In this paper are reported the local minimum problem by means of current greedy algorithm for training the empirical potential function of protein folding on 8623 non-native structures of 31 globular proteins and a so...In this paper are reported the local minimum problem by means of current greedy algorithm for training the empirical potential function of protein folding on 8623 non-native structures of 31 globular proteins and a solution of the problem based upon the simulated annealing algorithm. This simulated annealing algorithm is indispensable for developing and testing highly refined empirical potential functions.展开更多
This paper introduces the quantum control of Lyapunov functions based on the state distance, the mean of imaginary quantities and state errors.In this paper, the specific control laws under the three forms are given.S...This paper introduces the quantum control of Lyapunov functions based on the state distance, the mean of imaginary quantities and state errors.In this paper, the specific control laws under the three forms are given.Stability is analyzed by the La Salle invariance principle and the numerical simulation is carried out in a 2D test system.The calculation process for the Lyapunov function is based on a combination of the average of virtual mechanical quantities, the particle swarm algorithm and a simulated annealing algorithm.Finally, a unified form of the control laws under the three forms is given.展开更多
Simulated annealing (SA) has been a very useful stochastic method for solving problems of multidimensional global optimization that ensures convergence to a global optimum. This paper proposes a variable cooling facto...Simulated annealing (SA) has been a very useful stochastic method for solving problems of multidimensional global optimization that ensures convergence to a global optimum. This paper proposes a variable cooling factor (VCF) model for simulated annealing schedule as a new cooling scheme to determine an optimal annealing algorithm called the Powell-simulated annealing (PSA) algorithm. The PSA algorithm is aimed at speeding up the annealing process and also finding the global minima of test functions of several variables without calculating their derivatives. It has been applied and compared with the SA algorithm and Nelder and Mead Simplex (NMS) methods on Rosenbrock valleys in 2 dimensions and multiminima functions in 3, 4 and 8 dimensions. The PSA algorithm proves to be more reliable and always able to find the optimum or a point very close to it with minimal number of iterations and computational time. The VCF compares favourably with the Lundy and Mees, linear, exponential and geometric cooling schemes based on their relative cooling rates. The PSA algorithm has also been programmed to run on android smartphone systems (ASS) that facilitates the computation of combinatorial optimization problems.展开更多
A loop modeling method, adaptive simulated annealing, for ab initio prediction of protein loop structures, as an optimization problem of searching the global minimum of a given energy function, is proposed. An interfa...A loop modeling method, adaptive simulated annealing, for ab initio prediction of protein loop structures, as an optimization problem of searching the global minimum of a given energy function, is proposed. An interface-friendly toolbox—LoopModeller in Windows and Linux systems, VC++ and OpenGL environments is developed for analysis and visualization. Simulation results of three short-chain neurotoxins modeled by LoopModeller show that the method proposed is fast and efficient.展开更多
Multi-constrained Quality-of-Service (QoS) routing is a big challenge for Mobile Ad hoc Networks (MANETs) where the topology may change constantly. In this paper a novel QoS Routing Algorithm based on Simulated Anneal...Multi-constrained Quality-of-Service (QoS) routing is a big challenge for Mobile Ad hoc Networks (MANETs) where the topology may change constantly. In this paper a novel QoS Routing Algorithm based on Simulated Annealing (SA_RA) is proposed. This algorithm first uses an energy function to translate multiple QoS weights into a single mixed metric and then seeks to find a feasible path by simulated annealing. The pa- per outlines simulated annealing algorithm and analyzes the problems met when we apply it to Qos Routing (QoSR) in MANETs. Theoretical analysis and experiment results demonstrate that the proposed method is an effective approximation algorithms showing better performance than the other pertinent algorithm in seeking the (approximate) optimal configuration within a period of polynomial time.展开更多
To get simpler operation in modified fuzzy adaptive learning control network （FALCON） in some engineering application, sigmoid nonlinear function is employed as a substitute of traditional Gaussian membership functi...To get simpler operation in modified fuzzy adaptive learning control network （FALCON） in some engineering application, sigmoid nonlinear function is employed as a substitute of traditional Gaussian membership function. For making the modified FALCON learning more efficient and stable, a simulated annealing （SA） learning coefficient is introduced into learning algorithm. At first, the basic concepts and main advantages of FALCON were briefly reviewed. Subsequently, the topological structure and nodes operation were illustrated; the gradient-descent learning algorithm with SA learning coefficient was derived; and the distinctions between the archetype and the modification were analyzed. Eventually, the significance and worthiness of the modified FALCON were validated by its application to probability prediction of anode effect in aluminium electrolysis cells.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
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
The Weibull function,a continuous probability distribution,is widely used for diameter distribution modelling,in which parameter estimation performance is affected by stand attributes and fitting methods.The Weibull c...The Weibull function,a continuous probability distribution,is widely used for diameter distribution modelling,in which parameter estimation performance is affected by stand attributes and fitting methods.The Weibull cumulative distribution function is nonlinear,and classical fitting methods may provide a not optimal solution.Invoking the use of artificial intelligence by metaheuristics is reasonable for this optimisation task.Therefore,aimed and compared(1)the metaheuristics genetic algorithm and simulated annealing performance over the moment and percentile methods;(2)the hybrid strategy merging the metaheuristics tested and the percentile method and,(3)the metaheuristics fitness functions under basal area and density errors.A long-term experiment in a Pinus taeda stand subjected to crown thinning was used.According to our findings,all methods have a similar performance,independent of the thinning regimes and age.The pattern of the estimated parameters tends to be acceptable,as b increases over time and c increases after thinning.Overall,our findings suggest that methods based on metaheuristics have a higher precision than classical methods for estimating Weibull parameters.According to the classification test,the methods that involved simulated annealing stood out.The hybrid method involving this metaheuristic also stood out,with accurate estimates.Classical methods showed the poorest performance,and we therefore suggest the use of simulated annealing due to its faster processing time and high-quality solution.展开更多
基金Supported by the National Nataral Science Foundation of China(No.39980 0 0 5 )
文摘In this paper are reported the local minimum problem by means of current greedy algorithm for training the empirical potential function of protein folding on 8623 non-native structures of 31 globular proteins and a solution of the problem based upon the simulated annealing algorithm. This simulated annealing algorithm is indispensable for developing and testing highly refined empirical potential functions.
