Stamping is the main manufacturing process for sheet metal parts. However, during the stamping process, based on excessive blank holder force, unreasonable mold design, and other factors, it is easy to generate defect...
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Stamping is the main manufacturing process for sheet metal parts. However, during the stamping process, based on excessive blank holder force, unreasonable mold design, and other factors, it is easy to generate defects such as cracks in the drawing area and flange wrinkles. In this paper, a novel hybrid model based on a restricted Boltzmann machine and back-propagation neural network is proposed and its validity is verified through different testing functions. Additionally, an improved multi-objective particle swarm optimization (MOPSO) method based on a crowding operator is proposed and compared to several powerful existing algorithms. The proposed method was applied to the process optimization of a double-C part. The sensitivity of the forming quality to different process parameters was analyzed and a novel index was used to describe quality changes. A mapping relationship between the process parameters and forming quality was established based on the proposed hybrid model. Furthermore, optimal process parameters were obtained using MOPSO. The results demonstrated that the proposed method significantly reduces flange wrinkles without excessive thinning and improves the uniformity of formed parts.
In the RSSI-based positioning algorithm,regarding the problem of a great conflict between precision and cost,a low-power and low-cost synergic localization algorithm is proposed,where effective methods are adopted in ...
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In the RSSI-based positioning algorithm,regarding the problem of a great conflict between precision and cost,a low-power and low-cost synergic localization algorithm is proposed,where effective methods are adopted in each phase of the localization process and fully use the detective information in the network to improve the positioning precision and *** the ranging period,the power attenuation factor is obtained through the wireless channel modeling,and the RSSI value is transformed into *** the positioning period,the preferred reference nodes are used to calculate *** the position optimization period,Taylor expansion and least-squared iterative update algorithms are used to further improve the location *** the positioning,the notion of cooperative localization is introduced,in which the located node satisfying certain demands will be upgraded to a reference node so that it can participate in the positioning of other nodes,and improve the coverage and positioning *** results show that on the same network conditions,the proposed algorithm in this paper is similar to the Taylor series expansion algorithm based on the actual coordinates,but much higher than the basic least square algorithm,and the positioning precision is improved rapidly with the reduce of the range error.
This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification ...
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This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification of distillation processes,optimization of process parameters for distillation processes and recent research progress in dynamic control ***,the feasibility of using thermodynamic topological theories such as residual curve,phase equilibrium line and distillation boundary line to analyze different separation regions is discussed,and the rationality of distillation process design is discussed by using its ***,the application of molecular simulation methods such as molecular dynamics simulation and quantum chemical calculation in the screening of entrainer is discussed for the extractive distillation *** thermal coupling mechanism of different distillation processes is used to explore the process of different process ***,a mixed integer nonlinear optimization strategy for the distillation process based on different algorithms is ***,the improvement of dynamic control strategies for different distillation processes in recent years is *** work focuses on the application of process intensification and system optimization in the design of distillation process,and analyzes the challenges,prospects,and development trends of distillation technology in the separation of multicomponent azeotropes.
Quantification of vegetation biophysical variables such as leaf area index (LAI), fractional vegetation cover (fCover), and biomass are among the key factors across hydrological, agricultural, and irrigation managemen...
