4 October 2013, p. 127) claimed high prediction power for their model of citation dynamics. We replicate their analysis but find discouraging results: 14.75% papers are estimated with unreasonably large m (>5) and l (>10) and correspondingly enormous prediction errors. The prediction power is even worse than simply using short-term citations to approximate long-term citati...

Intermittency and uncertainty pose great challenges to the large-scale integration of wind power, so research on the probabilistic interval forecasting of wind power is becoming more and more important for power system planning and operation. In this paper, a Naive Bayesian wind power prediction interval model, combining rough set (RS) theory and particle swarm optimization (PSO), is proposed t...

Photovoltaic Power Plants (PVPP) are classified as a power energy sources with non-stabile supply of electric energy. It is necessary to back up power energy from PVPP for stabile electric network operation. We can set an optimal value of back up power energy with using variety of prediction models and methods for PVPP Power output prediction. Fuzzy classifiers and fuzzy rules can be informally...

Accurate prediction of the future electricity consumption is crucial for production electricity management. Since the storage of electrical energy is very difficult, reliable and accurate prediction of power consumption is important. Different approaches for this purpose were used. In this paper, Grey model (1,1) based on grey system theory has been used for forecasting results. Annual electric...