An aircraft tractor plays a significant role as a kind of important marine transport and support equipment. It＇s necessary to study its controlling and manoeuvring stability to improve operation efficiency. A virtual...An aircraft tractor plays a significant role as a kind of important marine transport and support equipment. It＇s necessary to study its controlling and manoeuvring stability to improve operation efficiency. A virtual prototyping model of the tractor-aircraft system based on Lagrange＇s equation of the first kind with Lagrange mutipliers was established in this paper, According to the towing characteristics, a path-tracking controller using fuzzy logic theory was designed. Direction control herein was carried out through a compensatory tracking approach. Interactive co-simulation was performed to validate the path-tracking behavior in closed-loop, Simulation results indicated that the tractor followed the reference courses precisely on a flat ground.展开更多
This paper presents a constructive design of new controllers that force underactuated ships under constant or slow time-varying sea loads to asymptotically track a parameterized reference path, that guarantees the dis...This paper presents a constructive design of new controllers that force underactuated ships under constant or slow time-varying sea loads to asymptotically track a parameterized reference path, that guarantees the distance from the ship to the reference path always be within a specified value. The control design is based on a global exponential disturbance observer, a transformation of the ship dynamics to an almost spherical form, an interpretation of the tracking errors in an earth-fixed frame, an introduction of dynamic variables to compensate for relaxation of the reference path generation, p-times differentiable step functions, and backstepping and Lyapunov＇s direct methods. The effectiveness of the proposed results is illustrated through simulations.展开更多
This paper proposes an adaptive-neural-network based robust hierarchical path-tracking controller for autonomous fourwheel-independent-drive electric vehicles(4WID-EVs)with parametric uncertainties and external distur...This paper proposes an adaptive-neural-network based robust hierarchical path-tracking controller for autonomous fourwheel-independent-drive electric vehicles(4WID-EVs)with parametric uncertainties and external disturbances.Firstly,considering the uncertain tire cornering stiffness and longitudinal speed,a control-oriented mismatched norm bounded uncertain system model of 4WID-EVs is established by using Takagi–Sugeno(T–S)fuzzy modeling approach.Secondly,an adaptive integral sliding mode controller combined with radial basis function neural network(RBFNN)is proposed,in which an improved RBFNN is used to approximate uncertain dynamics to improve tracking performance and reduce chattering.A sufficient condition for the asymptotic stability of sliding mode dynamics is given based on linear matrix inequality.According to Lyapunov theory,it has been proved that the estimation errors are bounded and finally converge near the origin.Further,a novel torque vectoring algorithm is introduced to allocate longitudinal driving force and additional yaw moment,aiming to reduce tire load rate and slip energy consumption,in which the weights assigned to the two objective functions are determined by taking into account the customized vehicle stability index and slip rate.Finally,the simulation results conducted on the CarSim-Simulink platform confirm the outstanding tracking and energy-efficient performance of the proposed controller.展开更多
As the demands for environmental sustainability and the requirements to lower carbon emissions have escalated,New Energy Vehicles(NEVs)have emerged as a compelling substitute for fossil-fuel-run automobiles.Hence,a sm...As the demands for environmental sustainability and the requirements to lower carbon emissions have escalated,New Energy Vehicles(NEVs)have emerged as a compelling substitute for fossil-fuel-run automobiles.Hence,a smart energy management strategy has been developed to enhance the performance of NEVs,maximizing the sustainability of transportation systems and minimizing environmental impacts.The system combines different power reserves,includ-ing a photovoltaic(PV)generator,fuel cell(FC),and battery system,to provide a continuous energy supply,even when the vehicle is running.The Multi-Directional Power Transfer converter for the battery provides the required energy ad-aptation between the input and output.The FC and PV systems are all connected through a direct current/direct current converter to effectively charge the battery whenever excess energy is present.The new energy management technique called Optimized Ant Colony Algorithm is proposed to dynamically allocate power among the different power sources,improving system efficiency.Unlike traditional methods,the suggested approach actively optimizes energy flow accord-ing to actual demand and availability,minimizing energy losses and enhancing sustainability.The MATLAB/Simulink tool was used to simulate the energetic performance of an electric car utilizing the suggested approach.The performance of this multi-source power system is assessed by contrasting the energy the PV and FC generating devices offer,and the energy generation of each recharge system.Additionally,the battery power comparison validates the cost-effectiveness and sustainability of the proposed model in NEVs.Results designate a significant improvement in energy efficiency and overall NEV environmental sustainability within contemporary transportation networks.展开更多
The belief rule-based(BRB)system has been popular in complexity system modeling due to its good interpretability.However,the current mainstream optimization methods of the BRB systems only focus on modeling accuracy b...The belief rule-based(BRB)system has been popular in complexity system modeling due to its good interpretability.However,the current mainstream optimization methods of the BRB systems only focus on modeling accuracy but ignore the interpretability.The single-objective optimization strategy has been applied in the interpretability-accuracy trade-off by inte-grating accuracy and interpretability into an optimization objec-tive.But the integration has a greater impact on optimization results with strong subjectivity.Thus,a multi-objective optimiza-tion framework in the modeling of BRB systems with inter-pretability-accuracy trade-off is proposed in this paper.Firstly,complexity and accuracy are taken as two independent opti-mization goals,and uniformity as a constraint to give the mathe-matical description.Secondly,a classical multi-objective opti-mization algorithm,nondominated sorting genetic algorithm II(NSGA-II),is utilized as an optimization tool to give a set of BRB systems with different accuracy and complexity.Finally,a pipeline leakage detection case is studied to verify the feasibility and effectiveness of the developed multi-objective optimization.The comparison illustrates that the proposed multi-objective optimization framework can effectively avoid the subjectivity of single-objective optimization,and has capability of joint optimiz-ing the structure and parameters of BRB systems with inter-pretability-accuracy trade-off.展开更多
