In recent years, piezoelectric actuators (PEAs) are widely used in precision positioning stage due to its outstanding advantages of small size, high displacement resolution and fast response. However, in practical app...
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ISBN:
(纸本)9781728152530
In recent years, piezoelectric actuators (PEAs) are widely used in precision positioning stage due to its outstanding advantages of small size, high displacement resolution and fast response. However, in practical applications, PEAs are also affected by the inherent nonlinear factors such as hysteresis and creep, which further results the positioning accuracy deceasing of the stage. In this paper, a modified Bouc-Wen model is proposed to identify the hysteresis characteristics of PEAs. In order to improve the identification accuracy of the model, the modified Bouc-Wen model parameters are identified by the Genetic algorithm (ga) which has a good global search capability. The experimental results show that the range of the absolute error (RAE) of the modified Bouc-Wen model is reduced by 5.87% and the average fitness value (AFV) is reduced by 4.87% compared to the standard Bouc-Wen model, which further validate the accuracy of the proposed modified Bouc-Wen model.
Under the condition that satellite communication resources are limited, how to ensure the high efficiency to ensure satellite communication tasks is one of the key issues facing satellite communication systems. This a...
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ISBN:
(数字)9781728143231
ISBN:
(纸本)9781728143231;9781728143224
Under the condition that satellite communication resources are limited, how to ensure the high efficiency to ensure satellite communication tasks is one of the key issues facing satellite communication systems. This article mainly introduces satellite communication tasks facing different task levels. Based on the improved ga algorithm, based on the analysis of satellite communication task parameter sets, it constructs satellite communication tasks through operations such as chromosome coding, fitness calculation, selection, crossover, and mutation. The dynamic allocation model and algorithm simulation are performed to compare the dynamic allocation and static fixed allocation methods. The simulation results show that the satellite communication task allocation algorithm based on ga algorithm can well satisfy the satellite communication task guarantees of different levels, and has certain reference value for improving the resource utilization of satellite communication systems.
This study achieved the goal of guiding bed design and optimization by conducting multi-objective optimization research on the performance of CNC lathe beds. In this study, Morris analysis was first performed on the s...
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This study achieved the goal of guiding bed design and optimization by conducting multi-objective optimization research on the performance of CNC lathe beds. In this study, Morris analysis was first performed on the sensitivity of the parameters, and then out to optimize the parameters using a combination of neural network and genetic algorithm. The loss function value, RMSE error accumulation, recall, sensitivity and specificity of the ASSga-BP optimization model were better. The maximum error between the predicted and true values of the ASSga-BP model was 0.28 mm. In the performance study of the multi-objective optimization method based on the Morris sensitivity analysis and the improved ga algorithm, the average MAE value is 0.91 %. The average RMSE value is 0.59 %. Also, the new model is significantly better than the NSga-II, Ega, and Fga algorithms in terms of both the number of final non-dominated solutions and the speed of reaching convergence. The above results demonstrate that the model proposed in this study has high performance, can achieve faster convergence and has the best stability of the convergence state. The innovation of this article lies in the use of the Morris method to screen and evaluate numerous parameters in order to improve the accuracy of the calculation results and ensure the effectiveness of the optimization results. The improved algorithm overcomes the problems of BP neural network and can effectively improve the generalization performance of the neural network, thereby improving the prediction accuracy of the model.
Networked Control Systerm is a distributed control system based on Network with high real-time *** a CPU connects with more than one node in NCS,the network scheduling is investigated.A new switched approach of ga alg...
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Networked Control Systerm is a distributed control system based on Network with high real-time *** a CPU connects with more than one node in NCS,the network scheduling is investigated.A new switched approach of ga algorithm with Communication Schedule is designed to integrate the performance scheduling and ve that the proposed method can improve the which reveals the effeHH∞ *** Simulation results pro∞ performance of NCS and corresponding control alrigothms are found,ctiveness of ga method.
