PurposeThe purpose of this paper is to perfect the axiom systems of buffer operator via adding the axiom of invariable trend.Design/methodology/approachBased on the three axioms of buffer operator, for any given data sequence of system behavior and any set of data satisfying the axiom of fixed point, it is proved that there always exists a buffer operator satisfying that the set of data is the buffer sequence of the given data sequence, and a specific constructor method of buffer operator is provided. Finally, the axiom of invariable trend is proposed to add in the axiom systems of buffer operator.FindingsThe results are convincing that although the raw sequence suffered from certain disturbance may be enlarged or reduced, the trend is in line with the original law. All predictions must be on the premise of this trend to forecast, or prediction will be considered invalid.Practical implicationsThe method exposed in the paper can be used to construct a specific buffer operator between two sequences satisfying the axiom of fixed point.Originality/valueThe paper succeeds in providing a kind of universal constructor method for buffer operator, and adding the axiom of invariable trend to perfect the axiom systems of buffer operator and ensure the consistency of variation trend between the predicted values and the actual values.
In this paper fuzzy simulation method of storage device of high capacity pulse equipment was advanced for the problem of impossibility of building a precise mathematical model because of the factors such as the influence of non-linear component of storage device of high capacity pulse equipment ,the saturation of storage device and the line loss/ device loss etc. Firstly a basic model was built according to the basic principles of storage equipment, then a fuzzy correction model was built as supplement of basic model combining with the running features of the storage equipment. Finally a simulation model was built and the rectified. The simulation result shows that the fuzzy simulation is more close to the real running data, index of IAE was lowered to about 16% of the normal simulation result.
PurposeThe purpose of this paper is to introduce the new class ratio dispersion, the new smooth degree sequence and the comparison criterion of the new smooth degree and to propose the new prior check of grey modeling in order to meet the modeling demand of the optimized grey models which have the white exponential law of coincidence.Design/methodology/approachThis paper introduces the corresponding new concepts and new comparison criterion which can reflect the approach degree of the raw data and the normal geometric progression by analogy with the traditional class ratio dispersion, smooth degree sequence and comparison criterion.FindingsTo the optimized grey models, the new concepts and the new comparison criterion can be regarded as the prior check of grey modeling.Originality/valueFirst, the new concepts and the new comparison criterion can reflect the approach degree of the raw data and the normal geometric progression, and this paper proposes the prior check of grey modeling to the optimized grey models. Second, this paper proposes the quantificational valuation criterion – the concept of the smooth degree which can reflect the approach degree of a single sequence and the normal geometric progression, and ends the status quo that there is only the comparison criterion of the smooth degree between two sequences but not the quantificational valuation criterion of a single sequence.
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