In a tractor automatic navigation system, path planning plays a significant role in improving operation efficiency. This study aims to create a suboptimal reference course for headland turning of a robot tractor and d...In a tractor automatic navigation system, path planning plays a significant role in improving operation efficiency. This study aims to create a suboptimal reference course for headland turning of a robot tractor and design a path-tracking controller to guide the robot tractor along the reference course. A time-minimum suboptimal control method was used to generate the reference turning course based on the mechanical parameters of the test tractor. A path-tracking controller consisting of both feedforward and feedback component elements was also proposed. The feedforward component was directly determined by the desired steering angle of the current navigation point on the reference course, whereas the feedback component was derived from the designed optimal controller. Computer simulation and field tests were performed to validate the path-tracking performance. Field test results indicated that the robot tractor followed the reference courses precisely on flat meadow, with average and standard lateral devia- tions being 0.031 m and 0.086 m, respectively. However, the tracking error increased while operating on sloping meadow due to the employed vehicle kinematic model.展开更多
Abstract： In the hot strip rolling control system, the temperature distribution and deformation resistance are the main parameters affecting prediction of rolling force. In order to improve the model prediction preci...Abstract： In the hot strip rolling control system, the temperature distribution and deformation resistance are the main parameters affecting prediction of rolling force. In order to improve the model prediction precision, an optimiza- tion algorithm based on objective function was put forward, in which the penalty function index was adopted. During the adaptation process, the temperature distribution and deformation resistance were taken as the optimized parame ters, and the Nelder-Mead simplex algorithm was used to search the optimal solution of the objective function. Fur thermore, the temperature adaptation and force adaptation were solved simultaneously. Application results show that the method can improve the accuracy of the rolling force model obviously, and it can meet the demand of the indus trial production and has a good application prospect.展开更多
The size and shape of the foveal avascular zone(FAZ)have a strong positive correlation with several vision-threatening ret inovascular diseases.The identification,segmentation and analysis of FAZ are of great signific...The size and shape of the foveal avascular zone(FAZ)have a strong positive correlation with several vision-threatening ret inovascular diseases.The identification,segmentation and analysis of FAZ are of great significance to clinical diagnosis and treatment.We presented an adaptive watershed algorithm to automatically extract F AZ from retinal optical coherence tomography angiography(OCTA)images.For the traditional watershed algorithm,"over-segmentation"is the most common problem.FAZ is often incorrectly divided into multiple regions by redundant"dams".This paper analyzed the relationship between the"dams"length and the maximum inscribed circle radius of FAZ,and proposed an adaptive watershed algorithm to solve the problem of"over-segmentation".Here,132 healthy retinal images and 50 diabetic retinopathy(DR)images were used to verify the accuracy and stability of the algorithm.Three ophthal-mologists were invited to make quan titative and qualitative evaluations on the segmentation results of this algorithm.The quantitative evaluation results show that the correlation coffi-cients between the automatic and manual segmentation results are 0.945(in healthy subjects)and 0.927(in DR patients),respectively.For qualitative evaluation,the percentages of"perfect segmentation"(score of 3)and"good segmentation"(score of 2)are 99.4%(in healthy subjects)and 98.7%(in DR patients),respectively.This work promotes the application of watershed algorithm in FAZ segmentation,making it a useful tool for analyzing and diagnosing eye diseases.展开更多
The random variables are always truncated in aerospace engineering and the truncated distribution is more feasible and effective for the random variables due to the limited samples available.For high-reliability aeros...The random variables are always truncated in aerospace engineering and the truncated distribution is more feasible and effective for the random variables due to the limited samples available.For high-reliability aerospace mechanism with truncated random variables, a method based on artificial bee colony（ABC） algorithm and line sampling（LS） is proposed.The artificial bee colony-based line sampling（ABCLS） method presents a multi-constrained optimization model to solve the potential non-convergence problem when calculating design point（is also as most probable point, MPP） of performance function with truncated variables; by implementing ABC algorithm to search for MPP in the standard normal space, the optimization efficiency and global searching ability are increased with this method dramatically.When calculating the reliability of aerospace mechanism with too small failure probability, the Monte Carlo simulation method needs too large sample size.The ABCLS method could overcome this drawback.For reliability problems with implicit functions, this paper combines the ABCLS with Kriging response surface method,therefore could alleviate computational burden of calculating the reliability of complex aerospace mechanism.A numerical example and an engineering example are carried out to verify this method and prove the applicability.展开更多