In recent years,piezoelectric actuators (PEAs) are widely used in precision positioning stage due to its outstanding advantages of small size,high displacement resolution and fast ***,in practical applications,PEAs ar...
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ISBN:
(数字)9781728152530
ISBN:
(纸本)9781728152547
In recent years,piezoelectric actuators (PEAs) are widely used in precision positioning stage due to its outstanding advantages of small size,high displacement resolution and fast ***,in practical applications,PEAs are also affected by the inherent nonlinear factors such as hysteresis and creep,which further results the positioning accuracy deceasing of the *** this paper,a modified Bouc-Wen model is proposed to identify the hysteresis characteristics of *** order to improve the identification accuracy of the model,the modified Bouc-Wen model parameters are identified by the Genetic algorithm (ga) which has a good global search *** experimental results show that the range of the absolute error (RAE) of the modified Bouc-Wen model is reduced by 5.87% and the average fitness value (AFV) is reduced by 4.87% compared to the standard Bouc-Wen model,which further validate the accuracy of the proposed modified Bouc-Wen model.
Currently, the prediction on milk yield can help pasture managers coordinate production and transportation planning for a farm on time. However, the input of each current daily milk yield prediction research is simple...
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ISBN:
(纸本)9781728144801
Currently, the prediction on milk yield can help pasture managers coordinate production and transportation planning for a farm on time. However, the input of each current daily milk yield prediction research is simple and the current researches are not considering the time sequence characteristic of daily milk yield of dairy cows. In this study, we analyzed the correlation analysis on the input variables. After analysis, we selected parity, early lactation, peak lactation, mid-lactation, late lactation, weight, and the total amount of feed as input. we propose a prediction algorithm, ga-LSTM. The algorithm introduces the genetic algorithm (ga) into the long short-term memory (LSTM) algorithm structure, which considers the time sequence and correlations between the above input variables. The experiment demonstrates that the ga-LSTM algorithm is more accurate and stable than the traditional LSTM algorithm in predicting daily milk yields.
The growing global population and increasing scarcity of conventional fuels raise concerns about meeting power demand, particularly in remote areas with limited grid access. Hybrid renewable microgrids offer a reliabl...
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The growing global population and increasing scarcity of conventional fuels raise concerns about meeting power demand, particularly in remote areas with limited grid access. Hybrid renewable microgrids offer a reliable and cost-effective solution to this challenge. These systems typically integrate multiple components, each with varying models and technologies suited to specific conditions. Optimizing such systems and selecting appropriate technologies are critical for enhancing their performance and ensuring cost-effectiveness. This paper focuses on the optimal design, sizing, and technology selection for a hybrid renewable microgrid comprising batteries, wind turbines, and photovoltaic panels. To capture the impact of technology choices, three distinct models for each component were selected, resulting in 27 configurations optimized to identify the most suitable setup for the case study area. The Particle Swarm Optimization algorithm was employed to maximize system reliability, measured by LPSP, and economic performance, reflected in TAC. The optimization results were validated against the Genetic algorithm, a widely recognized method for optimizing similar systems, using statistical benchmark tests. The optimal configuration (PV3/WT3/B1) comprises polycrystalline photovoltaic panels, vertical-axis wind turbines, and lithium-ion batteries, achieving a TAC of $117,521 at 2 % unavailability. In contrast, the least efficient configuration (PV1/WT1/B3) includes thin-film photovoltaic panels, horizontal-axis wind turbines, and lead-acid batteries, with a TAC of $281,167 representing a 139.2 % increase, highlighting the importance of technology selection. A comprehensive sensitivity analysis was also conducted, examining key meteorological, economic, and social factors. This analysis identified the most influential parameters, validated the optimization results, and provided actionable insights for future system designs.
Pattern design has a wide range of applications in daily life, such as decoration design, web design, and so on. Common design methods include artificial design and intelligent design, and design methods based on inte...
