Realistic human reconstruction embraces an extensive range of applications as depth sensors advance.However,current stateof-the-art methods with RGB-D input still suffer from artefacts,such as noisy surfaces,non-human...Realistic human reconstruction embraces an extensive range of applications as depth sensors advance.However,current stateof-the-art methods with RGB-D input still suffer from artefacts,such as noisy surfaces,non-human shapes,and depth ambiguity,especially for the invisible parts.The authors observe the main issue is the lack of geometric semantics without using depth input priors fully.This paper focuses on improving the representation ability of implicit function,exploring an effective method to utilise depth-related semantics effectively and efficiently.The proposed geometry-enhanced implicit function enhances the geometric semantics with the extra voxel-aligned features from point clouds,promoting the completion of missing parts for unseen regions while preserving the local details on the input.For incorporating multi-scale pixel-aligned and voxelaligned features,the authors use the Squeeze-and-Excitation attention to capture and fully use channel interdependencies.For the multi-view reconstruction,the proposed depth-enhanced attention explicitly excites the network to“sense”the geometric structure for a more reasonable feature aggregation.Experiments and results show that our method outperforms current RGB and depth-based SOTA methods on the challenging data from Twindom and Thuman3.0,and achieves a detailed and completed human reconstruction,balancing performance and efficiency well.展开更多
Nonlinear variations in the coordinate time series of global navigation satellite system(GNSS) reference stations are strongly correlated with surface displacements caused by environmental loading effects,including at...Nonlinear variations in the coordinate time series of global navigation satellite system(GNSS) reference stations are strongly correlated with surface displacements caused by environmental loading effects,including atmospheric, hydrological, and nontidal ocean loading. Continuous improvements in the accuracy of surface mass loading products, performance of Earth models, and precise data-processing technologies have significantly advanced research on the effects of environmental loading on nonlinear variations in GNSS coordinate time series. However, owing to theoretical limitations, the lack of high spatiotemporal resolution surface mass observations, and the coupling of GNSS technology-related systematic errors, environmental loading and nonlinear GNSS reference station displacements remain inconsistent. The applicability and capability of these loading products across different regions also require further evaluation. This paper outlines methods for modeling environmental loading, surface mass loading products, and service organizations. In addition, it summarizes recent advances in applying environmental loading to address nonlinear variations in global and regional GNSS coordinate time series. Moreover, the scientific questions of existing studies are summarized, and insights into future research directions are provided. The complex nonlinear motion of reference stations is a major factor limiting the accuracy of the current terrestrial reference frame. Further refining the environmental load modeling method, establishing a surface mass distribution model with high spatiotemporal resolution and reliability, exploring other environmental load factors such as ice sheet and artificial mass-change effects, and developing an optimal data-processing model and strategy for reprocessing global reference station data consistently could contribute to the development of a millimeter-level nonlinear motion model for GNSS reference stations with actual physical significance and provide theoretical support for establishing a terrestrial reference frame with 1 mm accuracy by 2050.展开更多
The accuracy of numerical computation heavily relies on appropriate meshing,whichserves as the foundation for numerical computation.Although adaptive refinement methods areavailable,an adaptive numerical solution is l...The accuracy of numerical computation heavily relies on appropriate meshing,whichserves as the foundation for numerical computation.Although adaptive refinement methods areavailable,an adaptive numerical solution is likely to be ineffective if it originates from a poorly ini-tial mesh.Therefore,it is crucial to generate meshes that accurately capture the geometric features.As an indispensable input in meshing methods,the Mesh Size Function(MSF)determines the qual-ity of the generated mesh.However,the current generation of MSF involves human participation tospecify numerous parameters,leading to difficulties in practical usage.Considering the capacity ofmachine learning to reveal the latent relationships within data,this paper proposes a novel machinelearning method,Implicit Geometry Neural Network(IGNN),for automatic prediction of appro-priate MSFs based on the existing mesh data,enabling the generation of unstructured meshes thatalign precisely with geometric features.IGNN employs the generative adversarial theory to learnthe mapping between the implicit representation of the geometry(Signed Distance Function,SDF)and the corresponding MSF.Experimental results show that the proposed method is capableof automatically generating appropriate meshes and achieving comparable meshing results com-pared to traditional methods.This paper demonstrates the possibility of significantly decreasingthe workload of mesh generation using machine learning techniques,and it is expected to increasethe automation level of mesh generation.展开更多
