The backtracking search optimization algorithm（BSA） is one of the most recently proposed population-based evolutionary algorithms for global optimization. Due to its memory ability and simple structure, BSA has powe...The backtracking search optimization algorithm（BSA） is one of the most recently proposed population-based evolutionary algorithms for global optimization. Due to its memory ability and simple structure, BSA has powerful capability to find global optimal solutions. However, the algorithm is still insufficient in balancing the exploration and the exploitation. Therefore, an improved adaptive backtracking search optimization algorithm combined with modified Hooke-Jeeves pattern search is proposed for numerical global optimization. It has two main parts： the BSA is used for the exploration phase and the modified pattern search method completes the exploitation phase. In particular, a simple but effective strategy of adapting one of BSA＇s important control parameters is introduced. The proposed algorithm is compared with standard BSA, three state-of-the-art evolutionary algorithms and three superior algorithms in IEEE Congress on Evolutionary Computation 2014（IEEE CEC2014） over six widely-used benchmarks and 22 real-parameter single objective numerical optimization benchmarks in IEEE CEC2014. The results of experiment and statistical analysis demonstrate the effectiveness and efficiency of the proposed algorithm.展开更多
As conventional methods for beam pattern synthesis can not always obtain the desired optimum pattern for the arbitrary underwater acoustic sensor arrays,a hybrid numerical synthesis method based on adaptive principle ...As conventional methods for beam pattern synthesis can not always obtain the desired optimum pattern for the arbitrary underwater acoustic sensor arrays,a hybrid numerical synthesis method based on adaptive principle and genetic algorithm was presented in this paper.First,based on the adaptive theory,a given array was supposed as an adaptive array and its sidelobes were reduced by assigning a number of interference signals in the sidelobe region.An initial beam pattern was obtained after several iterations and adjustments of the interference intensity,and based on its parameters,a desired pattern was created.Then,an objective function based on the difference between the designed and desired patterns can be constructed.The pattern can be optimized by using the genetic algorithm to minimize the objective function.A design example for a double-circular array demonstrates the effectiveness of this method.Compared with the approaches existing before,the proposed method can reduce the sidelobe effectively and achieve less synthesis magnitude error in the mainlobe.The method can search for optimum attainable pattern for the specific elements if the desired pattern can not be found.展开更多
In order to improve the recognition rate and accuracy rate of projectiles in six sky-screens intersection test system,this work proposes a new recognition method of projectiles by combining particle swarm optimization...In order to improve the recognition rate and accuracy rate of projectiles in six sky-screens intersection test system,this work proposes a new recognition method of projectiles by combining particle swarm optimization support vector and spatial-temporal constrain of six sky-screens detection sensor.Based on the measurement principle of the six sky-screens intersection test system and the characteristics of the output signal of the sky-screen,we analyze the existing problems regarding the recognition of projectiles.In order to optimize the projectile recognition effect,we use the support vector machine and basic particle swarm algorithm to form a new recognition algorithm.We set up the particle swarm algorithm optimization support vector projectile information recognition model that conforms to the six sky-screens intersection test system.We also construct a spatial-temporal constrain matching model based on the spatial geometric relationship of six sky-screen intersection,and form a new projectile signal recognition algorithm with six sky-screens spatial-temporal information constraints under the signal classification mechanism of particle swarm optimization algorithm support vector machine.Based on experiments,we obtain the optimal penalty and kernel function radius parameters in the PSO-SVM algorithm;we adjust the parameters of the support vector machine model,train the test signal data of every sky-screen,and gain the projectile signal classification results.Afterwards,according to the signal classification results,we calculate the coordinate parameters of the real projectile by using the spatial-temporal constrain of six sky-screens detection sensor,which verifies the feasibility of the proposed algorithm.展开更多
An artificial intelligence technique was applied to the optimization of flux adding systems and air blasting systems, the display of on line parameters, forecasting of mass and compositions of slag in the slagging per...An artificial intelligence technique was applied to the optimization of flux adding systems and air blasting systems, the display of on line parameters, forecasting of mass and compositions of slag in the slagging period, optimization of cold material adding systems and air blasting systems, the display of on line parameters, and the forecasting of copper mass in the copper blow period in copper smelting converters. They were integrated to build the Intelligent Decision Support System of the Operation Optimization of Copper Smelting Converter(IDSSOOCSC), which is self learning and self adaptating. Development steps, monoblock structure and basic functions of the IDSSOOCSC were introduced. After it was applied in a copper smelting converter, every production quota was clearly improved after IDSSOOCSC had been run for 4 months. Blister copper productivity is increased by 6%, processing load of cold input is increased by 8% and average converter life span is improved from 213 to 235 furnace times.展开更多
