Particle swarm optimization(PSO)is a stochastic computation tech-nique that has become an increasingly important branch of swarm intelligence optimization.However,like other evolutionary algorithms,PSO also suffers fr...Particle swarm optimization(PSO)is a stochastic computation tech-nique that has become an increasingly important branch of swarm intelligence optimization.However,like other evolutionary algorithms,PSO also suffers from premature convergence and entrapment into local optima in dealing with complex multimodal problems.Thus this paper puts forward an adaptive multi-updating strategy based particle swarm optimization(abbreviated as AMS-PSO).To start with,the chaotic sequence is employed to generate high-quality initial particles to accelerate the convergence rate of the AMS-PSO.Subsequently,according to the current iteration,different update schemes are used to regulate the particle search process at different evolution stages.To be specific,two different sets of velocity update strategies are utilized to enhance the exploration ability in the early evolution stage while the other two sets of velocity update schemes are applied to improve the exploitation capability in the later evolution stage.Followed by the unequal weightage of acceleration coefficients is used to guide the search for the global worst particle to enhance the swarm diversity.In addition,an auxiliary update strategy is exclusively leveraged to the global best particle for the purpose of ensuring the convergence of the PSO method.Finally,extensive experiments on two sets of well-known benchmark functions bear out that AMS-PSO outperforms several state-of-the-art PSOs in terms of solution accuracy and convergence rate.展开更多
In order to overcome the difficulties caused by singular optima, in the present paper, a new method for the solutions of structural topology optimization problems is proposed. The distinctive feature of this method is...In order to overcome the difficulties caused by singular optima, in the present paper, a new method for the solutions of structural topology optimization problems is proposed. The distinctive feature of this method is that instead of solving the original optimization problem directly, we turn to seeking the solutions of a sequence of approximated problems which are formulated by relaxing the constraints of the original problem to some extent. The approximated problem can be solved efficiently by employing the algorithms developed for sizing optimization problems because its solution is not singular. It can also be proved that when the relaxation parameter is tending to zero, the solution of the approximated problem will converge to the solution of the original problem uniformly. Numerical examples illustrate the effectiveness and validity of the present approach. Results are also compared with those obtained by traditional methods.展开更多
Active control of a flexible cantilever plate with multiple time delays is investigated using the discrete optimal control method. A controller with multiple time delays is presented. In this controller, time delay ef...Active control of a flexible cantilever plate with multiple time delays is investigated using the discrete optimal control method. A controller with multiple time delays is presented. In this controller, time delay effect is incorporated in the mathematical model of the dynamic system throughout the control design and no approximations and assumptions are made in the controller derivation, so the system stability is easily guaranteed. Furthermore, this controller is available for both small time delays and large time delays. The feasibility and efficiency of the proposed controller are verified through numerical simulations in the end of this paper.展开更多
Aims The present study aimed to determine the frequency and the impact on clinical outcome of atrial fibrillation(AF) in patients with acute myocardial infarction(AMI) and left ventricular dysfunction. Methods and res...Aims The present study aimed to determine the frequency and the impact on clinical outcome of atrial fibrillation(AF) in patients with acute myocardial infarction(AMI) and left ventricular dysfunction. Methods and results In the OPTIMAAL trial, 5477 patients with AMI and signs of left ventricular dysfunction were included. At baseline, 655 patients(12% ) had AF, and 345(7.2% ) developed new- onset AF during follow- up(2.7± 0.9 years). Older patients, patients with history of angina and worse Killip class had and developed AF more frequently(P< 0.001). Patients with AF at baseline were at increased risk relative to those without AF for mortality[adjusted hazard ratio(HR) of 1.32, P=0.001] and for stroke(HR 1.77, P< 0.001). New- onset AF was associated with increased subsequent mortality for the first 30 days following randomization(HR 3.83, P< 0.001) and the entire trial period(HR 1.82, P< 0.001). Risk of stroke was increased for the first 30 days(HR 14.6, P< 0.001) and for the whole trial period(HR 2.29, P< 0.001). Conclusion AF is frequently observed in patients with AMI complicated by heart failure. Current AF, and the development of new AF soon after AMI, is associated with increased risk of death and stroke.展开更多
基金sponsored by the Natural Science Foundation of Xinjiang Uygur Autonomous Region(No.2022D01A16)the Program of the Applied Technology Research and Development of Kashi Prefecture(No.KS2021026).