Soil carbon stock research has gained prominence in environmental studies amidst climate change concerns,especially given that soil is one of the largest terrestrial carbon reserves.Accurate predictions necessitate co...Soil carbon stock research has gained prominence in environmental studies amidst climate change concerns,especially given that soil is one of the largest terrestrial carbon reserves.Accurate predictions necessitate comprehensive soil profile measurements,which are resource-intensive to obtain.To address this,depth functions are employed to derive continuous estimates,aligning with standardized depths.However,global datasets employing depth functions in raster format have not been widely utilized,which could lower financial costs and improve accuracy in data-scarce regions.Furthermore,research into aggregating depth functions for realistic carbon stock estimations remains limited,offering opportunities to streamline cost and time.The aim of this study was to apply equal-area splines to estimate soil carbon stocks,utilizing SoilGrids and iSDAsoil datasets in a 317-km^(2) Quaternary catchment(30°48′E,29°18′S)in KwaZulu-Natal,South Africa.Both datasets were resampled to a 250-m resolution,and the splines were interpolated to a depth of 50 cm per pixel.Various aggregation methods were employed in calculation,including the cumulative sum(definite integral),discrete sum(sum of 1-cm spline predictions),and the mean carbon stock(mean to 50 cm).Quantitative evaluation was performed with 310 external soil samples.SoilGrids showed higher predictions(100–546 kg m^(-2))than iSDAsoil(66.9–225 kg m^(-2))for the cumulative sum.The discrete sum also exhibited higher prediction values for SoilGrids(293–789 kg m^(-2))compared to iSDAsoil(228–557 kg m^(-2)).SoilGrids aggregated with the discrete sum closely matched previous studies,estimating total carbon stock for the catchment at 7126 t,albeit with spatial inconsistencies.However,when evaluating with an external dataset,the results were not satisfactory for any method according to Lin's concordance correlation coefficient(CCC,correlation of a 1:1 line),with all models obtaining a CCC below 0.01.Similarly,all models had a root mean squared error larger than 59 kg m^(-2).It was concluded that SoilGrids and iSDAsoil were spatially inaccurate in the catchment but can still provide information about the total carbon stock.This method could be improved by obtaining more soil samples for the datasets,incorporating local data into the spline,making the method more computationally efficient,and accounting for discrete horizon boundaries.展开更多
Establishing the structure-property relationship in amorphous materials has been a long-term grand challenge due to the lack of a unified description of the degree of disorder.In this work,we develop SPRamNet,a neural...Establishing the structure-property relationship in amorphous materials has been a long-term grand challenge due to the lack of a unified description of the degree of disorder.In this work,we develop SPRamNet,a neural network based machine-learning pipeline that effectively predicts structure-property relationship of amorphous material via global descriptors.Applying SPRamNet on the recently discovered amorphous monolayer carbon,we successfully predict the thermal and electronic properties.More importantly,we reveal that a short range of pair correlation function can readily encode sufficiently rich information of the structure of amorphous material.Utilizing powerful machine learning architectures,the encoded information can be decoded to reconstruct macroscopic properties involving many-body and long-range interactions.Establishing this hidden relationship offers a unified description of the degree of disorder and eliminates the heavy burden of measuring atomic structure,opening a new avenue in studying amorphous materials.展开更多
The filled function method is an approach for finding a global minimum of multi-dimensional functions. With more and more relevant research, it becomes a promising way used in unconstrained global optimization. Some f...The filled function method is an approach for finding a global minimum of multi-dimensional functions. With more and more relevant research, it becomes a promising way used in unconstrained global optimization. Some filled functions with one or two parameters have already been suggested. However, there is no certain criterion to choose a parameter appropriately. In this paper, a parameter-free filled function was proposed. The definition of the original filled function and assumptions of the objective function given by Ge were improved according to the presented parameter-free filled function. The algorithm and numerical results of test functions were reported. Conclusions were drawn in the end. Key words global optimization - filled function method - local minimizer MSC 2000 90C30展开更多
In this paper, a new filled function with only one parameter is proposed. The main advantages of the new filled function are that it not only can be analyzed easily, but also can be approximated uniformly by a continu...In this paper, a new filled function with only one parameter is proposed. The main advantages of the new filled function are that it not only can be analyzed easily, but also can be approximated uniformly by a continuously differentiable function. Thus, a minimizer of the proposed filled function can be obtained easily by using a local optimization algorithm. The obtained minimizer is taken as the initial point to minimize the objective function and a better minimizer will be found. By repeating the above processes, we will find a global minimizer at last. The results of numerical experiments show that the new proposed filled function method is effective.展开更多
