共查询到20条相似文献，搜索用时 31 毫秒
1.
《重庆第二师范学院学报》2013,(6):166-168
Generalized nonlinear mixed quasi-variational inclusions with H-accretive opertors in banach spaces by YANG Xin-Bo P. 5 In this paper, the resolvent operator technique is applied to suggest a new iterative algorithm, to consider a new class of generalized nonlinear mixed quasi-variational inclusions involving H-accretive operator in q-uniformly smooth banach spaces, and to conduct convergence analysis of the results. Key words： H-accretive operator; q-uniformly smooth banaeh spaces; variational inclusions; iterative algo- rithm 相似文献
2.
A fault diagnosis model is proposed based on fuzzy support vector machine (FSVM) combined with fuzzy clustering (FC).Considering the relationship between the sample point and non-self class,FC algorithm is applied to generate fuzzy memberships.In the algorithm,sample weights based on a distribution density function of data point and genetic algorithm (GA) are introduced to enhance the performance of FC.Then a multi-class FSVM with radial basis function kernel is established according to directed acyclic graph algorithm,the penalty factor and kernel parameter of which are optimized by GA.Finally,the model is executed for multi-class fault diagnosis of rolling element bearings.The results show that the presented model achieves high performances both in identifying fault types and fault degrees.The performance comparisons of the presented model with SVM and distance-based FSVM for noisy case demonstrate the capacity of dealing with noise and generalization. 相似文献
3.
A maximum power point tracker for photovoltaic energy systems based on fuzzy neural networks 总被引：1，自引：0，他引：1
Chun-hua Li Xin-jian Zhu Guang-yi Cao Wan-qi Hu Sheng Sui Ming-ruo Hu 《浙江大学学报(A卷英文版)》2009,10(2):263-270
To extract the maximum power from a photovoltaic （PV） energy system, the real-time maximum power point （MPP） of the PV array must be tracked closely. The non-linear and time-variant characteristics of the PV array and the non-linear and non-minimum phase characteristics of a boost converter make it difficult to track the MPP for traditional control strategies. We propose a fuzzy neural network controller （FNNC）, which combines the reasoning capability of fuzzy logical systems and the learning capability of neural networks, to track the MPP. With a derived learning algorithm, the parameters of the FNNC are updated adaptively. A gradient estimator based on a radial basis function neural network is developed to provide the reference information to the FNNC. Simulation results show that the proposed control algorithm provides much better tracking performance compared with the filzzy logic control algorithm. 相似文献
4.
LIU Guang-hui CHEN Chuan-bo 《浙江大学学报(A卷英文版)》2007,8(8):1210-1217
When the edges of a convex polygon are traversed along one direction,the interior of the convex polygon is always on the same side of the edges. Based on this characteristic of convex polygons,a new algorithm for computing the convex hull of a simple polygon is proposed in this paper,which is then extended to a new algorithm for computing the convex hull of a planar point set. First,the extreme points of the planar point set are found,and the subsets of point candidate for vertex of the convex hull between extreme points are obtained. Then,the ordered convex hull point sequences between extreme points are constructed separately and concatenated by removing redundant extreme points to get the convex hull. The time complexity of the new planar convex hull algorithm is O(nlogh) ,which is equal to the time complexity of the best output-sensitive planar convex hull algorithms. Compared with the algorithm having the same complexity,the new algorithm is much faster. 相似文献
5.
《重庆大学学报(英文版)》2002,1(1):74-76
A class of strongly nonlinear implicit complementarity problems for set-valued mappings in Hilbert spaces is studied,Thereupon a new existence theorem is established and proved to be a solution to that kind of problems. 相似文献
6.
Fuzzy finish time modeling for project scheduling 总被引：1，自引：0，他引：1
This research aims at developing a new fuzzy activity finish time estimation model for project scheduling management.With the application of the fuzzy quality function deployment （FQFD） and fuzzy analytic hierarchy process （FAHP） methods,the degree of fuzziness for every project activity is calculated in accordance with considerations of project uncertainties.These uncertainties are measured by the risk level of such project-related characteristics as time limit,activity start time,budget,manpower,technological difficulty,and facility requirements.In this paper,rather than applying the de-fuzzification technique to obtain the crisp activity duration for project scheduling,the fuzzy finish time estimation method for every activity is proposed based on the degree of fuzziness.The corresponding fuzzy activity duration time plot is also developed in a new fuzzy Gantt chart.The proposed model can provide a reasonable fuzzy finish time estimation for every activity,while most scheduling methods only provide the finish time of the entire project.Compared to existing models,this time estimation model and its corresponding Gantt chart are predicted to have higher reliability and practical application in project management and scheduling. 相似文献
7.
8.
线性约束凸规划的一个新原-对偶路径-跟踪内点算法 总被引：1，自引：0，他引：1
In this paper, a primal-dual path-following interior-point algorithm for linearly constrained convex optimization （LCCO） is presented. The algorithm is based on a new technique for finding a class of search directions and the strategy of the central path. At each iteration, only full-Newton steps are used. Finally, the favorable polynomial complexity bound for the algorithm with the small-update method is deserved, namely, O（√nlog n/ε）. 相似文献
9.