基金Project supported by the National Natural Science Foundation of China (Grant No.62176140)。
文摘This paper introduces the quantum control of Lyapunov functions based on the state distance, the mean of imaginary quantities and state errors.In this paper, the specific control laws under the three forms are given.Stability is analyzed by the La Salle invariance principle and the numerical simulation is carried out in a 2D test system.The calculation process for the Lyapunov function is based on a combination of the average of virtual mechanical quantities, the particle swarm algorithm and a simulated annealing algorithm.Finally, a unified form of the control laws under the three forms is given.
文摘Simulated annealing (SA) has been a very useful stochastic method for solving problems of multidimensional global optimization that ensures convergence to a global optimum. This paper proposes a variable cooling factor (VCF) model for simulated annealing schedule as a new cooling scheme to determine an optimal annealing algorithm called the Powell-simulated annealing (PSA) algorithm. The PSA algorithm is aimed at speeding up the annealing process and also finding the global minima of test functions of several variables without calculating their derivatives. It has been applied and compared with the SA algorithm and Nelder and Mead Simplex (NMS) methods on Rosenbrock valleys in 2 dimensions and multiminima functions in 3, 4 and 8 dimensions. The PSA algorithm proves to be more reliable and always able to find the optimum or a point very close to it with minimal number of iterations and computational time. The VCF compares favourably with the Lundy and Mees, linear, exponential and geometric cooling schemes based on their relative cooling rates. The PSA algorithm has also been programmed to run on android smartphone systems (ASS) that facilitates the computation of combinatorial optimization problems.
文摘A loop modeling method, adaptive simulated annealing, for ab initio prediction of protein loop structures, as an optimization problem of searching the global minimum of a given energy function, is proposed. An interface-friendly toolbox—LoopModeller in Windows and Linux systems, VC++ and OpenGL environments is developed for analysis and visualization. Simulation results of three short-chain neurotoxins modeled by LoopModeller show that the method proposed is fast and efficient.
基金Supported by the National Natural Science Foundation of China (No.60472104), the Natural Science Research Program of Jiangsu Province (No.04KJB510094).
文摘Multi-constrained Quality-of-Service (QoS) routing is a big challenge for Mobile Ad hoc Networks (MANETs) where the topology may change constantly. In this paper a novel QoS Routing Algorithm based on Simulated Annealing (SA_RA) is proposed. This algorithm first uses an energy function to translate multiple QoS weights into a single mixed metric and then seeks to find a feasible path by simulated annealing. The pa- per outlines simulated annealing algorithm and analyzes the problems met when we apply it to Qos Routing (QoSR) in MANETs. Theoretical analysis and experiment results demonstrate that the proposed method is an effective approximation algorithms showing better performance than the other pertinent algorithm in seeking the (approximate) optimal configuration within a period of polynomial time.
文摘To get simpler operation in modified fuzzy adaptive learning control network （FALCON） in some engineering application, sigmoid nonlinear function is employed as a substitute of traditional Gaussian membership function. For making the modified FALCON learning more efficient and stable, a simulated annealing （SA） learning coefficient is introduced into learning algorithm. At first, the basic concepts and main advantages of FALCON were briefly reviewed. Subsequently, the topological structure and nodes operation were illustrated; the gradient-descent learning algorithm with SA learning coefficient was derived; and the distinctions between the archetype and the modification were analyzed. Eventually, the significance and worthiness of the modified FALCON were validated by its application to probability prediction of anode effect in aluminium electrolysis cells.
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.
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This work was supported fi nancially by agency CAPES(Coordination for the Improvement of Higher Education Personnel)(Finance Code 001).
文摘The Weibull function,a continuous probability distribution,is widely used for diameter distribution modelling,in which parameter estimation performance is affected by stand attributes and fitting methods.The Weibull cumulative distribution function is nonlinear,and classical fitting methods may provide a not optimal solution.Invoking the use of artificial intelligence by metaheuristics is reasonable for this optimisation task.Therefore,aimed and compared(1)the metaheuristics genetic algorithm and simulated annealing performance over the moment and percentile methods;(2)the hybrid strategy merging the metaheuristics tested and the percentile method and,(3)the metaheuristics fitness functions under basal area and density errors.A long-term experiment in a Pinus taeda stand subjected to crown thinning was used.According to our findings,all methods have a similar performance,independent of the thinning regimes and age.The pattern of the estimated parameters tends to be acceptable,as b increases over time and c increases after thinning.Overall,our findings suggest that methods based on metaheuristics have a higher precision than classical methods for estimating Weibull parameters.According to the classification test,the methods that involved simulated annealing stood out.The hybrid method involving this metaheuristic also stood out,with accurate estimates.Classical methods showed the poorest performance,and we therefore suggest the use of simulated annealing due to its faster processing time and high-quality solution.
