2 resultados para mathematical regression
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
The relation between metabolic demand and maximal oxygen consumption during exercise have been investigated in different areas of knowledge. In the health field, the determination of maximal oxygen consumption (VO2max) is considered a method to classify the level of physical fitness or the risk of cardiocirculatory diseases. The accuracy to obtain data provides a better evaluation of functional responses and allows a reduction in the error margin at the moment of risk classification, as well as, at the moment of determination of aerobic exercise work load. In Brasil, the use of respirometry associated to ergometric test became an opition in the cardiorespiratory evaluation. This equipment allows predictions concerning the oxyredutase process, making it possible to identify physiological responses to physical effort as the respiratory threshold. This thesis focused in the development of mathematical models developed by multiple regression validated by the stepwise method, aiming to predict the VO2max based on respiratory responses to physical effort. The sample was composed of a ramdom sample of 181 healthy individuals, men and women, that were randomized to two groups: regression group and cross validation group (GV). The voluntiars were submitted to a incremental treadmill test; objetiving to determinate of the second respiratory threshold (LVII) and the Peak VO2max. Using the método forward addition method 11 models of VO2max prediction in trendmill were developded. No significative differences were found between the VO2max meansured and the predicted by models when they were compared using ANOVA One-Way and the Post Hoc test of Turkey. We concluded that the developed mathematical models allow a prediction of the VO2max of healthy young individuals based on the LVII
Resumo:
This work purposes the application of a methodology to optimize the implantation cost of an wind-solar hybrid system for oil pumping. The developed model is estimated the implantation cost of system through Multiple Linear Regression technique, on the basis of the previous knowledge of variables: necessary capacity of storage, total daily energy demand, wind power, module power and module number. These variables are gotten by means of sizing. The considered model not only can be applied to the oil pumping, but also for any other purposes of electric energy generation for conversion of solar, wind or solar-wind energy, that demand short powers. Parametric statistical T-student tests had been used to detect the significant difference in the average of total cost to being considered the diameter of the wind, F by Snedecor in the variance analysis to test if the coefficients of the considered model are significantly different of zero and test not-parametric statistical by Friedman, toverify if there is difference in the system cost, by being considered the photovoltaic module powers. In decision of hypothesis tests was considered a 5%-significant level. The configurations module powers showed significant differences in total cost of investment by considering an electrical motor of 3 HP. The configurations module powers showed significant differences in total cost of investment by considering an electrical motor of 5 HP only to wind speed of 4m/s and 6 m/s in wind of 3 m, 4m and 5 m of diameter. There was not significant difference in costs to diameters of winds of 3 m and 4m. The mathematical model and the computational program may be used to others applications which require electrical between 2.250 W and 3.750 W. A computational program was developed to assist the study of several configurations that optimizes the implantation cost of an wind-solar system through considered mathematical model