Quantification of right ventricular(RV)volume and function remains a challenge because of RV complex geometry by conventional echocardiography.The purpose of this study was to assess RV global longitudinal function in...Quantification of right ventricular(RV)volume and function remains a challenge because of RV complex geometry by conventional echocardiography.The purpose of this study was to assess RV global longitudinal function in patients with tetralogy of Fallot(TOF)by 2-dimensional ultrasound speckle tracking imaging(STI).Thirty-eight patients with TOF were enrolled in this study and divided into child group(n=25)and adult group(n=13)according to age.Thirty-eight age-and sex-matched normal subjects were selected as c...展开更多
In this paper, we considered a homogeneous reaction-diffusion predator-prey system with Holling type II functional response subject to Neumann boundary conditions. Some new sufficient conditions were analytically esta...In this paper, we considered a homogeneous reaction-diffusion predator-prey system with Holling type II functional response subject to Neumann boundary conditions. Some new sufficient conditions were analytically established to ensure that this system has globally asymptotically stable equilibria and Hopf bifurcation surrounding interior equilibrium. In the analysis of Hopf bifurcation, based on the phenomenon of Turing instability and well-done conditions, the system undergoes a Hopf bifurcation and an example incorporating with numerical simulations to support the existence of Hopf bifurcation is presented. We also derived a useful algorithm for determining direction of Hopf bifurcation and stability of bifurcating periodic solutions correspond to j ≠0 and j = 0, respectively. Finally, all these theoretical results are expected to be useful in the future study of dynamical complexity of ecological environment.展开更多
This paper deals with the questio n of global stability of the positive locally asymptotically stable equilibrium in a class of predator\|prey system of Gause\|typ e with Holling Ⅲ functional response. The Dulac'...This paper deals with the questio n of global stability of the positive locally asymptotically stable equilibrium in a class of predator\|prey system of Gause\|typ e with Holling Ⅲ functional response. The Dulac's criterion is applied and lia punov functions are constructed to establish the global stability.展开更多
To solve the global optimization problems which have several local minimizers,a new F-C function is proposes by combining a lled function and a cross function.The properties of the F-C function are discussed and the c...To solve the global optimization problems which have several local minimizers,a new F-C function is proposes by combining a lled function and a cross function.The properties of the F-C function are discussed and the corresponding algorithm is given in this paper.F-C function has the same local minimizers with the objective function.Therefore,the F-C function method only needs to minimize the objective function once in the rst iteration.Numerical experiments are performed and the results show that the proposed method is very effective.展开更多
A class of discontinuous penalty functions was proposed to solve constrained minimization problems with the integral approach to global optimization, m-mean value and v-variance optimality conditions of a constrained ...A class of discontinuous penalty functions was proposed to solve constrained minimization problems with the integral approach to global optimization, m-mean value and v-variance optimality conditions of a constrained and penalized minimization problem were investigated. A nonsequential algorithm was proposed. Numerical examples were given to illustrate the effectiveness of the algorithm.展开更多
A filled function with adjustable parameters is suggested in this paper for finding a global minimum point of a general class of nonlinear programming problems with a bounded and closed domain. This function has two a...A filled function with adjustable parameters is suggested in this paper for finding a global minimum point of a general class of nonlinear programming problems with a bounded and closed domain. This function has two adjustable parameters. We will discuss the properties of the proposed filled function. Conditions on this function and on the values of parameters are given so that the constructed function has the desired properties of traditional filled function.展开更多
In this paper, auxiliary function method for global optimization with box constraints is considered. First, a new non-parameter filled function which has the same local minimizers of the objective function is proposed...In this paper, auxiliary function method for global optimization with box constraints is considered. First, a new non-parameter filled function which has the same local minimizers of the objective function is proposed. By the character that having same local minimizers, and these minimizers are all better than the current minimizer of the objective function, it does not need to minimize the objective function except for thefirst iteration in the filled function method. It changes the frame of conventional filled function methods that objective function and filled function are minimized alternately,and can effectively reduce the iterations of the algorithm and accelerate the speed of global optimization. And then the theoretical properties of the filled function are discussed and the corresponding algorithm is established. Finally, numerical experiments are made and comparisons on several test problems are shown which exhibit the feasibility and effectiveness of the algorithm.展开更多