In this paper, a new amplitude quantization synthesis method for ultralow sidelobe phased arrays is proposed, which is based on the constrained nonlinear optimization algorithm. By introducing a set of critical constr...In this paper, a new amplitude quantization synthesis method for ultralow sidelobe phased arrays is proposed, which is based on the constrained nonlinear optimization algorithm. By introducing a set of critical constraint conditions into the optimization model, we can directly quantize the amplitude distribution instead of replacing it with a continuous equivalent aperture antenna. The mutual coupling and the element patterns are also considered in the quantization synthesis. Finally, some array simulation results are given to show the effectiveness of the method.展开更多
Many difficult engineering problems cannot be solved by the conventional optimization techniques in practice. Direct searches that need no recourse to explicit derivatives are revived and become popular since the new ...Many difficult engineering problems cannot be solved by the conventional optimization techniques in practice. Direct searches that need no recourse to explicit derivatives are revived and become popular since the new century. In order to get a deep insight into this field, some notes on the direct searches for non-smooth optimization problems are made. The global convergence vs. local convergence and their influences on expected solutions for simulation-based stochastic optimization are pointed out. The sufficient and simple decrease criteria for step acceptance are analyzed, and why simple decrease is enough for globalization in direct searches is identified. The reason to introduce the positive spanning set and its usage in direct searches is explained. Other topics such as the generalization of direct searches to bound, linear and non-linear constraints are also briefly discussed.展开更多
快速城市化与气候变化的共同胁迫使得高密度城市面临多重生态风险,包括城市热岛、洪涝灾害与空气污染等,这些生态问题不仅影响城市生态系统的稳定性,同时威胁人类福祉。因此,亟需对全球高密度城市的生态问题与应对策略开展研究。以Web o...快速城市化与气候变化的共同胁迫使得高密度城市面临多重生态风险,包括城市热岛、洪涝灾害与空气污染等,这些生态问题不仅影响城市生态系统的稳定性,同时威胁人类福祉。因此,亟需对全球高密度城市的生态问题与应对策略开展研究。以Web of Science和Scopus为文献检索数据源,通过系统性分析258篇文献揭示全球高密度城市生态问题的研究特征。首先,对全球高密度城市关键生态问题的数量分布与地理空间分布特征进行分析;其次,对三大生态问题的影响因素与尺度差异进行讨论,并提出城区与场地尺度下生态问题的应对策略;最后,研究表明城市三维形态、立体生态空间是未来生态问题的重点。研究结论表明:(1)亚洲地区对高密度城市生态问题关注度最高,城市热岛是全球高密度城市研究的热点问题;(2)景观格局特征与建成环境特征是城市热岛与洪涝的重要影响因素,生物物理特征与建成环境特征是空气污染的重要影响因素;(3)优化城市景观构成与空间配置可缓解高密度城市生态问题。研究结果为高密度城市开展生态研究与应对生态风险提供了重要启发。展开更多
基金supported by the National Natural Science Foundation of China(61271250)
文摘The backtracking search optimization algorithm（BSA） is one of the most recently proposed population-based evolutionary algorithms for global optimization. Due to its memory ability and simple structure, BSA has powerful capability to find global optimal solutions. However, the algorithm is still insufficient in balancing the exploration and the exploitation. Therefore, an improved adaptive backtracking search optimization algorithm combined with modified Hooke-Jeeves pattern search is proposed for numerical global optimization. It has two main parts： the BSA is used for the exploration phase and the modified pattern search method completes the exploitation phase. In particular, a simple but effective strategy of adapting one of BSA＇s important control parameters is introduced. The proposed algorithm is compared with standard BSA, three state-of-the-art evolutionary algorithms and three superior algorithms in IEEE Congress on Evolutionary Computation 2014（IEEE CEC2014） over six widely-used benchmarks and 22 real-parameter single objective numerical optimization benchmarks in IEEE CEC2014. The results of experiment and statistical analysis demonstrate the effectiveness and efficiency of the proposed algorithm.
文摘As conventional methods for beam pattern synthesis can not always obtain the desired optimum pattern for the arbitrary underwater acoustic sensor arrays,a hybrid numerical synthesis method based on adaptive principle and genetic algorithm was presented in this paper.First,based on the adaptive theory,a given array was supposed as an adaptive array and its sidelobes were reduced by assigning a number of interference signals in the sidelobe region.An initial beam pattern was obtained after several iterations and adjustments of the interference intensity,and based on its parameters,a desired pattern was created.Then,an objective function based on the difference between the designed and desired patterns can be constructed.The pattern can be optimized by using the genetic algorithm to minimize the objective function.A design example for a double-circular array demonstrates the effectiveness of this method.Compared with the approaches existing before,the proposed method can reduce the sidelobe effectively and achieve less synthesis magnitude error in the mainlobe.The method can search for optimum attainable pattern for the specific elements if the desired pattern can not be found.