As a new variant of vehicle routing problem( VRP),a finished vehicle routing problem with time windows in finished vehicle logistics( FVRPTW) is modeled and solved. An optimization model for FVRPTW is presented with t...As a new variant of vehicle routing problem( VRP),a finished vehicle routing problem with time windows in finished vehicle logistics( FVRPTW) is modeled and solved. An optimization model for FVRPTW is presented with the objective of scheduling multiple transport routes considering loading constraints along with time penalty function to minimize the total cost. Then a genetic algorithm( GA) is developed. The specific encoding and genetic operators for FVRPTW are devised.Especially,in order to accelerate its convergence,an improved termination condition is given. Finally,a case study is used to evaluate the effectiveness of the proposed algorithm and a series of experiments are conducted over a set of finished vehicle routing problems. The results demonstrate that the proposed approach has superior performance and satisfies users in practice. Contributions of the study are the modeling and solving of a complex FVRPTW in logistics industry.展开更多
We suggest a design method of graded-refractive-index （GRIN） antireflection （AR） coating for s-polarized or p- polarized light at off-normal incidence. The spectrum characteristic of the designed antireflection co...We suggest a design method of graded-refractive-index （GRIN） antireflection （AR） coating for s-polarized or p- polarized light at off-normal incidence. The spectrum characteristic of the designed antireflection coating with a quintic effective refractive-index profile for a given state of polarization has been discussed. In addition, the genetic algorithm was used to optimize the refractive index profile of the GRIN antireflection for reducing the mean reflectance of s- and p-polarizations. The average reflectance loss was reduced to only 0.04% by applying optimized GRIN AR coatings onto BK7 glass over the wavelength range from 400 to 800 nm at the incident angle of θo = 70°.展开更多
With the increasing demands of health care,the design of hospital buildings has become increasingly demanding and complicated.However,the traditional layout design method for hospital is labor intensive,time consuming...With the increasing demands of health care,the design of hospital buildings has become increasingly demanding and complicated.However,the traditional layout design method for hospital is labor intensive,time consuming and prone to errors.With the development of artificial intelligence(AI),the intelligent design method has become possible and is considered to be suitable for the layout design of hospital buildings.Two intelli-gent design processes based on healthcare systematic layout planning(HSLP)and generative adversarial network(GAN)are proposed in this paper,which aim to solve the generation problem of the plane functional layout of the operating departments(ODs)of general hospitals.The first design method that is more like a mathemati-cal model with traditional optimization algorithm concerns the following two steps:developing the HSLP model based on the conventional systematic layout planning(SLP)theory,identifying the relationship and flows amongst various departments/units,and arriving at the preliminary plane layout design;establishing mathematical model to optimize the building layout by using the genetic algorithm(GA)to obtain the optimized scheme.The specific process of the second intelligent design based on more than 100 sets of collected OD drawings includes:labelling the corresponding functional layouts of each OD plan;building image-to-image translation with conditional ad-versarial network(pix2pix)for training OD plane layouts,which is one of the most representative GAN models.Finally,the functions and features of the results generated by the two methods are analyzed and compared from an architectural and algorithmic perspective.Comparison of the two design methods shows that the HSLP and GAN models can autonomously generate new OD plane functional layouts.The HSLP layouts have clear functional area adjacencies and optimization goals,but the layouts are relatively rigid and not specific enough.The GAN outputs are the most innovative layouts with strong applicability,but the dataset has strict constraints.The goal of this paper is to help release the heavy load of architects in the early design stage and present the effectiveness of these intelligent design methods in the field of medical architecture.展开更多
The spectrum sharing problem between primary and cognitive users is mainly investigated. Since the interference for primary users and the total power for cognitive users are constrained, based on the well-known water-...The spectrum sharing problem between primary and cognitive users is mainly investigated. Since the interference for primary users and the total power for cognitive users are constrained, based on the well-known water-filling theorem, a novel one-user water-filling algorithm is proposed, and then the corresponding simulation results are given to analyze the feasibility and validity. After that this algorithm is used to solve the communication utility optimization problem subject to the power constraints in cognitive radio network. First, through the gain to noise ratio for cognitive users, a subcarrier and power allocation algorithm based on the optimal frequency partition is proposed for two cognitive users. Then the spectrum sharing algorithm is extended to multiuser conditions such that the greedy and parallel algorithms are proposed for spectrum sharing. Theory and simulation analysis show that the subcarrier and power allocation algorithms can not only protect the primary users but also effectively solve the spectrum and power allocation problem for cognitive users.展开更多
Experiment statistical method and genetic algorithms based optimization method are used to obtain the optimum differential gear ratio for heavy truck that provides best fuel consumption when changing the working condi...Experiment statistical method and genetic algorithms based optimization method are used to obtain the optimum differential gear ratio for heavy truck that provides best fuel consumption when changing the working condition that affects its torque and speed range. The aim of the study is to obtain the optimum differential gear ratio with fast and accurate optimization calculation without affecting drivability characteristics of the vehicle according to certain driving cycles that represent the new working conditions of the truck. The study is carried on a mining dump truck YT3621 with 9 for- ward shift manual transmission. Two loading conditions, no load and 40 t, and four on road real driving cycles have been discussed. The truck powertrain is modeled using GT-drive, and DOE -post processing tool of the GT-suite is used for DOE analysis and genetic algorithm optimization.展开更多
