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world, are all certain things. But for some certain things, the information grasped in people’s brain may be fuzzy .For example, people’s face itself have not any uncertainty, but, even if the information in the husband (or wife)’s brain is fuzzy too, there is no quantitative certain data, but people can accurately distinguish the man known via the kind of fuzzy information. Therefore, we say, in present, the fuzziness of things considered is mainly uncertainty caused by the distinct definition and judgment standard that can’t be given for something. Or say the difference between things display either this or that in middle transition. As inconsistent law expound “when the complexity of a system add, people’s capacity to make it exact decrease, when arrive at a certain threshold, complexity and exactness repel each other, fuzziness accompany with complexity” [2]. In fuzzy system, or say when people handle fuzziness problem in reality, the mathematics tool adopted is fuzzy mathematics (namely fuzzy theory method). For fuzzy mathematics, its characteristic is depending on experience, Fuzzy mathematics faces uncertainty caused by inadequate knowledge, namely, solves the uncertain problem of “knowledge uncertainty”. Depending on experience talked here is membership function is given via experience. In practice, constructing a continuous membership functions usually needs infinite experience data (there are exceptions in specific). Hence, we may say, the information criterion of fuzzy theory is experience information. The involved is experience’s infinite information space (there are exceptions). The basis of fuzzy mathematics is fuzzy set. Fuzzy set are between 0 and 1, the characteristic value of element may be arbitrary number between “0” and “1”. The means is bound value . The operation of fuzzy set “max ” ∨ ,“min ” ∧ , namely take a value of bound . For fuzzy set theory, the “demand” is distribution according to membership function, the goal is knowledge expression. The original intension of fuzzy set is the knowledge of conception is described with number relation by people, so the goal of fuzzy mathematics is knowledge expression. The thinking way of vague mathematics is denotation quantification. For the characteristic of fuzzy set is denotation is uncertain, fuzzy mathematics’ thinking way is making uncertain denotation expressed by membership degree, namely, denotation quantification. Grey Information Problems in complex big system often involve a lot of information (data and knowledge). Because the noise in channel (objective) disturb, or the capacity of receiving system (subjective) is limited, We only infer the general range that information reflect, but didn’t know all the confirmed content, in addition, when some problem is handled, all information concerned is unnecessarily or impossibly obtained (only a part is known), which is information incompleteness. Grey system is the system which partial information is distinct and partial information is indistinct. It can be said information incomplete system. Grey system theory’s intension is “small sample uncertainty”. Grey system faces “the uncertainty” caused by a few data, namely, solves the problem of “a few data uncertainty”. It demands data is arbitrary distribution. Its goal is “reality law”. Because a few data studied is the data distributing in reality time zone. The data embody the reality law. The basis of grey system theory is “grey hazy set”. Grey hazy set is the set, under a certain proposition, whose element is from distinct to indistinct, information is from a little to a lot, and can be replenished unceasingly; the set from grey to white, from abstract to concrete; the set can evolve, have “life”, have “effectiveness for a given period of time”; the set is compatible to 0,1 property, cantor set and [0,1] property; the set have four kinds of forms (embryo, growth, maturity, actual evidence).[3], The Grey System theory is on the basis of information covering, that is, via information covering to describe, analyze, handle grey target whose information is incomplete, uncertain. The intension of information covering is to contain, cover information of given proposition with a group of information. The basis means of grey system theory is grey generation. Grey generation or generation is the data processing (concluding accumulation, ,transform, reject, interpolation…). Its goal is to provide comparable data for analysis; to provide reasonable data base for building model; to provide extremity uniform sample for making decision. Its characteristic is a few data; its thinking way is many angle of view; its information criterion is a little information. On the basis of “uncertainty of a few data”, only a little information can be obtained, hence, grey system theory involves finite information space. Above, three kinds of uncertain system and their theory (mathematics) method are discussed, their respective characteristic is analyzed from several aspects. The goal is make people to exactly apply uncertain system theory to solve real problem. The brief summary is given as follows TABLE kind aspect probability statistics fuzzy theory grey theory intension big sample knowledge small sample uncertainty uncertainty uncertainty basis Cantor set fuzzy set grey hazy set characteristic many data experience (data) a few data means statistical Bound value generation according to probability membership information distribution function covering demand classical function permit arbitrary distribution (distribution) distribution goal historical knowledge statistical law expression reality law thinking way appear again denotation many angle quantification of view information criterion infinite information experience information III. REMARK the least information There exists another kind of uncertain information, which our country’s famous scholar Guangyuan Wang academician finds and first provided, that is, unascertained 10
information, called weak uncertain information too. “Unascertained information” is the information that is must be used but unknown when making a strategy owing to restriction of objective condition. Or say, owing to inadequate evidence (information) grasped by decision maker is not enough to ascertain thing’s real state and quantity relation, which lead to the unascertained information of pure objective knowledge. The system with unascertained information is unascertained system. For unascertained system, its mathematics tool is “unascertained mathematics”, its basis is unascertained set. Reader can consult reference [4-6] It is noted that various kinds of uncertain system as well theory method is respectively discussed above, but in objective world, some big system may have not merely a kind of uncertainty, may have two or three kinds of uncertainty, which demands people plan as a whole in dealing with uncertain information. In aspect of handling system with two kinds of uncertainty, professor Wang Guanyuan and Zhang yue have established “fuzzy” random system theory[7-8], then, how to handle the problem of the other two or