In the paper,to solve the global optimization problems,we propose a novel parameter-free filled function.Based on the non-parameter filled function,a new filled function algorithm is designed.In the algorithm,the sele...In the paper,to solve the global optimization problems,we propose a novel parameter-free filled function.Based on the non-parameter filled function,a new filled function algorithm is designed.In the algorithm,the selection and adjustment of parameters can be ignored by the characteristic that the filled function is parameter-free.In addition,in the region lower than the current local minimizer of the objective function,the filled function is continuously differentiable which enables any gradient descent method to be used as a local search method in the algorithm.Through numerical experiments by solving two test problems,the effectiveness of the algorithm is verified.展开更多
In this paper,we present an approach for smooth surface reconstructions interpolating triangular meshes with ar- bitrary topology and geometry.The approach is based on the well-known radial basis functions (RBFs) and ...In this paper,we present an approach for smooth surface reconstructions interpolating triangular meshes with ar- bitrary topology and geometry.The approach is based on the well-known radial basis functions (RBFs) and the constructed surfaces are generalized thin-plate spline surfaces.Our algorithm first defines a pair of offset points for each vertex of a given mesh to en- hance the controUability of local geometry and to assure stability of the construction.A linear system is then solved by LU decomposi- tion and the implicit governing equation of interpolating surface is obtained.The constructed surfaces finally are visualized by a Marching Cubes based polygonizer.The approach provides a robust and efficient solution for smooth surface reconstruction from various 3 D meshes.展开更多
In order to measure the correlation propeties of two Boolean functions,the global avalanche characteristics of Boolean functions constructed by concatenation are discussed,i.e.,f_1‖f_2and f_1‖f_2‖f_3‖f_4.Firstly,f...In order to measure the correlation propeties of two Boolean functions,the global avalanche characteristics of Boolean functions constructed by concatenation are discussed,i.e.,f_1‖f_2and f_1‖f_2‖f_3‖f_4.Firstly,for the function f = f_1‖f_2,the cross-correlation function of f_1,f_2 in the special condition are studied.In this case,f,f_1,f_2 must be in desired form.By computing their sum-of-squares indicators,the crosscorrelation function between f_1,f_2 is obtained.Secondly,for the function g = f_1‖f_2‖f_3‖f_4,by analyzing the relation among their auto-correlation functions,their sum-of-squares indicators are investigated.Based on them,the sum-of-squares indicators of functions obtained by Canteaut et al.are investigated.The results show that the correlation property of g is good when the correlation properties of Boolean functions f_1,f_2,f_3,f_4 are good.展开更多
Global minimization algorithm is indispensable for solving protein folding problems based on thermodynamic hypothesis. A contact difference （CD） based on pseudo potential function, for simulating empirical contact p...Global minimization algorithm is indispensable for solving protein folding problems based on thermodynamic hypothesis. A contact difference （CD） based on pseudo potential function, for simulating empirical contact potential functions and testing global minimization algorithm was proposed. The present article describes a conformational sampiing and global minimization algorithm, which is called WL, based on Monte Carlo simulation and simulated annealing. It can be used to locate CD＇s globe minimum and refold extended protein structures, as small as 0. 03 nm, from the native structures, back to ones with root mean square distance（RMSD）. These results demonstrate that the global minimization problems for empirical contact potential functions may be solvable.展开更多
Global minimization algorithm is indispensable to solving the protein folding problem based upon thermodynamic hypothesis. Here we propose a pseudo potential function, contact difference(CD), for simulating empirical ...Global minimization algorithm is indispensable to solving the protein folding problem based upon thermodynamic hypothesis. Here we propose a pseudo potential function, contact difference(CD), for simulating empirical contact potential functions and testing global minimization algorithm. The present paper covers conformational sampling and global minimization algorithm called BML03, based upon Monte Carlo and simulated annealing, which is able to locate CD′s global minimum and refold extended protein structures into ones with root mean square distance(RMSD) as small as 0.03 nm from the native structures. For empirical contact potential functions, these results demonstrate that their global minimization problems may be solvable.展开更多
The stability of a periodic oscillation and the global exponential class of recurrent neural networks with non-monotone activation functions and time-varying delays are analyzed. For two sets of activation functions, ...The stability of a periodic oscillation and the global exponential class of recurrent neural networks with non-monotone activation functions and time-varying delays are analyzed. For two sets of activation functions, some algebraic criteria for ascertaining global exponential periodicity and global exponential stability of the class of recurrent neural networks are derived by using the comparison principle and the theory of monotone operator. These conditions are easy to check in terms of system parameters. In addition, we provide a new and efficacious method for the qualitative analysis of various neural networks.展开更多
基金supported by the National Key R&D Programme of China(2022YFF0902200).