A Genetic Algorithm-Ant Colony Algorithm(GA-ACA),which can be used to optimize multi-Unit Under Test(UUT)parallel test tasks sequences and resources configuration quickly and accurately,is proposed in the paper.With t...A Genetic Algorithm-Ant Colony Algorithm(GA-ACA),which can be used to optimize multi-Unit Under Test(UUT)parallel test tasks sequences and resources configuration quickly and accurately,is proposed in the paper.With the establishment of the mathematic model of multi-UUT parallel test tasks and resources,the condition of multi-UUT resources mergence is analyzed to obtain minimum resource requirement under minimum test time.The definition of cost efficiency is put forward,followed by the design of gene coding and path selection project,which can satisfy multi-UUT parallel test tasks scheduling.At the threshold of the algorithm,GA is adopted to provide initial pheromone for ACA,and then dual-convergence pheromone feedback mode is applied in ACA to avoid local optimization and parameters dependence.The practical application proves that the algorithm has a remarkable effect on solving the problems of multi-UUT parallel test tasks scheduling and resources configuration.展开更多
GM(1,1)models have been widely used in various fields due to their high performance in time series prediction.However,some hypotheses of the existing GM(1,1)model family may reduce their prediction performance in some...GM(1,1)models have been widely used in various fields due to their high performance in time series prediction.However,some hypotheses of the existing GM(1,1)model family may reduce their prediction performance in some cases.To solve this problem,this paper proposes a self-adaptive GM(1,1)model,termed as SAGM(1,1)model,which aims to solve the defects of the existing GM(1,1)model family by deleting their modeling hypothesis.Moreover,a novel multi-parameter simultaneous optimization scheme based on firefly algorithm is proposed,the proposed multi-parameter optimization scheme adopts machine learning ideas,takes all adjustable parameters of SAGM(1,1)model as input variables,and trains it with firefly algorithm.And Sobol’sensitivity indices are applied to study global sensitivity of SAGM(1,1)model parameters,which provides an important reference for model parameter calibration.Finally,forecasting capability of SAGM(1,1)model is illustrated by Anhui electricity consumption dataset.Results show that prediction accuracy of SAGM(1,1)model is significantly better than other models,and it is shown that the proposed approach enhances the prediction performance of GM(1,1)model significantly.展开更多
Public key cryptographic （PKC） algorithms, such as the RSA, elliptic curve digital signature algorithm （ECDSA） etc., are widely used in the secure communication sys- tems, such as OpenSSL, and a variety of in- for...Public key cryptographic （PKC） algorithms, such as the RSA, elliptic curve digital signature algorithm （ECDSA） etc., are widely used in the secure communication sys- tems, such as OpenSSL, and a variety of in- formation security systems. If designer do not securely implement them, the secret key will be easily extracted by side-channel attacks （SCAs） or combinational SCA thus mitigat- ing the security of the entire communication system. Previous countermeasures of PKC im- plementations focused on the core part of the algorithms and ignored the modular inversion which is widely used in various PKC schemes. Many researchers believe that instead of straightforward implementation, constant time modular inversion （CTMI） is enough to resist the attack of simple power analysis combined with lattice analysis. However, we find that the CTMI security can be reduced to a hidden t-bit multiplier problem. Based on this feature, we firstly obtain Hamming weight of interme- diate data through side-channel leakage. Then, we propose a heuristic algorithm to solve the problem by revealing the secret （partial and full） base of CTMI. Comparing previous nec-essary input message for masking filtering, our procedure need not any information about the secret base of the inversion. To our knowl- edge, this is the first time for evaluating the practical security of CTM! and experimental results show the fact that CTMI is not enough for high-level secure communication systems.展开更多
Currently, the article analyzes the CAN bus＇s rule of priority＇s arbitration bit by bit without destroy. It elicits the conclusion that if static priority based on the affirmatory system model is used, the lower pri...Currently, the article analyzes the CAN bus＇s rule of priority＇s arbitration bit by bit without destroy. It elicits the conclusion that if static priority based on the affirmatory system model is used, the lower priority＇s messages will be delayed considerably more, even some data will be lost when the bus＇s bandwidth is widely used. The scheduling cannot be modified neither during the system when static priority is used. The dynamic priority promoting method and the math model of SQSA and SQMA are presented; it analyzes the model＇s rate of taking in and sending out in large quantities, the largest delay, the problems and solutions when using SQMA. In the end, it is confirmed that the method of improving dynamic priority has good performances on the network rate of taking in and sending out in large quantities, the average delay, and the rate of network usage by emulational experiments.展开更多
Since the 5-steps rule was proposed in 2011, it has been widely used in many areas of molecular biology, both theoretical and experimental. It can be even used to deal with the commercial problems and bank systems, as...Since the 5-steps rule was proposed in 2011, it has been widely used in many areas of molecular biology, both theoretical and experimental. It can be even used to deal with the commercial problems and bank systems, as well as material science systems. Just like the machine-learning algorithms, it is the jade for nearly all the statistical systems.展开更多
基金Harbin Technological Innovation Research Fund(NO:2012RFXXG039)
文摘An aircraft tractor plays a significant role as a kind of important marine transport and support equipment. It＇s necessary to study its controlling and manoeuvring stability to improve operation efficiency. A virtual prototyping model of the tractor-aircraft system based on Lagrange＇s equation of the first kind with Lagrange mutipliers was established in this paper, According to the towing characteristics, a path-tracking controller using fuzzy logic theory was designed. Direction control herein was carried out through a compensatory tracking approach. Interactive co-simulation was performed to validate the path-tracking behavior in closed-loop, Simulation results indicated that the tractor followed the reference courses precisely on a flat ground.
