KEYWORDS: Genetic algorithms, Mathematical optimization, Education and training, Explosives, Roads, Data analysis, Universities, Process modeling, Power consumption, Evolutionary algorithms
This paper studies the power curve of two types riders (the Time Trial Specialist and the Sprinter) and set up a multiobjective optimization model by taking the total energy consumed and the total time used by a rider during the race as objective functions. By using the genetic algorithm to solve the multi-objective optimization model, the total energy and total time as far as possible to get the optimal solution under the condition of small number. The number of the optimal solutions corresponding to the rider in the process of competition has the opportunity to go beyond the opponent's corner number. The number of the optimal solutions can determine the relationship between the rider’s position on the course and the power the rider applies. Combining 2021 Tokyo Olympic Games, the model is applied to the individual time trials of two types of riders.
KEYWORDS: Resistance, Statistical analysis, Porosity, MATLAB, Data modeling, Monte Carlo methods, Data analysis, Tunable filters, Permeability, Performance modeling
The meltblown nonwoven material (MNM) is an important raw material for mask production. With good filtration performance, its production process is simple, low cost, and light quality. The research on the process parameters and structural variables of the MNM is widely concerned by domestic and foreign enterprises, and the relationship between structural variables and product performance is also. To the end, we study the process parameters and product performance of the MNM by using some mathematical methods for the high quality and high efficiency of the industry. We use a multiple nonlinear regression model to build a statistical model based on the data provided by the enterprise to reveal the variation pattern between process parameters and structural variables. The coefficient of decidability was calculated , and the correlation coefficient was above 0.9, which proved the accuracy of the model. Finally, in order to explore the relationship between structural variables and product performance, we used MATLAB to make a correlation four-dimensional diagram, used fitting polynomials to finally fit a quadratic correlation function, and used Monte Carlo multi-objective planning programming to obtain the maximum filtration efficiency of 96.8272% when the acceptance distance was 39.5cm and the hot air speed was 1188r/min.
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