This paper is concerned with the optimal design of an obstacle located in the viscous and incompressible fluid which is driven by the steady-state Oseen equations with thermal effects. The structure of shape gradient ...This paper is concerned with the optimal design of an obstacle located in the viscous and incompressible fluid which is driven by the steady-state Oseen equations with thermal effects. The structure of shape gradient of the cost functional is derived by applying the differentiability of a minimax formulation involving a Lagrange functional with a space parametrization technique. A gradient type algorithm is employed to the shape optimization problem. Numerical examples indicate that our theory is useful for practical purpose and the proposed algorithm is feasible.展开更多
Ant colony optimization(ACO)is a random search algorithm based on probability calculation.However,the uninformed search strategy has a slow convergence speed.The Bayesian algorithm uses the historical information of t...Ant colony optimization(ACO)is a random search algorithm based on probability calculation.However,the uninformed search strategy has a slow convergence speed.The Bayesian algorithm uses the historical information of the searched point to determine the next search point during the search process,reducing the uncertainty in the random search process.Due to the ability of the Bayesian algorithm to reduce uncertainty,a Bayesian ACO algorithm is proposed in this paper to increase the convergence speed of the conventional ACO algorithm for image edge detection.In addition,this paper has the following two innovations on the basis of the classical algorithm,one of which is to add random perturbations after completing the pheromone update.The second is the use of adaptive pheromone heuristics.Experimental results illustrate that the proposed Bayesian ACO algorithm has faster convergence and higher precision and recall than the traditional ant colony algorithm,due to the improvement of the pheromone utilization rate.Moreover,Bayesian ACO algorithm outperforms the other comparative methods in edge detection task.展开更多
Multiple tuned mass dampers(MTMDs)reduce dynamic response with multiple specified frequencies of building structures.Many optimization algorithms for placement design exist,though they rarely conform to code-based ver...Multiple tuned mass dampers(MTMDs)reduce dynamic response with multiple specified frequencies of building structures.Many optimization algorithms for placement design exist,though they rarely conform to code-based verification nor produce high quality solutions without high computational effort and high complexity.This study proposes an inverse element exchange method(IEEM)with multi-level programming and compares it to a single tuned mass damper(STMD)and uniform distribution of multiple tuned mass dampers in the frequency and time domains.A ten-story shear building is used for the numerical case study.The results show that the proposed method can offer improvement over the STMD,uniform distribution of multiple tuned mass dampers,and distribution optimized by genetic algorithms(GA)with regard to minimizing the interstory drift ratio(IDR)in both the frequency and time domains and the time consumption for optimization.展开更多
The class of bi-directional optimal velocity models can describe the bi-directional looking effect that usually exists in the reality and is even enhanced with the development of the connected vehicle technologies. It...The class of bi-directional optimal velocity models can describe the bi-directional looking effect that usually exists in the reality and is even enhanced with the development of the connected vehicle technologies. Its combined string stability condition can be obtained through the method of the ring-road based string stability analysis. However, the partial string stability about traffic fluctuation propagated backward or forward was neglected, which will be analyzed in detail in this work by the method of transfer function and its H∞ norm from the viewpoint of control theory. Then, through comparing the conditions of combined and partial string stabilities, their relationships can make traffic flow be divided into three distinguishable regions, displaying various combined and partial string stability performance. Finally, the numerical experiments verify the theoretical results and find that the final displaying string stability or instability performance results from the accumulated and offset effects of traffic fluctuations propagated from different directions.展开更多