文摘Realistic human reconstruction embraces an extensive range of applications as depth sensors advance.However,current stateof-the-art methods with RGB-D input still suffer from artefacts,such as noisy surfaces,non-human shapes,and depth ambiguity,especially for the invisible parts.The authors observe the main issue is the lack of geometric semantics without using depth input priors fully.This paper focuses on improving the representation ability of implicit function,exploring an effective method to utilise depth-related semantics effectively and efficiently.The proposed geometry-enhanced implicit function enhances the geometric semantics with the extra voxel-aligned features from point clouds,promoting the completion of missing parts for unseen regions while preserving the local details on the input.For incorporating multi-scale pixel-aligned and voxelaligned features,the authors use the Squeeze-and-Excitation attention to capture and fully use channel interdependencies.For the multi-view reconstruction,the proposed depth-enhanced attention explicitly excites the network to“sense”the geometric structure for a more reasonable feature aggregation.Experiments and results show that our method outperforms current RGB and depth-based SOTA methods on the challenging data from Twindom and Thuman3.0,and achieves a detailed and completed human reconstruction,balancing performance and efficiency well.
基金supported by the Basic Science Center Project of the National Natural Science Foundation of China(42388102)the National Natural Science Foundation of China(42174030)+2 种基金the Special Fund of Hubei Luojia Laboratory(220100020)the Major Science and Technology Program for Hubei Province(2022AAA002)the Fundamental Research Funds for the Central Universities of China(2042022dx0001 and 2042023kfyq01)。
文摘Nonlinear variations in the coordinate time series of global navigation satellite system(GNSS) reference stations are strongly correlated with surface displacements caused by environmental loading effects,including atmospheric, hydrological, and nontidal ocean loading. Continuous improvements in the accuracy of surface mass loading products, performance of Earth models, and precise data-processing technologies have significantly advanced research on the effects of environmental loading on nonlinear variations in GNSS coordinate time series. However, owing to theoretical limitations, the lack of high spatiotemporal resolution surface mass observations, and the coupling of GNSS technology-related systematic errors, environmental loading and nonlinear GNSS reference station displacements remain inconsistent. The applicability and capability of these loading products across different regions also require further evaluation. This paper outlines methods for modeling environmental loading, surface mass loading products, and service organizations. In addition, it summarizes recent advances in applying environmental loading to address nonlinear variations in global and regional GNSS coordinate time series. Moreover, the scientific questions of existing studies are summarized, and insights into future research directions are provided. The complex nonlinear motion of reference stations is a major factor limiting the accuracy of the current terrestrial reference frame. Further refining the environmental load modeling method, establishing a surface mass distribution model with high spatiotemporal resolution and reliability, exploring other environmental load factors such as ice sheet and artificial mass-change effects, and developing an optimal data-processing model and strategy for reprocessing global reference station data consistently could contribute to the development of a millimeter-level nonlinear motion model for GNSS reference stations with actual physical significance and provide theoretical support for establishing a terrestrial reference frame with 1 mm accuracy by 2050.