丁体明 《重庆大学学报(英文版)》2002,1(1):74-76
A class of strongly nonlinear implicit complementarity problems for set-valued mappings in Hilbert spaces is studied. Thereupon a new existence theorem is established and proved to be a solution to that kind of problems. 相似文献
10.
A new calibration algorithm for multi-camera systems using 1D calibration objects is proposed. The algorithm integrates the rank-4 factorization with Zhang （2004）＇s method. The intrinsic parameters as well as the extrinsic parameters are recovered by capturing with cameras the 1D object＇s rotations around a fixed point. The algorithm is based on factorization of the scaled measurement matrix, the projective depth of which is estimated in an analytical equation instead ofa recursive form. For more than three points on a 1D object, the approach of our algorithm is to extend the scaled measurement matrix. The obtained parameters are finally refined through the maximum likelihood inference. Simulations and experiments with real images verify that the proposed technique achieves a good trade-off between the intrinsic and extrinsic camera parameters. 相似文献
11.
The step-size procedure is very important for solving optimization problems. The Armijo step-size rule, the Armijo-Goldstein step-size rule and the Wolfe-Powell step-size rule are three well-known line search methods. On the basis of the above three types of line search methods and the idea of the proximal point methods, a new class of step-size rules was proposed. Instead of a single objective function f, f ＋1/2（x - xk）^TBk（x-Xk） was used as the merit function in iteration k, where Sk is a given symmetric positive definite matrix. The existence of the steplength for the new rules was proved. Some convergence properties were also discussed. 相似文献
12.
This paper presents the forward displacement analysis of an 8-PSS （prismatic-spherical-spherical） redundant parallel manipulator whose moving platform is linked to the base platform by eight kinemtic chains consisting of a PSS joint and a strut with fixed length. A general approximation algorithm is used to solve the problem. To avoid the extraction of root in the approximation process, the forward displacement analysis of the 8-PSS redundant parallel manipulator is transformed into another equivalent problem on the assumption that the strut is extensible while the slider is fixed. The problem is solved by a modified approximation algorithm which predicates that the manipulator will move along a pose vector to reduce the difference between the desired configuration and an instantaneous one, and the best movement should be with minimum norm and least quadratic sum. The characteristic of this modified algorithm is that its convergence domain is larger than that of the general approximation algorithm. Simulation results show that the modelified algorithm is general and can be used for the forward displacement analysis of the redundant parallel manipulator actuated by a revolute joint. 相似文献
13.
主流形和非线性维数化简的切向空间校正 总被引：8，自引：0，他引：8
We present a new algorithm for manifold learning and nonlinear dimensionality reduction. Based on a set of unorganized da-ta points sampled with noise from a parameterized manifold, the local geometry of the manifold is learned by constructing an approxi-mation for the tangent space at each point, and those tangent spaces are then aligned to give the global coordinates of the data pointswith respect to the underlying manifold. We also present an error analysis of our algorithm showing that reconstruction errors can bequite small in some cases. We illustrate our algorithm using curves and surfaces both in 2D/3D Euclidean spaces and higher dimension-al Euclidean spaces. We also address several theoretical and algorithmic issues for further research and improvements. 相似文献
14.
In the economic order quantity （EOQ） model, the decision maker has vague information about holding cost, ordering cost and market demand. With these uncertainties characterized as fuzzy variables, a new formula is developed by analyzing the fuzzy total cost. By comparing with other four EOQ formulas, i.e., using the crisp numbers with the highest membership values in classic EOQ formula, using the expected values of fuzzy parameters in classic EOQ formula, using the fuzzy variables in classic EOQ formula and then calculating the expected value, and calculat- ing EOQ by hybrid intelligent algorithm simulation, the effectiveness of this formula Js illustrated. 相似文献
15.
Algorithm for 2D irregular-shaped nesting problem based on the NFP algorithm and lowest-gravity-center princlple 总被引：1，自引：0，他引：1
LIU Hu-yao HE Yuan-jun 《浙江大学学报(A卷英文版)》2006,7(4):570-576
The nesting problem involves arranging pieces on a plate to maximize use of material. A new scheme for 2D irregular-shaped nesting problem is proposed. The new scheme is based on the NFP （No Fit Polygon） algorithm and a new placement principle for pieces. The novel placement principle is to place a piece to the position with lowest gravity center based on NFP. In addition, genetic algorithm （GA） is adopted to find an efficient nesting sequence. The proposed scheme can deal with pieces with arbitrary rotation and containing region with holes, and achieves competitive results in experiment on benchmark datasets. 相似文献
16.
