We designed the window function of the optimal Gabor transform based on the time-frequency rotation property of the fractional Fourier transform. Thus, we obtained the adaptive optimal Gabor transform in the fractiona...We designed the window function of the optimal Gabor transform based on the time-frequency rotation property of the fractional Fourier transform. Thus, we obtained the adaptive optimal Gabor transform in the fractional domain and improved the time-frequency concentration of the Gabor transform. The algorithm first searches for the optimal rotation factor, then performs the p-th FrFT of the signal and, finally, performs time and frequency analysis of the FrFT result. Finally, the algorithm rotates the plane in the fractional domain back to the normal time-frequency plane. This promotes the application of FrFT in the field of high-resolution reservoir prediction. Additionally, we proposed an adaptive search method for the optimal rotation factor using the Parseval principle in the fractional domain, which simplifies the algorithm. We carried out spectrum decomposition of the seismic signal, which showed that the instantaneous frequency slices obtained by the proposed algorithm are superior to the ones obtained by the traditional Gabor transform. The adaptive time frequency analysis is of great significance to seismic signal processing.展开更多
Based on the analysis to the random sear ch algorithm of LUUS, a modified random directed integer search algorithm (MRDI SA) is given for first time. And a practical example is given to show that the adva ntage of th...Based on the analysis to the random sear ch algorithm of LUUS, a modified random directed integer search algorithm (MRDI SA) is given for first time. And a practical example is given to show that the adva ntage of this kind of algorithm is the reliability can’t be infuenced by the ini tial value X (0) and the start search domain R (0) . Besides, i t can be applied to solve the higher dimensional constrained nonlinear integer p rogramming problem.展开更多
Based on crowding mechanism, a novel niche genetic algorithm was proposed which can record evolution- ary direction dynamically during evolution. After evolution, the solutions’s precision can be greatly improved by ...Based on crowding mechanism, a novel niche genetic algorithm was proposed which can record evolution- ary direction dynamically during evolution. After evolution, the solutions’s precision can be greatly improved by means of the local searching along the recorded direction. Simulation shows that this algorithm can not only keep population diversity but also find accurate solutions. Although using this method has to take more time compared with the standard GA, it is really worth applying to some cases that have to meet a demand for high solution precision.展开更多
A maximally flat FIR filter design method based on explicit formulas combined with simulated annealing and random search was presented. Utilizing the explicit formulas to calculate the ini- tial values, the firate-wor...A maximally flat FIR filter design method based on explicit formulas combined with simulated annealing and random search was presented. Utilizing the explicit formulas to calculate the ini- tial values, the firate-word-length FIR filter design problem was converted into optimization of the filter coefficients, An optimization method combined with local discrete random search and simulated annealing was proposed, with the result of optimum solution in the sense of Chebyshev approximation. The proposed method can simplify the design process of FIR filter and reduce the calculation burden. The simulation result indicates that the proposed method is superior to the traditional round off method and can reduce the value of the objective function to 41%～74%.展开更多
Biologic behaviors are the principal source for proposing new intelligent algorithms. Based on the mechanism of the bio-subsistence and the bio-migration, this paper proposes a novel algorithm—Living Migration Algori...Biologic behaviors are the principal source for proposing new intelligent algorithms. Based on the mechanism of the bio-subsistence and the bio-migration, this paper proposes a novel algorithm—Living Migration Algorithm (LMA). The original contributions of LMA are three essential attributes of each individual: the minimal life-needs which are the necessaries for survival, the migrating which is a basal action for searching new living space, and the judging which is an important ability of deciding whether to migrate or not. When living space of all individuals can satisfy the minimal life-needs at some generation, they are considered as the optimal living places where objective functions will obtain the optima. LMA may be employed in large-scale computation and engineering field. The paper mostly operates LMA to deal with four non-linear and heterogeneous optimizations, and experiments prove LMA has better performances than Free Search algorithm.展开更多
This paper discusses a search problem for a Helix target motion in which any information of the target position is not available to the searchers. There exist three searchers start searching for the target from the or...This paper discusses a search problem for a Helix target motion in which any information of the target position is not available to the searchers. There exist three searchers start searching for the target from the origin. The purpose of this paper is to formulate a search model and finds the conditions under which the expected value of the first meeting time between one of the searchers and the target is finite. Also, the existence of the optimal search plan that minimizes the expected value of the first meeting time is shown. Furthermore,this optimal search plan is found. The effectiveness of this method is illustrated by using an example with numerical results.展开更多
In order to make cloud users get credible, high-quality composition of services, the trust quality of service aware(TQoS-aware) based parallel ant colony algorithm is proposed. Our approach takes the service credibili...In order to make cloud users get credible, high-quality composition of services, the trust quality of service aware(TQoS-aware) based parallel ant colony algorithm is proposed. Our approach takes the service credibility as the weight of the quality of service, then calculates the trust service quality T-QoS for each service, making the service composition situated in a credible environment. Through the establishment on a per-service T-QoS initialization pheromone matrix, we can reduce the colony's initial search time. By modifying the pheromone updating rules and introducing two ant colonies to search from different angles in parallel,we can avoid falling into the local optimal solution, and quickly find the optimal combination of global solutions. Experiments show that our approach can combine high-quality services and the improvement of the operational success rate. Also, the convergence rate and the accuracy of optimal combination are improved.展开更多