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Pattern design has a wide range of applications in daily life, such as decoration design, web design, and so on. Common design methods include artificial design and intelligent design, and design methods based on intelligent technology tend to have higher efficiency. In order to make the generation of plane pattern intelligent design more convenient and fast, a pattern design generation method based on Reversible Jump Markov Chain Monte Carlo (RJMCMC) algorithm was proposed, and the correlation was carried out. At the same time, the same type of genetic algorithm (ga) and ant colony algorithm (AC) were introduced for performance comparison and verification. The research results show that the maximum pattern sampling accuracy of the RJMCMC algorithm is about 0.972, and the AUC value corresponding to the ROC curve is about 0.936, which are higher than other algorithms. In the algorithm iteration process, the iterative efficiency of the RJMCMC algorithm is also higher than the other two algorithms. At the same time, in the same pattern sampling processing time, the sampling number of RJMCMC algorithm is significantly higher than the other two algorithms. In the comparison of the loss value curve, the RJMCMC algorithm shows a better fitting effect, and its loss value is lower than the other two algorithms after iteration. In addition, after iteration, the error of RJMCMC algorithm is also smaller than the other two algorithms. Comprehensive analysis shows that the RJMCMC algorithm has excellent performance in pattern sampling, which can provide great help for the design and generation of plane patterns.
Recently, Mobility as a Service (MaaS) has garnered increasing attention by integrating various modes of transportation to provide users with a unified travel solution. However, In multimodal transportation planning, ...
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Recently, Mobility as a Service (MaaS) has garnered increasing attention by integrating various modes of transportation to provide users with a unified travel solution. However, In multimodal transportation planning, we primarily face three challenges: Firstly, a multimodal travel network is constructed that covers multiple travel modes and is highly scalable. Secondly, the routing algorithm fully considers the dynamic and real-time nature of the multimodal travel process. Finally, a generalized travel cost objective function is constructed that considers the psychological burden of transfers on passengers in multimodal travel scenarios. In this study, we firstly constructed an integrated multimodal transport network based on graph theory, which covers four transport modes, namely, the metro, the bus, the car-sharing and the walking. Subsequently, by introducing a double-Q learning mechanism and an optimized dynamic exploration strategy, we propose a new algorithm, Q_EDQ, the algorithm aims to learn the globally optimal path as efficiently as possible, with faster convergence speed and improved stability. Experiments utilizing real bus and metro data from Xi'an, Shaanxi Province, were conducted to compare the Q_EDQ algorithm with traditional genetic algorithms. In the conducted four experiments, compared to the optimal paths planned by traditional genetic algorithms, the improved Q-algorithm achieved a minimum efficiency increase of 12.52% and a maximum of 35%. These results demonstrate the enhanced capability of the improved Q-algorithm to learn globally optimal paths in complex multimodal transportation networks. Compared to the classical Q algorithm, the algorithmic model in this study shows an average performance improvement of 10% to 30% in global optimal path search, as well as convergence performance including loss and reward values.
Increasing the ga algorithm to find DG placements to reduce loss planning for the installation of DG locations is one factor that makes the distribution system work reliably. The installation of DG will lead to a redu...
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ISBN:
(纸本)9781665434027
Increasing the ga algorithm to find DG placements to reduce loss planning for the installation of DG locations is one factor that makes the distribution system work reliably. The installation of DG will lead to a reduction in power loss and improve the voltage value. In this study, the installation of DG in the distribution system in Lampung, Indonesia. It was modified on the system so that it became a system with 33 buses. The method used is the ga using Matlab software-power flow analysis using the newton Rapson method. Before the installation of DG, there were voltages on some buses which were below utility standards. DG is installed on four buses, increasing the voltage profile according to the utility standard 0.95-1.05. The reduction in power loss from 5.8 kW. This research can be used to repair the quality of the distribution system in Lampung, Indonesia
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