New Square Method

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New Square Method
YanPing, CEO, China

Non-linear; Data regression; Model application.

The "new square method" is an improved approach based on the "least square method". It calculates not only the constants and coefficients but also the variables’ power values in a model in the course of data regression calculations, thus bringing about a simpler and more accurate calculation for non-linear data regression processes.

A test is a way which people use to study the process of causality and the change discipline. Through a test, we can get some relating data and deduct the change process of things. We can return the data into the mathematical model to help us analyze and solve the problems in the test.

During the design we need complicated computing. The computing depends on the test data or the charts protracted on the basis of large amount of test data. We return the data or charts into the mathematical model to make the computing process and mathematical model into a computer program. Eventually such program will get the correct result by pressing some buttons.

In the project process, we can return unused data into the mathematical model, and in the later project process, forecast the process of the project through the software, so as to get the forecast and predict aim of computers. In the same way, we can simulate computer imitation, edit relating imitation software through setting the mathematical model with the unused data, and use computers to imitate manipulation.

We use the data regression to set mathematical mode, edit the computer program, and to input computers. And to realize the process optimized control. Due to the complexity of the real process, it is not enough to depend on models to control the process exactly, but it has a forecast function, and can make control easier. Though the illegible control is exact, it controls through the feedback of the result. There is a period of dispatch between complicating from reference point to controlling objective, and this causes the lag of illegible control. The exceeding of model control is not correct, the illegible control is correct but lags. So if we combine the two parts and find the deficiencies of each other to make the process optimized and find a best plan. So with the combination of model control and illegible control, we can get the process direction for computers. In addition, the affected variants are too much. The restriction of the computers makes it hard for some models to be set. The complicated process can be divided into several units. The affected variants of the unit will reduce. To the model of the unit, the unit model setting is both easy and correct, and integrate all the unit models, so as to achieve the computer optimized control aim.

We can use some tools such as a spectrum and chromatogram, to test character data, and test the relating data of the matter. Conjunct the data and character data to set mathematical model, so it can be used to test the data and mathematical model and compute the relating character data value. Using this way, a checking apparatus can be made.


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