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Quantification of vegetation biophysical variables such as leaf area index (LAI), fractional vegetation cover (fCover), and biomass are among the key factors across hydrological, agricultural, and irrigation management studies. The present study proposes a kernel-based machine learning algorithm capable of performing adaptive and nonlinear data fitting so as to generate a suitable, accurate, and robust algorithm for spatio-temporal estimation of the three mentioned variables using Sentinel-2 images. To this aim, Gaussian process regression (GPR)-particle swarm optimization (PSO), GPR-genetic algorithm (GA), GPR-tabu search (TS), and GPR-simulated annealing (SA) hyperparameter-optimized algorithms were developed and compared against kernel-based machine learning regression algorithms and artificial neural network (ANN) and random forest (RF) algorithms. The accuracy of the proposed algorithms was assessed using digital hemispherical photography (DHP) data and destructive measurements performed during the growing season of silage maize in agricultural fields of Ghale-Nou, southern Tehran, Iran, in the summer of 2019. The results on biophysical variables against validation data showed that the developed GPR-PSO algorithm outperformed other algorithms under study in terms of robustness and accuracy (0.917, 0.931, 0.882 using R-2 and 0.627, 0.078, and 1.99 using RMSE in LAI, fCover, and biomass of Sentinel-2 20 m, respectively). GPR-PSO also possesses the unique ability to generate pixel-based uncertainty maps (confidence level) for prediction purposes (i.e., estimated uncertainty level <0.7 in LAI, fCover, and biomass, for 96%, 98%, and 71% of the total study area, respectively). Altogether, GPR-PSO appears to be the most suitable option for mapping biophysical variables at the local scale using Sentinel-2 images.
The technology teaching of university basketball general course is a focus which all sectors of the community should pay more attention. How will the technology teaching of university basketball general course carry o...
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ISBN:
(纸本)9783038351153
The technology teaching of university basketball general course is a focus which all sectors of the community should pay more attention. How will the technology teaching of university basketball general course carry out optimization of integration, to play the biggest role, is also the key point of this paper. This paper from the main content of post-modern education and university basketball general course technology teaching, to understand the current situation of university basketball education, and construct basketball general course technology evaluation system. At the same time, using fuzzy evaluation method to do statistical analysis on the situation of basketball general course technology education, and in a targeted manner to set up teaching mode of basketball general course technology under Post-modern educational perspective, use the society, network, universities' and other resources effectively, to sharing the resources, realize technology education and the optimization configuration of resource.
One aim of controlling a manipulator robot is to maximize its performances such as accuracy, speed, time etc.. However, limiting the power of actuators causes a limitation of their generalized accelerations and veloci...
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ISBN:
(纸本)9781479936694
One aim of controlling a manipulator robot is to maximize its performances such as accuracy, speed, time etc.. However, limiting the power of actuators causes a limitation of their generalized accelerations and velocities;this is due to the high inertial forces, which create dangerous voltages at the machines elements. This paper propose an algorithm to solve the problem of maximizing the manipulator performances considering that the end-effector position and orientation is characterized by a 6x1 vector i.e., six degrees of freedom;moreover, the need to move the end-effector from the start position to the target with a minimum time, without violating its boundaries. The presented solution is well suited to this context. It is optimal with respect to time constraints, and it allows a direct calculation.
In the paper, we investigate the optimization problem(OP) by applying the optimal control method. The optimization problem is reformulated as an optimal control problem(OCP) where the controller(iteration updating) is...
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In the paper, we investigate the optimization problem(OP) by applying the optimal control method. The optimization problem is reformulated as an optimal control problem(OCP) where the controller(iteration updating) is designed to minimize the sum of costs in the future time instant, which thus theoretically generates the “optimal algorithm”(fastest and most stable). By adopting the maximum principle and linearization with Taylor expansion, new algorithms are proposed. It is shown that the proposed algorithms have a superlinear convergence rate and thus converge more rapidly than the gradient descent;meanwhile, they are superior to Newton's method because they are not divergent in general and can be applied in the case of a singular or indefinite Hessian matrix. More importantly, the OCP method contains the gradient descent and the Newton's method as special cases, which discovers the theoretical basis of gradient descent and Newton's method and reveals how far these algorithms are from the optimal algorithm. The merits of the proposed optimization algorithm are illustrated by numerical experiments.
The characteristics of multilayered microwave absorbing materials are very efficient compared with those of single layer. In this article, a hybrid optimization algorithm (genetic algorithm + pattern search) combined ...
