We propose a combined SLF method to extrapolate feeder load growth by using feeder's history peak value and the merits of gray theory and Genetic Programming ( GP ). At first, we adopt load transfer coupling method to correct load history and its error for load transfer.
Here we adopt the relativity analysis of gray system theory to analyze the relationship between the contamination concentration released by furnace and import factors that determine the combustion. Finding out the optimized running mode of boiler and the most important causes that influence the contamination production are our goals.
The results are analyzed by employing the grey relation function (ξ) and grey relation grade (R) based on the Grey Theory.
It is an advantage that the methods have gotten rid of discretization error in contrast with the methods of grey theory.
The basic difference non-equal interval model GM(1,1) in grey theory was used to fit and forecast data series with non-equal lengths and different inertias, acquired from oil monitoring of internal combustion engines.
In this paper, we systematically discuss the basic concepts of grey theory, particularly the grey differential equation and its mathematical foundation, which is essentially unknown in the reliability engineering community.
Based on the grey theory and fuzzy mathematics, a new comprehensive evaluation method from qualitative to quantitative, called grey-fuzzy evaluation, was proposed for evaluating eco-environment vulnerability.
The dynamic models were developed by gray theory for estimating the fuels loads of arbor, shrub, herbs, grass, litter, and semi-decomposed litter, inflammable fuel and the total fuels in each forest type.
Mathematic programming is always an important means for the optimal computation of the power system. In recent years it is still developing. At the same time, Fuzzy mathematics and Grey theory are permeating into the field of the power system. This paper introduces the achievements of the author's research in this field.
In the paper, the method how to set up the pratical mathamatical model of predicting annual production of me chanical and electrical elements according to the present and future conditions was described in detail and the relative coun termeasure was put forward to give a reference.
As the Complicated randomness and vnstable of the condition in the whole power system exists from beginning to end in the process of the load forecarst, it is just the characteristic of the object which we studied in the grey system,we set up a grey-forecast module,a remain-identification module and grey-decision module in this paper, we have a discriminant was given, We have gained the percision more better and the risk more lower than before