基金Supported in Part by the Australian Research Council Under Grant No.DP0988424
文摘This paper presents a constructive design of new controllers that force underactuated ships under constant or slow time-varying sea loads to asymptotically track a parameterized reference path, that guarantees the distance from the ship to the reference path always be within a specified value. The control design is based on a global exponential disturbance observer, a transformation of the ship dynamics to an almost spherical form, an interpretation of the tracking errors in an earth-fixed frame, an introduction of dynamic variables to compensate for relaxation of the reference path generation, p-times differentiable step functions, and backstepping and Lyapunov＇s direct methods. The effectiveness of the proposed results is illustrated through simulations.
基金support of the National Natural Science Foundation of China[grant number 52472411,52272397]the Key Research&Development and Achievement Transformation Program of Wuhu[grant number 2023YF010].
文摘This paper proposes an adaptive-neural-network based robust hierarchical path-tracking controller for autonomous fourwheel-independent-drive electric vehicles(4WID-EVs)with parametric uncertainties and external disturbances.Firstly,considering the uncertain tire cornering stiffness and longitudinal speed,a control-oriented mismatched norm bounded uncertain system model of 4WID-EVs is established by using Takagi–Sugeno(T–S)fuzzy modeling approach.Secondly,an adaptive integral sliding mode controller combined with radial basis function neural network(RBFNN)is proposed,in which an improved RBFNN is used to approximate uncertain dynamics to improve tracking performance and reduce chattering.A sufficient condition for the asymptotic stability of sliding mode dynamics is given based on linear matrix inequality.According to Lyapunov theory,it has been proved that the estimation errors are bounded and finally converge near the origin.Further,a novel torque vectoring algorithm is introduced to allocate longitudinal driving force and additional yaw moment,aiming to reduce tire load rate and slip energy consumption,in which the weights assigned to the two objective functions are determined by taking into account the customized vehicle stability index and slip rate.Finally,the simulation results conducted on the CarSim-Simulink platform confirm the outstanding tracking and energy-efficient performance of the proposed controller.
文摘As the demands for environmental sustainability and the requirements to lower carbon emissions have escalated,New Energy Vehicles(NEVs)have emerged as a compelling substitute for fossil-fuel-run automobiles.Hence,a smart energy management strategy has been developed to enhance the performance of NEVs,maximizing the sustainability of transportation systems and minimizing environmental impacts.The system combines different power reserves,includ-ing a photovoltaic(PV)generator,fuel cell(FC),and battery system,to provide a continuous energy supply,even when the vehicle is running.The Multi-Directional Power Transfer converter for the battery provides the required energy ad-aptation between the input and output.The FC and PV systems are all connected through a direct current/direct current converter to effectively charge the battery whenever excess energy is present.The new energy management technique called Optimized Ant Colony Algorithm is proposed to dynamically allocate power among the different power sources,improving system efficiency.Unlike traditional methods,the suggested approach actively optimizes energy flow accord-ing to actual demand and availability,minimizing energy losses and enhancing sustainability.The MATLAB/Simulink tool was used to simulate the energetic performance of an electric car utilizing the suggested approach.The performance of this multi-source power system is assessed by contrasting the energy the PV and FC generating devices offer,and the energy generation of each recharge system.Additionally,the battery power comparison validates the cost-effectiveness and sustainability of the proposed model in NEVs.Results designate a significant improvement in energy efficiency and overall NEV environmental sustainability within contemporary transportation networks.
基金supported by the National Natural Science Foundation of China(71901212)the Science and Technology Innovation Program of Hunan Province(2020RC4046).
