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# The Ellipse Model In Related To Fuzzy Logic

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### The Ellipse Model In Related To Fuzzy Logic

1. 1. The ellipse model in related to fuzzy logic a parabola equation x square= 4cy and y square= 4cx If we add two parabola together, we create a pseudo ellipse from x square + y square = 4 c (x+y); Assumed that x+ y = c (if we calculated it from Bayesian linear equation), we rearrange the pseudo ellipse to be as (x square/ 4) + (y square / 4) = c square. Fuzzy logic is disproportionate by itself. If we find another pseudo ellipse from an interrogated paradigm of (x square /4) + (y square / 4) = C square. Then, we calculate the crossing intersection of ( a , b ) from c = x + y and C = x + y. The real ellipse will be (x square / a square) + (y square / b square) = (c square). It means that if we add two hypothetical theories together such as 'the substantial facts vs the question of law' and 'the less errors in legal procedure vs the reality of evident', we will get a better prediction in decision making from informatics by computerized pattern recognition. A wild card in informatics, science, and law The following is my idea to build rubric in order to sort out needed data from legal resources. My rubric is to set up A as agent (the judicial systems), C as congress, T as trade (enterprises), G as government, U as people (like us), S as sub chapter s- corp, B as sub chapter c-corp, K as sub chapter partnership etc. The second step is to write computer programs for data mining and computer algorithm in informatics and then extract those assigned codes such as A,C,T,G,U,S,B,K etc from considered judicial database, and create some linked codes such as 'hashfljksafhhsahalhahg' . XML is to markup those extracted codes 'hashfljksafhhsahalhahg' in the linked syllables for computer to read and store those syllables, just like we read English sentences to our memory. After that, computer will run neural networking, Bayesian linear equation and Fuzzy logic. The third step, XML may be able to interpret those linked codes 'hashfljksafhhsahalhahg' and write certain English sentences under their decision making. Here, XML can use human English pattern such as the pattern of 'Subject + Verb + Object' and also indirect sentence 'Object + (is/was/are) + verb transitive( past participle ) + Subject'. For example, Tom grabs a piece of paper. XML mark Tom as Subject, grab as Verb, and paper as Object. XML reversely flips back to write 'A piece of paper is grabbed by Tom.' The reason is that the pointer of browser's icon will flip back to the original place when they write an indirect sentence. At this moment, computer will ask us for feedback, then we give computer some input to decide 'do it' or 'not do it'. The interactive relationship between machine and human is built here. Concerning some question of Bayesian application in legal mental calculus. I have written essay of Bayesian application in informatics, but it is not in legal mind