This paper proposes an inexact SQP method in association with line search filter technique for solving nonlinear equality constrained optimization. For large-scale applications, it is expensive to get an exact search ...This paper proposes an inexact SQP method in association with line search filter technique for solving nonlinear equality constrained optimization. For large-scale applications, it is expensive to get an exact search direction, and hence the authors use an inexact method that finds an approximate solution satisfying some appropriate conditions. The global convergence of the proposed algorithm is established by using line search filter technique. The second-order correction step is used to overcome the Maratos effect, while the line search filter inexact SQP method has q-superlinear local convergence rate. Finally, the results of numerical experiments indicate that the proposed method is efficient for the given test problems.展开更多
The locally optimal block preconditioned 4-d conjugate gradient method(LOBP4dC G) for the linear response eigenvalue problem was proposed by Bai and Li(2013) and later was extended to the generalized linear response e...The locally optimal block preconditioned 4-d conjugate gradient method(LOBP4dC G) for the linear response eigenvalue problem was proposed by Bai and Li(2013) and later was extended to the generalized linear response eigenvalue problem by Bai and Li(2014). We put forward two improvements to the method: A shifting deflation technique and an idea of extending the search subspace. The deflation technique is able to deflate away converged eigenpairs from future computation, and the idea of extending the search subspace increases convergence rate per iterative step. The resulting algorithm is called the extended LOBP4 dC G(ELOBP4dC G).Numerical results of the ELOBP4 dC G strongly demonstrate the capability of deflation technique and effectiveness the search space extension for solving linear response eigenvalue problems arising from linear response analysis of two molecule systems.展开更多
In this paper, a new class of memoryless non-quasi-Newton method for solving unconstrained optimization problems is proposed, and the global convergence of this method with inexact line search is proved. Furthermore, ...In this paper, a new class of memoryless non-quasi-Newton method for solving unconstrained optimization problems is proposed, and the global convergence of this method with inexact line search is proved. Furthermore, we propose a hybrid method that mixes both the memoryless non-quasi-Newton method and the memoryless Perry-Shanno quasi-Newton method. The global convergence of this hybrid memoryless method is proved under mild assumptions. The initial results show that these new methods are efficient for the given test problems. Especially the memoryless non-quasi-Newton method requires little storage and computation, so it is able to efficiently solve large scale optimization problems.展开更多
基金supported by national natural science foundation of China(No.41274127,41301460,40874066,and 40839905)
文摘We designed the window function of the optimal Gabor transform based on the time-frequency rotation property of the fractional Fourier transform. Thus, we obtained the adaptive optimal Gabor transform in the fractional domain and improved the time-frequency concentration of the Gabor transform. The algorithm first searches for the optimal rotation factor, then performs the p-th FrFT of the signal and, finally, performs time and frequency analysis of the FrFT result. Finally, the algorithm rotates the plane in the fractional domain back to the normal time-frequency plane. This promotes the application of FrFT in the field of high-resolution reservoir prediction. Additionally, we proposed an adaptive search method for the optimal rotation factor using the Parseval principle in the fractional domain, which simplifies the algorithm. We carried out spectrum decomposition of the seismic signal, which showed that the instantaneous frequency slices obtained by the proposed algorithm are superior to the ones obtained by the traditional Gabor transform. The adaptive time frequency analysis is of great significance to seismic signal processing.
文摘Based on the analysis to the random sear ch algorithm of LUUS, a modified random directed integer search algorithm (MRDI SA) is given for first time. And a practical example is given to show that the adva ntage of this kind of algorithm is the reliability can’t be infuenced by the ini tial value X (0) and the start search domain R (0) . Besides, i t can be applied to solve the higher dimensional constrained nonlinear integer p rogramming problem.
文摘Based on crowding mechanism, a novel niche genetic algorithm was proposed which can record evolution- ary direction dynamically during evolution. After evolution, the solutions’s precision can be greatly improved by means of the local searching along the recorded direction. Simulation shows that this algorithm can not only keep population diversity but also find accurate solutions. Although using this method has to take more time compared with the standard GA, it is really worth applying to some cases that have to meet a demand for high solution precision.
文摘A maximally flat FIR filter design method based on explicit formulas combined with simulated annealing and random search was presented. Utilizing the explicit formulas to calculate the ini- tial values, the firate-word-length FIR filter design problem was converted into optimization of the filter coefficients, An optimization method combined with local discrete random search and simulated annealing was proposed, with the result of optimum solution in the sense of Chebyshev approximation. The proposed method can simplify the design process of FIR filter and reduce the calculation burden. The simulation result indicates that the proposed method is superior to the traditional round off method and can reduce the value of the objective function to 41%～74%.
