摘要 :
In order that the mechanism designed meets the requirements of kinematics with optimal dynamics behaviors, a quadratic optimization method is proposed based on the different characteristics of kinematic and dynamic optimization. T...
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In order that the mechanism designed meets the requirements of kinematics with optimal dynamics behaviors, a quadratic optimization method is proposed based on the different characteristics of kinematic and dynamic optimization. This method includes two steps of optimization, that is, kinematic and dynamic optimization. Meanwhile, it uses the results of the kinematic optimization as the constraint equations of dynamic optimization. This method is used in the parameters optimization of transplanting mechanism with elliptic planetary gears of high-speed rice seedling transplanter with remarkable significance. The parameters spectrum, which meets to the kinematic requirements, is obtained through visualized human-computer interactions in the kinematics optimization, and the optimal parameters are obtained based on improved genetic algorithm in dynamic optimization. In the dynamic optimization, the objective function is chosen as the optimal dynamic behavior and the constraint equations are from the results of the kinematic optimization. This method is suitable for multi-objective optimization when both the kinematic and dynamic performances act as objective functions.
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Seeker optimization algorithm (SOA) has applications in continuous space of swarm intelligence. In the fields of proton ex-change membrane fuel cell (PEMFC) modeling, SOA was proposed to research a set of optimized parameters in P...
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Seeker optimization algorithm (SOA) has applications in continuous space of swarm intelligence. In the fields of proton ex-change membrane fuel cell (PEMFC) modeling, SOA was proposed to research a set of optimized parameters in PEMFC polariza-tion curve model. Experimental result showed that the mean square error of the optimization modeling strategy was only 6.9 × 10-23. Hence, the optimization model could fit the experiment data with high precision.
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The intelligent optimizing method of cutting parameters and the cutting stable districts searching method are set up. The cutting parameters of each cutting pass could be optimized automatically, the cutting chatter is predicted t...
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The intelligent optimizing method of cutting parameters and the cutting stable districts searching method are set up. The cutting parameters of each cutting pass could be optimized automatically, the cutting chatter is predicted through setting up the dynamic cutting force AR(2) model on-line, the spindle rotation speed is adjusted according to the predicting results so as to ensure the cutting system work in stable district.
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According to the data observed in a China- Japan Joint Investigation, the parameters of an ecosystem dynamics model (Qiao et al., 2000) were optimized. The values of eighteen parameters for the model were obtained, with nutrient h...
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According to the data observed in a China- Japan Joint Investigation, the parameters of an ecosystem dynamics model (Qiao et al., 2000) were optimized. The values of eighteen parameters for the model were obtained, with nutrient haft saturation constant, Kn = 1.4 μmol/dm3, Kp = 0.129 μmol/dm3 and Ks= 1.16μmol/dm3 for the diatom and Kn=0.345μmol/dm3, Kp=0.113 μmol/dm3 for the flagellate. Three proposals to set up a function for this multiple objective problem were discussed in detail.
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A nonlinear analysis of the energy consistency of multivariable finite elements based onincompatible trial functions is presented. The nonlinear forms of the convergence and opti-mization condition are set up. The relevant optimiz...
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A nonlinear analysis of the energy consistency of multivariable finite elements based onincompatible trial functions is presented. The nonlinear forms of the convergence and opti-mization condition are set up. The relevant optimization approach for hybrid elements andthe optimal parameter matching is suggested and applied to the 3-dimensional problem ofelasticity.
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@@ In Shengli oilfield, remarkable achievements have been obtained in research and tests on the technologies of jet drilling and optimizing parameter drilling, extensive applications of the technologies have greatly improved drill...
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@@ In Shengli oilfield, remarkable achievements have been obtained in research and tests on the technologies of jet drilling and optimizing parameter drilling, extensive applications of the technologies have greatly improved drilling speed and sharply decreased drilling time and costs, thus achieving excellent social and economic benefits.
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This paper presents an application of an Ant Colony Optimization (ACO) algorithm to optimize the parameters in the design of a type of nonlinear PID controller. The ACO algorithm is a novel heuristic bionic algorithm, which is bas...
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This paper presents an application of an Ant Colony Optimization (ACO) algorithm to optimize the parameters in the design of a type of nonlinear PID controller. The ACO algorithm is a novel heuristic bionic algorithm, which is based on the behaviour of real ants in nature searching for food. In order to optimize the parameters of the nonlinear PID controller using ACO algorithm,an objective function based on position tracing error was constructed, and elitist strategy was adopted in the improved ACO algorithm. Detailed simulation steps are presented. This nonlinear PID controller using the ACO algorithm has high precision of control and quick response.
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This paper presents a method by which the maximum possible rate of pulverized coal injection (PCI) in blast furnace can be predicted. The method is based on a two-step approach. First, a first principle simulation model of the bla...
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This paper presents a method by which the maximum possible rate of pulverized coal injection (PCI) in blast furnace can be predicted. The method is based on a two-step approach. First, a first principle simulation model of the blast furnace is used to generate data sets for the development of a linear model of pulverized coal injection rate. The data has been generated randomly in MATLAB software within the range of operating parameters (constraints) of the blast furnace. After that, the coefficients of the function have been determined. The inputs and the resulting outputs formed the data on which the linear optimization model was developed. Next, the linear model was used for maximizing the pulverized coal rate injection by optimizing the other variables. Two operating Indian Blast Furnaces have been chosen to validate the optimization model.
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