Feature Selection(FS)is a key pre-processing step in pattern recognition and data mining tasks,which can effectively avoid the impact of irrelevant and redundant features on the performance of classification models.In...Feature Selection(FS)is a key pre-processing step in pattern recognition and data mining tasks,which can effectively avoid the impact of irrelevant and redundant features on the performance of classification models.In recent years,meta-heuristic algorithms have been widely used in FS problems,so a Hybrid Binary Chaotic Salp Swarm Dung Beetle Optimization(HBCSSDBO)algorithm is proposed in this paper to improve the effect of FS.In this hybrid algorithm,the original continuous optimization algorithm is converted into binary form by the S-type transfer function and applied to the FS problem.By combining the K nearest neighbor(KNN)classifier,the comparative experiments for FS are carried out between the proposed method and four advanced meta-heuristic algorithms on 16 UCI(University of California,Irvine)datasets.Seven evaluation metrics such as average adaptation,average prediction accuracy,and average running time are chosen to judge and compare the algorithms.The selected dataset is also discussed by categorizing it into three dimensions:high,medium,and low dimensions.Experimental results show that the HBCSSDBO feature selection method has the ability to obtain a good subset of features while maintaining high classification accuracy,shows better optimization performance.In addition,the results of statistical tests confirm the significant validity of the method.展开更多
Establishing a suitable closed-loop transfer function model for the grid-connected PMSG system is the key basis in performing inter-harmonic characteristics analysis.Multiple closed-loop transfer functions can be cons...Establishing a suitable closed-loop transfer function model for the grid-connected PMSG system is the key basis in performing inter-harmonic characteristics analysis.Multiple closed-loop transfer functions can be constructed when different components of the converter controller are taken into account.However,the effect of different components of the converter controller on inter-harmonic stability analysis is not clear.In this paper,the complete transfer function,considering different loops,is first given.Based on the complete closed-loop transfer function,the DC-link,PLL and voltage forward-feed are removed step by step to derive different closed-loop transfer functions.The inter-harmonic related poles of different closed-loop transfer functions are further calculated to analyze the effect of closedloop transfer functions on inter-harmonic characteristics analysis.Finally,by performing time domain simulation,the correctness of the theoretical analysis results is verified.The results show that under the conditions of a weak AC system,each loop of the converter control system will reduce the stability of the interharmonic in the sub-synchronous frequency range and influence the inter-harmonic oscillation frequency.The transfer function needs to consider the influence of each loop to accurately calculate the inter-harmonic stability of the system.展开更多
针对某车型的噪声、振动和粗糙度(noise、vibration、harshness,NVH)性能与质量的平衡设计,采用响应面法进行车身NVH性能多学科优化。首先进行BIP模态、内饰车身(trimmed body,TB)动刚度和噪声传递函数(noise transfer function,NTF)的...针对某车型的噪声、振动和粗糙度(noise、vibration、harshness,NVH)性能与质量的平衡设计,采用响应面法进行车身NVH性能多学科优化。首先进行BIP模态、内饰车身(trimmed body,TB)动刚度和噪声传递函数(noise transfer function,NTF)的基础性能分析;然后以钣金件料厚为设计变量,采用最优拉丁方法进行实验设计(design of experiment,DOE);最后通过二次开发和模态追踪等方法获取优化响应,并创建响应面模型进行多学科优化。结果表明:在性能基本不变的前提下,车身减轻7.4 kg,减重率为3.8%。展开更多
Computational Fluid Dynamics is used to assess the thermal(heat transfer)performances of an automobile engine considering different grille opening and closing degrees.For this purpose the entire vehicle is modelled an...Computational Fluid Dynamics is used to assess the thermal(heat transfer)performances of an automobile engine considering different grille opening and closing degrees.For this purpose the entire vehicle is modelled and three fundamental aspects are examined,namely,the open area of the air intake grille,the position of the upper and lower grilles and their shape.The results show that the opening area and position of the grille have some influence also on the aerodynamic characteristics of the automobile.With an increase in the opening angle of the grille,the CD(Drag Coefficient)value of the whole vehicle becomes higher.When the air intake grille of the car is fully open or closed,the CD value is 0.35434 or 0.31777,respectively,that is,the flow resistance in the engine compartment accounts for 10.32%of the CD value for the whole automobile.展开更多
A new fuzzy optimization neural network model is proposed based on the Levenberg-Marquardt (LM) algorithm on account of the disadvantages of slow convergence of traditional fuzzy optimization neural network model. In ...A new fuzzy optimization neural network model is proposed based on the Levenberg-Marquardt (LM) algorithm on account of the disadvantages of slow convergence of traditional fuzzy optimization neural network model. In this new model,the gradient descent algorithm is replaced by the LM algorithm to obtain the minimum of output errors during network training,which changes the weights adjusting equations of the network and increases the training speed. Moreover,to avoid the results yielding to local minimum,the transfer function is also revised to sigmoid function. A case study is utilized to validate this new model,and the results reveal that the new model fast training speed and better forecasting capability.展开更多