文摘Biologic behaviors are the principal source for proposing new intelligent algorithms. Based on the mechanism of the bio-subsistence and the bio-migration, this paper proposes a novel algorithm—Living Migration Algorithm (LMA). The original contributions of LMA are three essential attributes of each individual: the minimal life-needs which are the necessaries for survival, the migrating which is a basal action for searching new living space, and the judging which is an important ability of deciding whether to migrate or not. When living space of all individuals can satisfy the minimal life-needs at some generation, they are considered as the optimal living places where objective functions will obtain the optima. LMA may be employed in large-scale computation and engineering field. The paper mostly operates LMA to deal with four non-linear and heterogeneous optimizations, and experiments prove LMA has better performances than Free Search algorithm.
文摘This paper discusses a search problem for a Helix target motion in which any information of the target position is not available to the searchers. There exist three searchers start searching for the target from the origin. The purpose of this paper is to formulate a search model and finds the conditions under which the expected value of the first meeting time between one of the searchers and the target is finite. Also, the existence of the optimal search plan that minimizes the expected value of the first meeting time is shown. Furthermore,this optimal search plan is found. The effectiveness of this method is illustrated by using an example with numerical results.
基金supported by the National Natural Science Foundation of China(6140224161170065+13 种基金61373017611710536110319561203217612011636120200461202354)Scientific&Technological Support Project(Industry)of Jiangsu Province(BE2012183BE2012755)Natural Science Key Fund for Colleges and Universities of Jiangsu Province(11KJA52000112KJA520002)the Natural Science Fund for Colleges and Universities of Jiangsu Province(13KJB520017)Scientific Research&Industry Promotion Project for Higher Education Institutions(JHB2012-7)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)(yx002001)
文摘In order to make cloud users get credible, high-quality composition of services, the trust quality of service aware(TQoS-aware) based parallel ant colony algorithm is proposed. Our approach takes the service credibility as the weight of the quality of service, then calculates the trust service quality T-QoS for each service, making the service composition situated in a credible environment. Through the establishment on a per-service T-QoS initialization pheromone matrix, we can reduce the colony's initial search time. By modifying the pheromone updating rules and introducing two ant colonies to search from different angles in parallel,we can avoid falling into the local optimal solution, and quickly find the optimal combination of global solutions. Experiments show that our approach can combine high-quality services and the improvement of the operational success rate. Also, the convergence rate and the accuracy of optimal combination are improved.
基金supported by the National Science Foundation Grant under Grant No.10871130the Shanghai Leading Academic Discipline Project under Grant No.T0401
文摘This paper proposes an inexact SQP method in association with line search filter technique for solving nonlinear equality constrained optimization. For large-scale applications, it is expensive to get an exact search direction, and hence the authors use an inexact method that finds an approximate solution satisfying some appropriate conditions. The global convergence of the proposed algorithm is established by using line search filter technique. The second-order correction step is used to overcome the Maratos effect, while the line search filter inexact SQP method has q-superlinear local convergence rate. Finally, the results of numerical experiments indicate that the proposed method is efficient for the given test problems.
基金supported by National Science Foundation of USA(Grant Nos.DMS1522697,CCF-1527091,DMS-1317330 and CCF-1527091)National Natural Science Foundation of China(Grant No.11428104)
文摘The locally optimal block preconditioned 4-d conjugate gradient method(LOBP4dC G) for the linear response eigenvalue problem was proposed by Bai and Li(2013) and later was extended to the generalized linear response eigenvalue problem by Bai and Li(2014). We put forward two improvements to the method: A shifting deflation technique and an idea of extending the search subspace. The deflation technique is able to deflate away converged eigenpairs from future computation, and the idea of extending the search subspace increases convergence rate per iterative step. The resulting algorithm is called the extended LOBP4 dC G(ELOBP4dC G).Numerical results of the ELOBP4 dC G strongly demonstrate the capability of deflation technique and effectiveness the search space extension for solving linear response eigenvalue problems arising from linear response analysis of two molecule systems.
基金Foundation item： the National Natural Science Foundation of China （No. 60472071） the Science Foundation of Beijing Municipal Commission of Education （No. KM200710028001）.
文摘In this paper, a new class of memoryless non-quasi-Newton method for solving unconstrained optimization problems is proposed, and the global convergence of this method with inexact line search is proved. Furthermore, we propose a hybrid method that mixes both the memoryless non-quasi-Newton method and the memoryless Perry-Shanno quasi-Newton method. The global convergence of this hybrid memoryless method is proved under mild assumptions. The initial results show that these new methods are efficient for the given test problems. Especially the memoryless non-quasi-Newton method requires little storage and computation, so it is able to efficiently solve large scale optimization problems.