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The characteristics of multilayered microwave absorbing materials are very efficient compared with those of single layer. In this article, a hybrid optimization algorithm (genetic algorithm + pattern search) combined with transmission line matrix method has been presented. The selection of parameters, including the arrangement of layers, thickness of layers, absorption index, and shielding efficiency, forms the foundation of this process. The optimization algorithm was applied to two new multilayered structures. The first structure consists of conductive layers (CLs) of carbon nanotube (CNT) with ceramic layers of zirconium dioxide ZrO2. The second structure includes CLs of CNT with layers based on magnetite polyaniline nanomaterial (PANI_Fe3O4). Performances of both structures were evaluated in the X-band frequency range. Simulation results showed that both designs have higher absorption index picks (> 90%) and, low S-11 magnitude value with low layer thickness. This approach offers a solid foundation for future experimental trials in the development of efficient microwave absorbing and shielding structures with tunable electromagnetic performances suitable for X-band applications.
Liquefied natural gas (LNG) has a large amount of cold energy, and recovering LNG cold energy can not only reduce dependence on traditional energy and promote sustainable energy development but also reduce pollutant e...
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Liquefied natural gas (LNG) has a large amount of cold energy, and recovering LNG cold energy can not only reduce dependence on traditional energy and promote sustainable energy development but also reduce pollutant emissions, and liquified air energy storage (LAES) is an advanced energy storage technology, but its electrical round trip efficiency (ERTE) is low due to the lack of sufficient cold energy. Thus, to improve the efficiency and benefit of LNG cold energy utilization and the ERTE of LAES, an integrated power generation system combining organic Rankine cycle (ORC) with LAES driven by LNG cold energy (denoted as LNG-ORC-LAES) is proposed in this paper. The system operates in two modes, utilizing LNG cold energy at peak and off-peak times. The system is optimized under different peak electricity price scenarios by using multi-objective optimizations to achieve better performance. The LINMAP (Linear Programming Technique for Multidimensional Analysis of Preference) and TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) methods can dimensionless the optimization results and calculate the distance between each point on the optimal Pareto surfaces and the ideal point, so the two decision methods are used to screen the optimization results. The exergy efficiency and specific net output power of existing similar systems are similar to 70.31 % and similar to 94.75 kJ/kgLNG, but they can achieve 72.26 % and 124.43 kJ/kgLNG respectively after multi-objective optimization in the proposed system, and the high net present value (NPV) is obtained, the optimized system exhibits superior performance than other similar systems. The energy and exergy analysis demonstrate that the LNG cold energy utilization ratio can reach 81.96 % under optimal working conditions, the LNG cold exergy can be fully utilized by LAES. The results show that the proposed system has industrial and economic feasibility, which provides a design concept with practical significan
Under the influence of road excitations, the acquisition of optimal time-delayed feedback control parameters is deemed crucial for the improvement of the vibration reduction effect of semi-active vehicle suspension sy...
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Under the influence of road excitations, the acquisition of optimal time-delayed feedback control parameters is deemed crucial for the improvement of the vibration reduction effect of semi-active vehicle suspension systems. Moreover, different effects on vibration reduction are generally exhibited by vehicle suspension systems based on different time-delayed state feedback control. Therefore, the mechanical model of time-delayed feedback control in semi-active vehicle suspension systems is chosen as the research focus in this paper. Firstly, the optimal values of time-delayed feedback control parameters are derived through an optimization algorithm based on "equivalent harmonic excitation." Secondly, driven by the optimal values derived from optimization, this study is primarily focused on the investigation of the vibration reduction effect of time delay in a vehicle's semi-active suspension system under road excitation, thereby revealing the optimal time-delayed feedback control strategy. Finally, the study suggests that a stable state with full time delay within the effective vibration frequency range is more likely to be achieved by the semi-active vehicle suspension system based on time-delayed state feedback control of wheel vertical displacement. Additionally, the optimization efficiencies for vertical seat acceleration, vertical body acceleration, suspension travel, and tire displacement are reported as 97.73%, 98.95%, 47.30%, and 46.38%, respectively.
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