基金co-supported by the Aeronautical Science Foundation of China(Nos.2018ZA52002 and 2019ZA052011)。
文摘The accuracy of numerical computation heavily relies on appropriate meshing,whichserves as the foundation for numerical computation.Although adaptive refinement methods areavailable,an adaptive numerical solution is likely to be ineffective if it originates from a poorly ini-tial mesh.Therefore,it is crucial to generate meshes that accurately capture the geometric features.As an indispensable input in meshing methods,the Mesh Size Function(MSF)determines the qual-ity of the generated mesh.However,the current generation of MSF involves human participation tospecify numerous parameters,leading to difficulties in practical usage.Considering the capacity ofmachine learning to reveal the latent relationships within data,this paper proposes a novel machinelearning method,Implicit Geometry Neural Network(IGNN),for automatic prediction of appro-priate MSFs based on the existing mesh data,enabling the generation of unstructured meshes thatalign precisely with geometric features.IGNN employs the generative adversarial theory to learnthe mapping between the implicit representation of the geometry(Signed Distance Function,SDF)and the corresponding MSF.Experimental results show that the proposed method is capableof automatically generating appropriate meshes and achieving comparable meshing results com-pared to traditional methods.This paper demonstrates the possibility of significantly decreasingthe workload of mesh generation using machine learning techniques,and it is expected to increasethe automation level of mesh generation.
文摘Soil carbon stock research has gained prominence in environmental studies amidst climate change concerns,especially given that soil is one of the largest terrestrial carbon reserves.Accurate predictions necessitate comprehensive soil profile measurements,which are resource-intensive to obtain.To address this,depth functions are employed to derive continuous estimates,aligning with standardized depths.However,global datasets employing depth functions in raster format have not been widely utilized,which could lower financial costs and improve accuracy in data-scarce regions.Furthermore,research into aggregating depth functions for realistic carbon stock estimations remains limited,offering opportunities to streamline cost and time.The aim of this study was to apply equal-area splines to estimate soil carbon stocks,utilizing SoilGrids and iSDAsoil datasets in a 317-km^(2) Quaternary catchment(30°48′E,29°18′S)in KwaZulu-Natal,South Africa.Both datasets were resampled to a 250-m resolution,and the splines were interpolated to a depth of 50 cm per pixel.Various aggregation methods were employed in calculation,including the cumulative sum(definite integral),discrete sum(sum of 1-cm spline predictions),and the mean carbon stock(mean to 50 cm).Quantitative evaluation was performed with 310 external soil samples.SoilGrids showed higher predictions(100–546 kg m^(-2))than iSDAsoil(66.9–225 kg m^(-2))for the cumulative sum.The discrete sum also exhibited higher prediction values for SoilGrids(293–789 kg m^(-2))compared to iSDAsoil(228–557 kg m^(-2)).SoilGrids aggregated with the discrete sum closely matched previous studies,estimating total carbon stock for the catchment at 7126 t,albeit with spatial inconsistencies.However,when evaluating with an external dataset,the results were not satisfactory for any method according to Lin's concordance correlation coefficient(CCC,correlation of a 1:1 line),with all models obtaining a CCC below 0.01.Similarly,all models had a root mean squared error larger than 59 kg m^(-2).It was concluded that SoilGrids and iSDAsoil were spatially inaccurate in the catchment but can still provide information about the total carbon stock.This method could be improved by obtaining more soil samples for the datasets,incorporating local data into the spline,making the method more computationally efficient,and accounting for discrete horizon boundaries.
基金supported by the National Key R&D Program of China under Grant No.2021YFA1400500the Strategic Priority Research Program of the Chinese Academy of Sciences under Grant No.XDB33000000+1 种基金the National Natural Science Foundation of China under Grant No.12334003the Beijing Municipal Natural Science Foundation under Grant Nos.JQ22001 and QY23014。
文摘Establishing the structure-property relationship in amorphous materials has been a long-term grand challenge due to the lack of a unified description of the degree of disorder.In this work,we develop SPRamNet,a neural network based machine-learning pipeline that effectively predicts structure-property relationship of amorphous material via global descriptors.Applying SPRamNet on the recently discovered amorphous monolayer carbon,we successfully predict the thermal and electronic properties.More importantly,we reveal that a short range of pair correlation function can readily encode sufficiently rich information of the structure of amorphous material.Utilizing powerful machine learning architectures,the encoded information can be decoded to reconstruct macroscopic properties involving many-body and long-range interactions.Establishing this hidden relationship offers a unified description of the degree of disorder and eliminates the heavy burden of measuring atomic structure,opening a new avenue in studying amorphous materials.