Quan Yu Kesheng Wang 《上海大学学报(英文版)》2014,(1):32-38
3D quality inspection is widely applied in many industrial fields including mould design, automotive and blade manufacturing, etc. A commonly used method is to obtain the point cloud of the inspected object and make a comparison between the point cloud and the corresponding CAD model or template. Thus, it is important to align the point cloud with the template first and foremost. Moreover, for the purpose of automatization of quality inspection, this alignment process is expected to be completed without manual interference. In this paper, we propose to combine the particle swarm optimization （PSO） with iterative closest point （ICP） algorithm to achieve the automated point cloud alignment. The combination of the two algorithms can achieve a balance between the alignment speed and accuracy, and avoid the local optimal caused by bad initial position of the point cloud. 相似文献
17.
As a basic mathematical structure,the system of inequalities over symmetric cones and its solution can provide an effective method for solving the startup problem of interior point method which is used to solve many optimization problems.In this paper,a non-interior continuation algorithm is proposed for solving the system of inequalities under the order induced by a symmetric cone.It is shown that the proposed algorithm is globally convergent and well-defined.Moreover,it can start from any point and only needs to solve one system of linear equations at most at each iteration.Under suitable assumptions,global linear and local quadratic convergence is established with Euclidean Jordan algebras.Numerical results indicate that the algorithm is efficient.The systems of random linear inequalities were tested over the second-order cones with sizes of 10,100,,1 000 respectively and the problems of each size were generated randomly for 10 times.The average iterative numbers show that the proposed algorithm can generate a solution at one step for solving the given linear class of problems with random initializations.It seems possible that the continuation algorithm can solve larger scale systems of linear inequalities over the secondorder cones quickly.Moreover,a system of nonlinear inequalities was also tested over Cartesian product of two simple second-order cones,and numerical results indicate that the proposed algorithm can deal with the nonlinear cases. 相似文献
18.
Motion simulator usually appears the phenomenon of false cues and the workspace is limited in the process of washout. The proposed washout algorithm combines fuzzy logic control with the vestibular system to design the tilt coordination fuzzy adaptive filter, in order to minimize the vestibular sensory error below the human perception threshold. Owing to tilt coordination angular velocity limiter, the loss of low-pass acceleration must be compensated by the acceleration transform model. The translational channel decreases the possibility of the workspace beyond limitation and expands the scope of motion platform simulating input acceleration by using third-order filter. The simulation results show that the proposed algorithm can effectively overcome the phase retardation of classical washout algorithm, and then prevent the produce of false cues, decrease the displacement of motion platform simultaneously; in addition, white Gaussian noise simulates large variations in acceleration. The proposed washout algorithm can have maximal extreme value of acceleration and accurate simulating performance in general. It also proves that the proposed washout algorithm has a strong adaptability and reliability, which can effectively improve the dynamic fidelity for motion simulator. 相似文献
19.
The free vibration and transient wave in a prestressed Rayleigh-Timoshenko beam subject to arbitrary transverse forces are analyzed by the newly developed method of reverberation-ray matrix （MRRM）. The effects of shear deformation and rotational inertia are taken into consideration. With a Fourier transform technique, the general wave solutions with two sets of unknown amplitude coefficients are obtained in the transformed domain for an unbonded prestressed beam under the action of arbitrary external excitations. From the coupling at joints and the compatibility of displacements in each member, the free and forced vibration responses of a beam with various boundary conditions are finally evaluated through certain numerical algorithms, Results are presented for a simply-supported beam subject to either a point fixed load or moving load. Good agreement with the finite element method （FEM） is obtained. The present work is instructive for high-speed railway bridge design and structural health monitoring. 相似文献
20.
Modeling and multi-objective optimization of a gasoline engine using neural networks and evolutionary algorithms 总被引：1，自引：0，他引：1
José D.MARTNEZ-MORALES Elvia R.PALACIOS-HERNNDEZ Gerardo A.VELZQUEZ-CARRILLO 《浙江大学学报(A卷英文版)》2013,14(9):657-670
In this paper, a multi-objective particle swarm optimization （MOPSO） algorithm and a nondominated sorting genetic algorithm II （NSGA-II） are used to optimize the operating parameters of a 1.6 L, spark ignition （SI） gasoline engine. The aim of this optimization is to reduce engine emissions in terms of carbon monoxide （CO）, hydrocarbons （HC）, and nitrogen oxides （NOx）, which are the causes of diverse environmental problems such as air pollution and global warming. Stationary engine tests were performed for data generation, covering 60 operating conditions. Artificial neural networks （ANNs） were used to predict exhaust emissions, whose inputs were from six engine operating parameters, and the outputs were three resulting exhaust emissions. The outputs of ANNs were used to evaluate objective functions within the optimization algorithms： NSGA-II and MOPSO. Then a decision-making process was conducted, using a fuzzy method to select a Pareto solution with which the best emission reductions can be achieved. The NSGA-II algorithm achieved reductions of at least 9.84%, 82.44%, and 13.78% for CO, HC, and NOx, respectively. With a MOPSO algorithm the reached reductions were at least 13.68%, 83.80%, and 7.67% for CO, HC, and NOx, respectively. 相似文献