文摘The belief rule-based(BRB)system has been popular in complexity system modeling due to its good interpretability.However,the current mainstream optimization methods of the BRB systems only focus on modeling accuracy but ignore the interpretability.The single-objective optimization strategy has been applied in the interpretability-accuracy trade-off by inte-grating accuracy and interpretability into an optimization objec-tive.But the integration has a greater impact on optimization results with strong subjectivity.Thus,a multi-objective optimiza-tion framework in the modeling of BRB systems with inter-pretability-accuracy trade-off is proposed in this paper.Firstly,complexity and accuracy are taken as two independent opti-mization goals,and uniformity as a constraint to give the mathe-matical description.Secondly,a classical multi-objective opti-mization algorithm,nondominated sorting genetic algorithm II(NSGA-II),is utilized as an optimization tool to give a set of BRB systems with different accuracy and complexity.Finally,a pipeline leakage detection case is studied to verify the feasibility and effectiveness of the developed multi-objective optimization.The comparison illustrates that the proposed multi-objective optimization framework can effectively avoid the subjectivity of single-objective optimization,and has capability of joint optimiz-ing the structure and parameters of BRB systems with inter-pretability-accuracy trade-off.
基金Project (No. 2006AA10A304) supported by the Hi-Tech Researchand Development Program (863) of China
文摘In a tractor automatic navigation system, path planning plays a significant role in improving operation efficiency. This study aims to create a suboptimal reference course for headland turning of a robot tractor and design a path-tracking controller to guide the robot tractor along the reference course. A time-minimum suboptimal control method was used to generate the reference turning course based on the mechanical parameters of the test tractor. A path-tracking controller consisting of both feedforward and feedback component elements was also proposed. The feedforward component was directly determined by the desired steering angle of the current navigation point on the reference course, whereas the feedback component was derived from the designed optimal controller. Computer simulation and field tests were performed to validate the path-tracking performance. Field test results indicated that the robot tractor followed the reference courses precisely on flat meadow, with average and standard lateral devia- tions being 0.031 m and 0.086 m, respectively. However, the tracking error increased while operating on sloping meadow due to the employed vehicle kinematic model.
基金Sponsored by National Natural Science Foundation of China(51074051)The Fundamental Research Funds for the CentralUniversities of China(N110307001)
文摘Abstract： In the hot strip rolling control system, the temperature distribution and deformation resistance are the main parameters affecting prediction of rolling force. In order to improve the model prediction precision, an optimiza- tion algorithm based on objective function was put forward, in which the penalty function index was adopted. During the adaptation process, the temperature distribution and deformation resistance were taken as the optimized parame ters, and the Nelder-Mead simplex algorithm was used to search the optimal solution of the objective function. Fur thermore, the temperature adaptation and force adaptation were solved simultaneously. Application results show that the method can improve the accuracy of the rolling force model obviously, and it can meet the demand of the indus trial production and has a good application prospect.
基金the National Natural Science Foundation of China(61771119,61901100 and 62075037)the Natural Science Foundation of Hebei Province(H2019501010,F2019501132,E2020501029 and F2020501040).
文摘The size and shape of the foveal avascular zone(FAZ)have a strong positive correlation with several vision-threatening ret inovascular diseases.The identification,segmentation and analysis of FAZ are of great significance to clinical diagnosis and treatment.We presented an adaptive watershed algorithm to automatically extract F AZ from retinal optical coherence tomography angiography(OCTA)images.For the traditional watershed algorithm,"over-segmentation"is the most common problem.FAZ is often incorrectly divided into multiple regions by redundant"dams".This paper analyzed the relationship between the"dams"length and the maximum inscribed circle radius of FAZ,and proposed an adaptive watershed algorithm to solve the problem of"over-segmentation".Here,132 healthy retinal images and 50 diabetic retinopathy(DR)images were used to verify the accuracy and stability of the algorithm.Three ophthal-mologists were invited to make quan titative and qualitative evaluations on the segmentation results of this algorithm.The quantitative evaluation results show that the correlation coffi-cients between the automatic and manual segmentation results are 0.945(in healthy subjects)and 0.927(in DR patients),respectively.For qualitative evaluation,the percentages of"perfect segmentation"(score of 3)and"good segmentation"(score of 2)are 99.4%(in healthy subjects)and 98.7%(in DR patients),respectively.This work promotes the application of watershed algorithm in FAZ segmentation,making it a useful tool for analyzing and diagnosing eye diseases.
基金supported by the National Basic Research Program of China (No.2013CB733002)
文摘The random variables are always truncated in aerospace engineering and the truncated distribution is more feasible and effective for the random variables due to the limited samples available.For high-reliability aerospace mechanism with truncated random variables, a method based on artificial bee colony（ABC） algorithm and line sampling（LS） is proposed.The artificial bee colony-based line sampling（ABCLS） method presents a multi-constrained optimization model to solve the potential non-convergence problem when calculating design point（is also as most probable point, MPP） of performance function with truncated variables; by implementing ABC algorithm to search for MPP in the standard normal space, the optimization efficiency and global searching ability are increased with this method dramatically.When calculating the reliability of aerospace mechanism with too small failure probability, the Monte Carlo simulation method needs too large sample size.The ABCLS method could overcome this drawback.For reliability problems with implicit functions, this paper combines the ABCLS with Kriging response surface method,therefore could alleviate computational burden of calculating the reliability of complex aerospace mechanism.A numerical example and an engineering example are carried out to verify this method and prove the applicability.