Purpose: Children are sometimes examined with Computed Tomography protocols designed for adults, leading to radiation doses higher than necessary. Lack of optimisation could lead to image quality higher than what is n...Purpose: Children are sometimes examined with Computed Tomography protocols designed for adults, leading to radiation doses higher than necessary. Lack of optimisation could lead to image quality higher than what is needed for diagnostic purposes with associated high doses to patients. Optimising the protocols for paediatric head trauma CT imaging will reduce radiation dose. Objective: The study aimed to optimise radiation dose and assess the image quality for a set of protocols by evaluating noise, a contrast to noise ratio, modulation transfer function and noise power spectrum. Methods: Somaton Sensation 64 was used to scan the head of an anthropomorphic phantom with a set of protocols. ImageJ software was used to analyse the paediatric head image from the scanner. IMPACTSCAN dosimeter software was used to evaluate the radiation dose to the various organs in the head. MATLAB was used to analyse the Modulation Transfer Function and the Noise Power. Results: The estimated Computed Tomography Dose Index volume (CTDI<sub>vol</sub>) increased with increasing tube current and tube voltage. The high pitch of 0.9 gave a lower dose than the 0.5 pitch. The eye lens received the highest radiation dose (39.2 mGy) whiles the thyroid received the least radiation dose (13.7 mGy). There was an increase in noise (62.46) when the H60 kernel was used and a lower noise (8.829) was noticed when the H30 kernel was used. Conclusion: The results obtained show that the H30 kernel (smooth kernel) gave higher values for noise and contrast to noise ratio (CNR) than the H60 kernel (sharp kernel). The H60 kernel produced high values for the modulation transfer function (MTF) and noise power spectrum (NPS). The eye lens received the highest radiation dose.展开更多
The electric power transfer capability on the Manitoba-Ontario interconnection depends on various system operating conditions such as area generation patterns and ambient temperatures. This work models the power netwo...The electric power transfer capability on the Manitoba-Ontario interconnection depends on various system operating conditions such as area generation patterns and ambient temperatures. This work models the power network as a black-box function, which is evaluated with the system reliability analysis techniques to determine the maximum transfer capability under a given operating condition. A metamodel or an approximation model of the maximized power transfer capability is built based on the sampled system responses and optimized with respect to the corresponding operating conditions. An optimal metamodel is implemented as a prototype software tool, PTCanalyzer, and applied to Manitoba-Ontario interconnection power transfer calculations. This optimized metamodel technique provides an in-depth understanding of the dependency of the power transfer capability on system operating conditions and proves to be an effective tool in optimizing the operation planning of the interconnection for a given power system configuration. The PTCanalyzer has the potential to be used for optimization of other power network interconnections.展开更多
文摘This paper is concerned with the optimal design of an obstacle located in the viscous and incompressible fluid which is driven by the steady-state Oseen equations with thermal effects. The structure of shape gradient of the cost functional is derived by applying the differentiability of a minimax formulation involving a Lagrange functional with a space parametrization technique. A gradient type algorithm is employed to the shape optimization problem. Numerical examples indicate that our theory is useful for practical purpose and the proposed algorithm is feasible.
基金supported by the National Natural Science Foundation of China(62276055).
文摘Ant colony optimization(ACO)is a random search algorithm based on probability calculation.However,the uninformed search strategy has a slow convergence speed.The Bayesian algorithm uses the historical information of the searched point to determine the next search point during the search process,reducing the uncertainty in the random search process.Due to the ability of the Bayesian algorithm to reduce uncertainty,a Bayesian ACO algorithm is proposed in this paper to increase the convergence speed of the conventional ACO algorithm for image edge detection.In addition,this paper has the following two innovations on the basis of the classical algorithm,one of which is to add random perturbations after completing the pheromone update.The second is the use of adaptive pheromone heuristics.Experimental results illustrate that the proposed Bayesian ACO algorithm has faster convergence and higher precision and recall than the traditional ant colony algorithm,due to the improvement of the pheromone utilization rate.Moreover,Bayesian ACO algorithm outperforms the other comparative methods in edge detection task.