文摘The filled function method is an approach for finding a global minimum of multi-dimensional functions. With more and more relevant research, it becomes a promising way used in unconstrained global optimization. Some filled functions with one or two parameters have already been suggested. However, there is no certain criterion to choose a parameter appropriately. In this paper, a parameter-free filled function was proposed. The definition of the original filled function and assumptions of the objective function given by Ge were improved according to the presented parameter-free filled function. The algorithm and numerical results of test functions were reported. Conclusions were drawn in the end. Key words global optimization - filled function method - local minimizer MSC 2000 90C30
文摘In this paper, a new filled function with only one parameter is proposed. The main advantages of the new filled function are that it not only can be analyzed easily, but also can be approximated uniformly by a continuously differentiable function. Thus, a minimizer of the proposed filled function can be obtained easily by using a local optimization algorithm. The obtained minimizer is taken as the initial point to minimize the objective function and a better minimizer will be found. By repeating the above processes, we will find a global minimizer at last. The results of numerical experiments show that the new proposed filled function method is effective.
文摘Quantification of right ventricular(RV)volume and function remains a challenge because of RV complex geometry by conventional echocardiography.The purpose of this study was to assess RV global longitudinal function in patients with tetralogy of Fallot(TOF)by 2-dimensional ultrasound speckle tracking imaging(STI).Thirty-eight patients with TOF were enrolled in this study and divided into child group(n=25)and adult group(n=13)according to age.Thirty-eight age-and sex-matched normal subjects were selected as c...
文摘In this paper, we considered a homogeneous reaction-diffusion predator-prey system with Holling type II functional response subject to Neumann boundary conditions. Some new sufficient conditions were analytically established to ensure that this system has globally asymptotically stable equilibria and Hopf bifurcation surrounding interior equilibrium. In the analysis of Hopf bifurcation, based on the phenomenon of Turing instability and well-done conditions, the system undergoes a Hopf bifurcation and an example incorporating with numerical simulations to support the existence of Hopf bifurcation is presented. We also derived a useful algorithm for determining direction of Hopf bifurcation and stability of bifurcating periodic solutions correspond to j ≠0 and j = 0, respectively. Finally, all these theoretical results are expected to be useful in the future study of dynamical complexity of ecological environment.
基金Supported by the National Natural Science Foundation of China(195 310 70 )
文摘This paper deals with the questio n of global stability of the positive locally asymptotically stable equilibrium in a class of predator\|prey system of Gause\|typ e with Holling Ⅲ functional response. The Dulac's criterion is applied and lia punov functions are constructed to establish the global stability.
基金Supported by National Natural Science Foundation of China(No.11471102)Basic research projects for key scientific research projects in Henan Province(No.20ZX001)。
文摘To solve the global optimization problems which have several local minimizers,a new F-C function is proposes by combining a lled function and a cross function.The properties of the F-C function are discussed and the corresponding algorithm is given in this paper.F-C function has the same local minimizers with the objective function.Therefore,the F-C function method only needs to minimize the objective function once in the rst iteration.Numerical experiments are performed and the results show that the proposed method is very effective.
文摘A class of discontinuous penalty functions was proposed to solve constrained minimization problems with the integral approach to global optimization, m-mean value and v-variance optimality conditions of a constrained and penalized minimization problem were investigated. A nonsequential algorithm was proposed. Numerical examples were given to illustrate the effectiveness of the algorithm.
基金Supported by the National Science Foundation of China(10171118)Supported by the Science Foundation of University of Science and Technology of Henan(2003ZY06)
文摘A filled function with adjustable parameters is suggested in this paper for finding a global minimum point of a general class of nonlinear programming problems with a bounded and closed domain. This function has two adjustable parameters. We will discuss the properties of the proposed filled function. Conditions on this function and on the values of parameters are given so that the constructed function has the desired properties of traditional filled function.
基金Supported by National Natural Science Foundation of China (Grant No. 11471102, 11701150,12071112)Basic research projects for key scientific research projects in Henan Province (Grant No. 20ZX001)。
文摘In this paper, auxiliary function method for global optimization with box constraints is considered. First, a new non-parameter filled function which has the same local minimizers of the objective function is proposed. By the character that having same local minimizers, and these minimizers are all better than the current minimizer of the objective function, it does not need to minimize the objective function except for thefirst iteration in the filled function method. It changes the frame of conventional filled function methods that objective function and filled function are minimized alternately,and can effectively reduce the iterations of the algorithm and accelerate the speed of global optimization. And then the theoretical properties of the filled function are discussed and the corresponding algorithm is established. Finally, numerical experiments are made and comparisons on several test problems are shown which exhibit the feasibility and effectiveness of the algorithm.