文摘Particle swarm optimization(PSO)is a stochastic computation tech-nique that has become an increasingly important branch of swarm intelligence optimization.However,like other evolutionary algorithms,PSO also suffers from premature convergence and entrapment into local optima in dealing with complex multimodal problems.Thus this paper puts forward an adaptive multi-updating strategy based particle swarm optimization(abbreviated as AMS-PSO).To start with,the chaotic sequence is employed to generate high-quality initial particles to accelerate the convergence rate of the AMS-PSO.Subsequently,according to the current iteration,different update schemes are used to regulate the particle search process at different evolution stages.To be specific,two different sets of velocity update strategies are utilized to enhance the exploration ability in the early evolution stage while the other two sets of velocity update schemes are applied to improve the exploitation capability in the later evolution stage.Followed by the unequal weightage of acceleration coefficients is used to guide the search for the global worst particle to enhance the swarm diversity.In addition,an auxiliary update strategy is exclusively leveraged to the global best particle for the purpose of ensuring the convergence of the PSO method.Finally,extensive experiments on two sets of well-known benchmark functions bear out that AMS-PSO outperforms several state-of-the-art PSOs in terms of solution accuracy and convergence rate.
基金The project supported by the National Natural Science Foundation of China under project No.19572023
文摘In order to overcome the difficulties caused by singular optima, in the present paper, a new method for the solutions of structural topology optimization problems is proposed. The distinctive feature of this method is that instead of solving the original optimization problem directly, we turn to seeking the solutions of a sequence of approximated problems which are formulated by relaxing the constraints of the original problem to some extent. The approximated problem can be solved efficiently by employing the algorithms developed for sizing optimization problems because its solution is not singular. It can also be proved that when the relaxation parameter is tending to zero, the solution of the approximated problem will converge to the solution of the original problem uniformly. Numerical examples illustrate the effectiveness and validity of the present approach. Results are also compared with those obtained by traditional methods.
基金the National Natural Science Foundation of China (Nos. 10772112 and 10472065)the KeyProject of Ministry of Education of China (No. 107043)the Specialized Research Fund for the Doctoral Program ofHigher Education of China (No. 20070248032).
文摘Active control of a flexible cantilever plate with multiple time delays is investigated using the discrete optimal control method. A controller with multiple time delays is presented. In this controller, time delay effect is incorporated in the mathematical model of the dynamic system throughout the control design and no approximations and assumptions are made in the controller derivation, so the system stability is easily guaranteed. Furthermore, this controller is available for both small time delays and large time delays. The feasibility and efficiency of the proposed controller are verified through numerical simulations in the end of this paper.
文摘Aims The present study aimed to determine the frequency and the impact on clinical outcome of atrial fibrillation(AF) in patients with acute myocardial infarction(AMI) and left ventricular dysfunction. Methods and results In the OPTIMAAL trial, 5477 patients with AMI and signs of left ventricular dysfunction were included. At baseline, 655 patients(12% ) had AF, and 345(7.2% ) developed new- onset AF during follow- up(2.7± 0.9 years). Older patients, patients with history of angina and worse Killip class had and developed AF more frequently(P< 0.001). Patients with AF at baseline were at increased risk relative to those without AF for mortality[adjusted hazard ratio(HR) of 1.32, P=0.001] and for stroke(HR 1.77, P< 0.001). New- onset AF was associated with increased subsequent mortality for the first 30 days following randomization(HR 3.83, P< 0.001) and the entire trial period(HR 1.82, P< 0.001). Risk of stroke was increased for the first 30 days(HR 14.6, P< 0.001) and for the whole trial period(HR 2.29, P< 0.001). Conclusion AF is frequently observed in patients with AMI complicated by heart failure. Current AF, and the development of new AF soon after AMI, is associated with increased risk of death and stroke.