文摘Multiple tuned mass dampers(MTMDs)reduce dynamic response with multiple specified frequencies of building structures.Many optimization algorithms for placement design exist,though they rarely conform to code-based verification nor produce high quality solutions without high computational effort and high complexity.This study proposes an inverse element exchange method(IEEM)with multi-level programming and compares it to a single tuned mass damper(STMD)and uniform distribution of multiple tuned mass dampers in the frequency and time domains.A ten-story shear building is used for the numerical case study.The results show that the proposed method can offer improvement over the STMD,uniform distribution of multiple tuned mass dampers,and distribution optimized by genetic algorithms(GA)with regard to minimizing the interstory drift ratio(IDR)in both the frequency and time domains and the time consumption for optimization.
基金Projects(51108465,71371192)supported by the National Natural Science Foundation of ChinaProject(2014M552165)supported by China Postdoctoral Science FoundationProject(20113187851460)supported by Technology Project of the Ministry of Transport of China
文摘The class of bi-directional optimal velocity models can describe the bi-directional looking effect that usually exists in the reality and is even enhanced with the development of the connected vehicle technologies. Its combined string stability condition can be obtained through the method of the ring-road based string stability analysis. However, the partial string stability about traffic fluctuation propagated backward or forward was neglected, which will be analyzed in detail in this work by the method of transfer function and its H∞ norm from the viewpoint of control theory. Then, through comparing the conditions of combined and partial string stabilities, their relationships can make traffic flow be divided into three distinguishable regions, displaying various combined and partial string stability performance. Finally, the numerical experiments verify the theoretical results and find that the final displaying string stability or instability performance results from the accumulated and offset effects of traffic fluctuations propagated from different directions.
基金This research was funded by the Short-Term Electrical Load Forecasting Based on Feature Selection and optimized LSTM with DBO which is the Fundamental Scientific Research Project of Liaoning Provincial Department of Education(JYTMS20230189)the Application of Hybrid Grey Wolf Algorithm in Job Shop Scheduling Problem of the Research Support Plan for Introducing High-Level Talents to Shenyang Ligong University(No.1010147001131).
文摘Feature Selection(FS)is a key pre-processing step in pattern recognition and data mining tasks,which can effectively avoid the impact of irrelevant and redundant features on the performance of classification models.In recent years,meta-heuristic algorithms have been widely used in FS problems,so a Hybrid Binary Chaotic Salp Swarm Dung Beetle Optimization(HBCSSDBO)algorithm is proposed in this paper to improve the effect of FS.In this hybrid algorithm,the original continuous optimization algorithm is converted into binary form by the S-type transfer function and applied to the FS problem.By combining the K nearest neighbor(KNN)classifier,the comparative experiments for FS are carried out between the proposed method and four advanced meta-heuristic algorithms on 16 UCI(University of California,Irvine)datasets.Seven evaluation metrics such as average adaptation,average prediction accuracy,and average running time are chosen to judge and compare the algorithms.The selected dataset is also discussed by categorizing it into three dimensions:high,medium,and low dimensions.Experimental results show that the HBCSSDBO feature selection method has the ability to obtain a good subset of features while maintaining high classification accuracy,shows better optimization performance.In addition,the results of statistical tests confirm the significant validity of the method.
基金supported by Research Project Huadong Engineering Corporation Limited,and National Natural Science Foundation of China(U22B20100,52321004).
文摘Establishing a suitable closed-loop transfer function model for the grid-connected PMSG system is the key basis in performing inter-harmonic characteristics analysis.Multiple closed-loop transfer functions can be constructed when different components of the converter controller are taken into account.However,the effect of different components of the converter controller on inter-harmonic stability analysis is not clear.In this paper,the complete transfer function,considering different loops,is first given.Based on the complete closed-loop transfer function,the DC-link,PLL and voltage forward-feed are removed step by step to derive different closed-loop transfer functions.The inter-harmonic related poles of different closed-loop transfer functions are further calculated to analyze the effect of closedloop transfer functions on inter-harmonic characteristics analysis.Finally,by performing time domain simulation,the correctness of the theoretical analysis results is verified.The results show that under the conditions of a weak AC system,each loop of the converter control system will reduce the stability of the interharmonic in the sub-synchronous frequency range and influence the inter-harmonic oscillation frequency.The transfer function needs to consider the influence of each loop to accurately calculate the inter-harmonic stability of the system.