more kinds of information coexisting It wait people to tap and open up. ACKNOWLEDGMENT This paper is supported by the National Natural Science Foundation of China (70271006, 60674107), and by the Natural Science Foundation of Hebei Province (F2006000571, F2006000343), and by the Natural Science Foundation of Education Committee of Hebei Province (20070607) REFERENCES [1] Wang Qingyin, et al. “Exploration of Research Method in Systems with Uncertainties”. U.S.A. ASSA Lnauguration Issue,1995,pp.136-138 [2] Zadeh L A. “Outline of a new approach to the analysis of complex systems and decision processes”, IEEE Trans. Syst Man Cybern, 1973,(3),pp.28-44 [3] Deng Julong, “ Introduction to Grey Mathematics”. Wuhan: HUST Press, 1992 [4] Wang Guanyuan, “Unascertained Information and Its Mathematical Treatment”. Journal of Harbin Architecture engineering Institute, 1990,23(4) [5] Wang Guanyuan, et al. “A Preliminary Study on Unascertained Mathematics”, Journal of Hebei Mining and Civil Engineering Institute (Higher Education Research Edition) [6] Wang Guanyuan, et al. “Unascertained Mathematics”. Journal of Hebei Mining and Civil Engineering Institute, 1992,(3)pp.86-130 [7] Wang Guanyuan and Zhang yue, “Fuzzy Random Process Theory”,.Guiyang: Guizhou Science Press, 1994 [8] Wang Guanyuan and Zhang yue, “Fuzzy Random Dynamic System”. Beijing: Science Press, 1993 11
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special services. SOAP is used to b
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detection methods of DDoS attacks m
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distance of view point. Given that
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Ⅳ. EVALUATION OF BLENDED LEARNING
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symmetric with respect to the origi
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A. Data Preparing To generate our t
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Strong earthquake 0.1< M L
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indirect causes, and the logical re
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egression. Granger causality test i
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B. Evaluation We have evaluated thi
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used as a source and neighboring ce
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Figure 3. Drainage networks generat
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Combinational logic unit failures i
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Tabal.1 Combinational fault logic t
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under the endorsement of both the m
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TABLE I. DESCRIPTION OF PROPOSITION
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Figure 2. The process of the invers
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Figure 9. (a)the original image.(b)
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that studying being going to be to
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Reference[10] analyzed the evolutio
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module, communication module, apper
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After the comprehensive performance
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system testing can be seen that the
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III. AUTONOMIC RESOURCE ALLOCATION
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The QoE i (T i ) is the ith user’
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nodes will be formed one cluster, t
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Keyboard event Application User mod
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SQL Azure will eventually include a
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The nodes in the suffix tree are dr
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[3] Y. Li, S. M. Chung, and J. D. H
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some drilling fluid produces hydrog
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"normalization", whose membership b
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B. Research on protocol actions Com
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ACKNOWLEDGMENT This work is funded
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A. Problem Description In a small b
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[4] Huang, Hung, and J. Y. jen Hsu.
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Further by calculating, the followi
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TABLE II. THE CONCENTRATION BETWEEN
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private key that obtained by using
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ontology, and the domain dictionary
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Eq.4 is NP-hard and can be solved b
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Theorem 2.4([10]). Let L 1 and L 2
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evocation and the fourth group stor
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focused mainly on rule-based forms
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Ⅵ. CONCLUSION Figure 6. The Flask
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EDCF in comparison with DCF, has so
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in routing table. When search resou
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others through the selective emotio
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1) Process context storage areas. I
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V. CONCLUSION In this thesis, sCPU-
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main types of horizontal search env
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Enterprise Portal security provides
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() t = [ S () t S () t ] T N S ,...
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[2] Kumaravel, N., and Kavitha, V.,
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output, so BP network has been wide
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input to the artificial neural netw
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(2) In a process (tokens from outsi
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The reduction process consists of t
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all eight normal vectors are identi
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is B object , and the number of emp
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xi, j y' = εα ( (1 + tanh( )) −
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Error 8000 7000 6000 5000 4000 3000
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Architecture (AMBA) a new bus archi
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to execution time. Also, DBA would
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Liping Chen .......................
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