文摘In the paper,to solve the global optimization problems,we propose a novel parameter-free filled function.Based on the non-parameter filled function,a new filled function algorithm is designed.In the algorithm,the selection and adjustment of parameters can be ignored by the characteristic that the filled function is parameter-free.In addition,in the region lower than the current local minimizer of the objective function,the filled function is continuously differentiable which enables any gradient descent method to be used as a local search method in the algorithm.Through numerical experiments by solving two test problems,the effectiveness of the algorithm is verified.
文摘In this paper,we present an approach for smooth surface reconstructions interpolating triangular meshes with ar- bitrary topology and geometry.The approach is based on the well-known radial basis functions (RBFs) and the constructed surfaces are generalized thin-plate spline surfaces.Our algorithm first defines a pair of offset points for each vertex of a given mesh to en- hance the controUability of local geometry and to assure stability of the construction.A linear system is then solved by LU decomposi- tion and the implicit governing equation of interpolating surface is obtained.The constructed surfaces finally are visualized by a Marching Cubes based polygonizer.The approach provides a robust and efficient solution for smooth surface reconstruction from various 3 D meshes.
基金Sponsored by the National Natural Science Foundations of Anhui Higher Education Institutions of China(Grant No.KJ2014A220,KJ2014A231)the Anhui Provincial Natural Science Foundation(Grant No.1608085MF143)the Key Program in the Youth Elite Support Plan in Universities of Anhui Province(Grant No.gxyq ZD2016112)
文摘In order to measure the correlation propeties of two Boolean functions,the global avalanche characteristics of Boolean functions constructed by concatenation are discussed,i.e.,f_1‖f_2and f_1‖f_2‖f_3‖f_4.Firstly,for the function f = f_1‖f_2,the cross-correlation function of f_1,f_2 in the special condition are studied.In this case,f,f_1,f_2 must be in desired form.By computing their sum-of-squares indicators,the crosscorrelation function between f_1,f_2 is obtained.Secondly,for the function g = f_1‖f_2‖f_3‖f_4,by analyzing the relation among their auto-correlation functions,their sum-of-squares indicators are investigated.Based on them,the sum-of-squares indicators of functions obtained by Canteaut et al.are investigated.The results show that the correlation property of g is good when the correlation properties of Boolean functions f_1,f_2,f_3,f_4 are good.
文摘Global minimization algorithm is indispensable for solving protein folding problems based on thermodynamic hypothesis. A contact difference （CD） based on pseudo potential function, for simulating empirical contact potential functions and testing global minimization algorithm was proposed. The present article describes a conformational sampiing and global minimization algorithm, which is called WL, based on Monte Carlo simulation and simulated annealing. It can be used to locate CD＇s globe minimum and refold extended protein structures, as small as 0. 03 nm, from the native structures, back to ones with root mean square distance（RMSD）. These results demonstrate that the global minimization problems for empirical contact potential functions may be solvable.
基金Supported by the National Natural Science Foundation of China(No.30 2 4 0 0 16)
文摘Global minimization algorithm is indispensable to solving the protein folding problem based upon thermodynamic hypothesis. Here we propose a pseudo potential function, contact difference(CD), for simulating empirical contact potential functions and testing global minimization algorithm. The present paper covers conformational sampling and global minimization algorithm called BML03, based upon Monte Carlo and simulated annealing, which is able to locate CD′s global minimum and refold extended protein structures into ones with root mean square distance(RMSD) as small as 0.03 nm from the native structures. For empirical contact potential functions, these results demonstrate that their global minimization problems may be solvable.
基金Supported by the Natural Science Foundation of Hubei Province (2007ABA124)the Youth Project Foundation of Hubei Province Education Department (Q200722001)the Major Foundation of Hubei Province Education Department (D200722002)
文摘The stability of a periodic oscillation and the global exponential class of recurrent neural networks with non-monotone activation functions and time-varying delays are analyzed. For two sets of activation functions, some algebraic criteria for ascertaining global exponential periodicity and global exponential stability of the class of recurrent neural networks are derived by using the comparison principle and the theory of monotone operator. These conditions are easy to check in terms of system parameters. In addition, we provide a new and efficacious method for the qualitative analysis of various neural networks.