文摘针对某车型的噪声、振动和粗糙度(noise、vibration、harshness,NVH)性能与质量的平衡设计,采用响应面法进行车身NVH性能多学科优化。首先进行BIP模态、内饰车身(trimmed body,TB)动刚度和噪声传递函数(noise transfer function,NTF)的基础性能分析;然后以钣金件料厚为设计变量,采用最优拉丁方法进行实验设计(design of experiment,DOE);最后通过二次开发和模态追踪等方法获取优化响应,并创建响应面模型进行多学科优化。结果表明:在性能基本不变的前提下,车身减轻7.4 kg,减重率为3.8%。
文摘Computational Fluid Dynamics is used to assess the thermal(heat transfer)performances of an automobile engine considering different grille opening and closing degrees.For this purpose the entire vehicle is modelled and three fundamental aspects are examined,namely,the open area of the air intake grille,the position of the upper and lower grilles and their shape.The results show that the opening area and position of the grille have some influence also on the aerodynamic characteristics of the automobile.With an increase in the opening angle of the grille,the CD(Drag Coefficient)value of the whole vehicle becomes higher.When the air intake grille of the car is fully open or closed,the CD value is 0.35434 or 0.31777,respectively,that is,the flow resistance in the engine compartment accounts for 10.32%of the CD value for the whole automobile.
基金Sponsored by the National Natural Science Foundation of China (Grant No. 50579095)Ertan Hydropower Development Company, LTD.
文摘A new fuzzy optimization neural network model is proposed based on the Levenberg-Marquardt (LM) algorithm on account of the disadvantages of slow convergence of traditional fuzzy optimization neural network model. In this new model,the gradient descent algorithm is replaced by the LM algorithm to obtain the minimum of output errors during network training,which changes the weights adjusting equations of the network and increases the training speed. Moreover,to avoid the results yielding to local minimum,the transfer function is also revised to sigmoid function. A case study is utilized to validate this new model,and the results reveal that the new model fast training speed and better forecasting capability.
文摘Purpose: Children are sometimes examined with Computed Tomography protocols designed for adults, leading to radiation doses higher than necessary. Lack of optimisation could lead to image quality higher than what is needed for diagnostic purposes with associated high doses to patients. Optimising the protocols for paediatric head trauma CT imaging will reduce radiation dose. Objective: The study aimed to optimise radiation dose and assess the image quality for a set of protocols by evaluating noise, a contrast to noise ratio, modulation transfer function and noise power spectrum. Methods: Somaton Sensation 64 was used to scan the head of an anthropomorphic phantom with a set of protocols. ImageJ software was used to analyse the paediatric head image from the scanner. IMPACTSCAN dosimeter software was used to evaluate the radiation dose to the various organs in the head. MATLAB was used to analyse the Modulation Transfer Function and the Noise Power. Results: The estimated Computed Tomography Dose Index volume (CTDI<sub>vol</sub>) increased with increasing tube current and tube voltage. The high pitch of 0.9 gave a lower dose than the 0.5 pitch. The eye lens received the highest radiation dose (39.2 mGy) whiles the thyroid received the least radiation dose (13.7 mGy). There was an increase in noise (62.46) when the H60 kernel was used and a lower noise (8.829) was noticed when the H30 kernel was used. Conclusion: The results obtained show that the H30 kernel (smooth kernel) gave higher values for noise and contrast to noise ratio (CNR) than the H60 kernel (sharp kernel). The H60 kernel produced high values for the modulation transfer function (MTF) and noise power spectrum (NPS). The eye lens received the highest radiation dose.
文摘The electric power transfer capability on the Manitoba-Ontario interconnection depends on various system operating conditions such as area generation patterns and ambient temperatures. This work models the power network as a black-box function, which is evaluated with the system reliability analysis techniques to determine the maximum transfer capability under a given operating condition. A metamodel or an approximation model of the maximized power transfer capability is built based on the sampled system responses and optimized with respect to the corresponding operating conditions. An optimal metamodel is implemented as a prototype software tool, PTCanalyzer, and applied to Manitoba-Ontario interconnection power transfer calculations. This optimized metamodel technique provides an in-depth understanding of the dependency of the power transfer capability on system operating conditions and proves to be an effective tool in optimizing the operation planning of the interconnection for a given power system configuration. The PTCanalyzer has the potential to be used for optimization of other power network interconnections.