基金Supported by the National Natural Science Foundation of China(No.51565036)
文摘As a new variant of vehicle routing problem( VRP),a finished vehicle routing problem with time windows in finished vehicle logistics( FVRPTW) is modeled and solved. An optimization model for FVRPTW is presented with the objective of scheduling multiple transport routes considering loading constraints along with time penalty function to minimize the total cost. Then a genetic algorithm( GA) is developed. The specific encoding and genetic operators for FVRPTW are devised.Especially,in order to accelerate its convergence,an improved termination condition is given. Finally,a case study is used to evaluate the effectiveness of the proposed algorithm and a series of experiments are conducted over a set of finished vehicle routing problems. The results demonstrate that the proposed approach has superior performance and satisfies users in practice. Contributions of the study are the modeling and solving of a complex FVRPTW in logistics industry.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.10704079 and 10976030)
文摘We suggest a design method of graded-refractive-index （GRIN） antireflection （AR） coating for s-polarized or p- polarized light at off-normal incidence. The spectrum characteristic of the designed antireflection coating with a quintic effective refractive-index profile for a given state of polarization has been discussed. In addition, the genetic algorithm was used to optimize the refractive index profile of the GRIN antireflection for reducing the mean reflectance of s- and p-polarizations. The average reflectance loss was reduced to only 0.04% by applying optimized GRIN AR coatings onto BK7 glass over the wavelength range from 400 to 800 nm at the incident angle of θo = 70°.
基金the Scientific Research Project of Shanghai Science and Technology Commission(No.18DZ1205603)the Science Research Plan of Shanghai Municipal Science and Technology Committee(No.20DZ1201300)the National Key Research and Development Program of China(No.2017YFC0806100)。
文摘With the increasing demands of health care,the design of hospital buildings has become increasingly demanding and complicated.However,the traditional layout design method for hospital is labor intensive,time consuming and prone to errors.With the development of artificial intelligence(AI),the intelligent design method has become possible and is considered to be suitable for the layout design of hospital buildings.Two intelli-gent design processes based on healthcare systematic layout planning(HSLP)and generative adversarial network(GAN)are proposed in this paper,which aim to solve the generation problem of the plane functional layout of the operating departments(ODs)of general hospitals.The first design method that is more like a mathemati-cal model with traditional optimization algorithm concerns the following two steps:developing the HSLP model based on the conventional systematic layout planning(SLP)theory,identifying the relationship and flows amongst various departments/units,and arriving at the preliminary plane layout design;establishing mathematical model to optimize the building layout by using the genetic algorithm(GA)to obtain the optimized scheme.The specific process of the second intelligent design based on more than 100 sets of collected OD drawings includes:labelling the corresponding functional layouts of each OD plan;building image-to-image translation with conditional ad-versarial network(pix2pix)for training OD plane layouts,which is one of the most representative GAN models.Finally,the functions and features of the results generated by the two methods are analyzed and compared from an architectural and algorithmic perspective.Comparison of the two design methods shows that the HSLP and GAN models can autonomously generate new OD plane functional layouts.The HSLP layouts have clear functional area adjacencies and optimization goals,but the layouts are relatively rigid and not specific enough.The GAN outputs are the most innovative layouts with strong applicability,but the dataset has strict constraints.The goal of this paper is to help release the heavy load of architects in the early design stage and present the effectiveness of these intelligent design methods in the field of medical architecture.
基金supported by the National Natural Science Foundation of China(61071104)the National High Technology Research and Development Program(2008AA12Z305)
文摘The spectrum sharing problem between primary and cognitive users is mainly investigated. Since the interference for primary users and the total power for cognitive users are constrained, based on the well-known water-filling theorem, a novel one-user water-filling algorithm is proposed, and then the corresponding simulation results are given to analyze the feasibility and validity. After that this algorithm is used to solve the communication utility optimization problem subject to the power constraints in cognitive radio network. First, through the gain to noise ratio for cognitive users, a subcarrier and power allocation algorithm based on the optimal frequency partition is proposed for two cognitive users. Then the spectrum sharing algorithm is extended to multiuser conditions such that the greedy and parallel algorithms are proposed for spectrum sharing. Theory and simulation analysis show that the subcarrier and power allocation algorithms can not only protect the primary users but also effectively solve the spectrum and power allocation problem for cognitive users.
文摘Experiment statistical method and genetic algorithms based optimization method are used to obtain the optimum differential gear ratio for heavy truck that provides best fuel consumption when changing the working condition that affects its torque and speed range. The aim of the study is to obtain the optimum differential gear ratio with fast and accurate optimization calculation without affecting drivability characteristics of the vehicle according to certain driving cycles that represent the new working conditions of the truck. The study is carried on a mining dump truck YT3621 with 9 for- ward shift manual transmission. Two loading conditions, no load and 40 t, and four on road real driving cycles have been discussed. The truck powertrain is modeled using GT-drive, and DOE -post processing tool of the GT-suite is used for DOE analysis and genetic algorithm optimization.