基金supported by Project of the National Natural Science Foundation of China(Grant No.62073256)in part by Shaanxi Provincial Science and Technology Department(Grant No.2020GY-125)。
文摘In order to improve the recognition rate and accuracy rate of projectiles in six sky-screens intersection test system,this work proposes a new recognition method of projectiles by combining particle swarm optimization support vector and spatial-temporal constrain of six sky-screens detection sensor.Based on the measurement principle of the six sky-screens intersection test system and the characteristics of the output signal of the sky-screen,we analyze the existing problems regarding the recognition of projectiles.In order to optimize the projectile recognition effect,we use the support vector machine and basic particle swarm algorithm to form a new recognition algorithm.We set up the particle swarm algorithm optimization support vector projectile information recognition model that conforms to the six sky-screens intersection test system.We also construct a spatial-temporal constrain matching model based on the spatial geometric relationship of six sky-screen intersection,and form a new projectile signal recognition algorithm with six sky-screens spatial-temporal information constraints under the signal classification mechanism of particle swarm optimization algorithm support vector machine.Based on experiments,we obtain the optimal penalty and kernel function radius parameters in the PSO-SVM algorithm;we adjust the parameters of the support vector machine model,train the test signal data of every sky-screen,and gain the projectile signal classification results.Afterwards,according to the signal classification results,we calculate the coordinate parameters of the real projectile by using the spatial-temporal constrain of six sky-screens detection sensor,which verifies the feasibility of the proposed algorithm.
文摘An artificial intelligence technique was applied to the optimization of flux adding systems and air blasting systems, the display of on line parameters, forecasting of mass and compositions of slag in the slagging period, optimization of cold material adding systems and air blasting systems, the display of on line parameters, and the forecasting of copper mass in the copper blow period in copper smelting converters. They were integrated to build the Intelligent Decision Support System of the Operation Optimization of Copper Smelting Converter(IDSSOOCSC), which is self learning and self adaptating. Development steps, monoblock structure and basic functions of the IDSSOOCSC were introduced. After it was applied in a copper smelting converter, every production quota was clearly improved after IDSSOOCSC had been run for 4 months. Blister copper productivity is increased by 6%, processing load of cold input is increased by 8% and average converter life span is improved from 213 to 235 furnace times.
文摘In this paper, a new amplitude quantization synthesis method for ultralow sidelobe phased arrays is proposed, which is based on the constrained nonlinear optimization algorithm. By introducing a set of critical constraint conditions into the optimization model, we can directly quantize the amplitude distribution instead of replacing it with a continuous equivalent aperture antenna. The mutual coupling and the element patterns are also considered in the quantization synthesis. Finally, some array simulation results are given to show the effectiveness of the method.
基金supported by the Key Foundation of Southwest University for Nationalities(09NZD001).
文摘Many difficult engineering problems cannot be solved by the conventional optimization techniques in practice. Direct searches that need no recourse to explicit derivatives are revived and become popular since the new century. In order to get a deep insight into this field, some notes on the direct searches for non-smooth optimization problems are made. The global convergence vs. local convergence and their influences on expected solutions for simulation-based stochastic optimization are pointed out. The sufficient and simple decrease criteria for step acceptance are analyzed, and why simple decrease is enough for globalization in direct searches is identified. The reason to introduce the positive spanning set and its usage in direct searches is explained. Other topics such as the generalization of direct searches to bound, linear and non-linear constraints are also briefly discussed.
文摘快速城市化与气候变化的共同胁迫使得高密度城市面临多重生态风险,包括城市热岛、洪涝灾害与空气污染等,这些生态问题不仅影响城市生态系统的稳定性,同时威胁人类福祉。因此,亟需对全球高密度城市的生态问题与应对策略开展研究。以Web of Science和Scopus为文献检索数据源,通过系统性分析258篇文献揭示全球高密度城市生态问题的研究特征。首先,对全球高密度城市关键生态问题的数量分布与地理空间分布特征进行分析;其次,对三大生态问题的影响因素与尺度差异进行讨论,并提出城区与场地尺度下生态问题的应对策略;最后,研究表明城市三维形态、立体生态空间是未来生态问题的重点。研究结论表明:(1)亚洲地区对高密度城市生态问题关注度最高,城市热岛是全球高密度城市研究的热点问题;(2)景观格局特征与建成环境特征是城市热岛与洪涝的重要影响因素,生物物理特征与建成环境特征是空气污染的重要影响因素;(3)优化城市景观构成与空间配置可缓解高密度城市生态问题。研究结果为高密度城市开展生态研究与应对生态风险提供了重要启发。