基金supported by“11th Five-year Projects”pre-research projects fund of the National Arming Department
文摘A Genetic Algorithm-Ant Colony Algorithm(GA-ACA),which can be used to optimize multi-Unit Under Test(UUT)parallel test tasks sequences and resources configuration quickly and accurately,is proposed in the paper.With the establishment of the mathematic model of multi-UUT parallel test tasks and resources,the condition of multi-UUT resources mergence is analyzed to obtain minimum resource requirement under minimum test time.The definition of cost efficiency is put forward,followed by the design of gene coding and path selection project,which can satisfy multi-UUT parallel test tasks scheduling.At the threshold of the algorithm,GA is adopted to provide initial pheromone for ACA,and then dual-convergence pheromone feedback mode is applied in ACA to avoid local optimization and parameters dependence.The practical application proves that the algorithm has a remarkable effect on solving the problems of multi-UUT parallel test tasks scheduling and resources configuration.
基金supported by the National Natural Science Foundation of China(72171116,71671090)the Fundamental Research Funds for the Central Universities(NP2020022)+1 种基金the Key Research Projects of Humanities and Social Sciences in Anhui Education Department(SK2021A1018)Qinglan Project for Excellent Youth or Middlea ged Academic Leaders in Jiangsu Province,China.
文摘GM(1,1)models have been widely used in various fields due to their high performance in time series prediction.However,some hypotheses of the existing GM(1,1)model family may reduce their prediction performance in some cases.To solve this problem,this paper proposes a self-adaptive GM(1,1)model,termed as SAGM(1,1)model,which aims to solve the defects of the existing GM(1,1)model family by deleting their modeling hypothesis.Moreover,a novel multi-parameter simultaneous optimization scheme based on firefly algorithm is proposed,the proposed multi-parameter optimization scheme adopts machine learning ideas,takes all adjustable parameters of SAGM(1,1)model as input variables,and trains it with firefly algorithm.And Sobol’sensitivity indices are applied to study global sensitivity of SAGM(1,1)model parameters,which provides an important reference for model parameter calibration.Finally,forecasting capability of SAGM(1,1)model is illustrated by Anhui electricity consumption dataset.Results show that prediction accuracy of SAGM(1,1)model is significantly better than other models,and it is shown that the proposed approach enhances the prediction performance of GM(1,1)model significantly.
基金supported by the Key Technology Research and Sample-Chip Manufacture on Resistance to Physical Attacks at Circuit Level(546816170002)
文摘Public key cryptographic （PKC） algorithms, such as the RSA, elliptic curve digital signature algorithm （ECDSA） etc., are widely used in the secure communication sys- tems, such as OpenSSL, and a variety of in- formation security systems. If designer do not securely implement them, the secret key will be easily extracted by side-channel attacks （SCAs） or combinational SCA thus mitigat- ing the security of the entire communication system. Previous countermeasures of PKC im- plementations focused on the core part of the algorithms and ignored the modular inversion which is widely used in various PKC schemes. Many researchers believe that instead of straightforward implementation, constant time modular inversion （CTMI） is enough to resist the attack of simple power analysis combined with lattice analysis. However, we find that the CTMI security can be reduced to a hidden t-bit multiplier problem. Based on this feature, we firstly obtain Hamming weight of interme- diate data through side-channel leakage. Then, we propose a heuristic algorithm to solve the problem by revealing the secret （partial and full） base of CTMI. Comparing previous nec-essary input message for masking filtering, our procedure need not any information about the secret base of the inversion. To our knowl- edge, this is the first time for evaluating the practical security of CTM! and experimental results show the fact that CTMI is not enough for high-level secure communication systems.
基金supported by the National Natural Science Foundation of China (50421703)the National Key Laboratory of Electrical Engineering of Naval Engineering University
文摘Currently, the article analyzes the CAN bus＇s rule of priority＇s arbitration bit by bit without destroy. It elicits the conclusion that if static priority based on the affirmatory system model is used, the lower priority＇s messages will be delayed considerably more, even some data will be lost when the bus＇s bandwidth is widely used. The scheduling cannot be modified neither during the system when static priority is used. The dynamic priority promoting method and the math model of SQSA and SQMA are presented; it analyzes the model＇s rate of taking in and sending out in large quantities, the largest delay, the problems and solutions when using SQMA. In the end, it is confirmed that the method of improving dynamic priority has good performances on the network rate of taking in and sending out in large quantities, the average delay, and the rate of network usage by emulational experiments.
文摘Since the 5-steps rule was proposed in 2011, it has been widely used in many areas of molecular biology, both theoretical and experimental. It can be even used to deal with the commercial problems and bank systems, as well as material science systems. Just like the machine-learning algorithms, it is the jade for nearly all the statistical systems.
