The methods of moment and genetic algorithm (GA) are combined to optimize the Yagi Uda antenna array and Log periodic dipole antenna (LPDA) array. The element lengths and spacing are optimized for the Yagi Uda arra...The methods of moment and genetic algorithm (GA) are combined to optimize the Yagi Uda antenna array and Log periodic dipole antenna (LPDA) array. The element lengths and spacing are optimized for the Yagi Uda array; while the ratio factor of spacing to length as well as the ratio of length to diameter of the elements are optimized for LPDA array. The results show that the main parameters, such as gain and pattern, have been improved apparently; and the high back lobe level of LPDA can be reduced greatly, therefore, GA is a very competent method for optimizing the linear array as well as in other fields.展开更多
In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of faul...In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of fault sections is developed in the forward model and the message passing interface (MPI) approach is chosen to parallel the genetic algorithms by global sin-gle-population master-slave method (GPGAs). The proposed approach is applied to a sample system consisting of 28 sections, 84 protective relays and 40 circuit breakers. Simulation results show that the new model based on GPGAs can achieve very fast computation in online applications of large-scale power systems.展开更多
Performance parameter prediction technology is the core research content of aeroengine health management,and more and more machine learning algorithms have been applied in the field.Regularized extreme learning machin...Performance parameter prediction technology is the core research content of aeroengine health management,and more and more machine learning algorithms have been applied in the field.Regularized extreme learning machine(RELM)is one of them.However,the regularization parameter determination of RELM consumes computational resources,which makes it unsuitable in the field of aeroengine performance parameter prediction with a large amount of data.This paper uses the forward and backward segmentation(FBS)algorithms to improve the RELM performance,and introduces an adaptive step size determination method and an improved solution mechanism to obtain a new machine learning algorithm.While maintaining good generalization,the new algorithm is not sensitive to regularization parameters,which greatly saves computing resources.The experimental results on the public data sets prove the above conclusions.Finally,the new algorithm is applied to the prediction of aero-engine performance parameters,and the excellent prediction performance is achieved.展开更多
Objective： To evaluate the clinical efficacy and quality of life of combined warming needle and patented Chinese medicine for patients with irritable bowel syndrome （IBS） due to liver-qi stagnation with spleen defi...Objective： To evaluate the clinical efficacy and quality of life of combined warming needle and patented Chinese medicine for patients with irritable bowel syndrome （IBS） due to liver-qi stagnation with spleen deficiency. Method： Sixty IBS cases were randomized into a treatment or control group by single-blind method. Warming needles on Tianshu （ST 25） and Dachangshu （BL 25） combined with patented Chinese medicine were adopted for cases in the treatment group, whereas the patented Chinese medicine alone was adopted in the control group. Results： The therapeutic efficacies in the two groups did not show substantial differences. The main symptoms were significantly improved after the treatment （P〈0.01）. After 2 weeks of treatment, the cases in the treatment group obtained a better improvement than the control group （P〈0.01, P〈0.05） in the severity or frequency of abdominal pain, abdominal distension, restlessness, insomnia, anxiety, suspiciousness, and loose stools with a sense of incomplete emptying. The patient＇s quality of life was improved in both groups （P〈0.01）. Conclusion： Both treatment methods could improve the clinical symptoms and increase the patient＇s quality of life. The total effective rate in the treatment group was slightly higher than the control group. Also, the combined warming needle and Chinese herbs could improve the main symptoms in a faster way.展开更多
文摘The methods of moment and genetic algorithm (GA) are combined to optimize the Yagi Uda antenna array and Log periodic dipole antenna (LPDA) array. The element lengths and spacing are optimized for the Yagi Uda array; while the ratio factor of spacing to length as well as the ratio of length to diameter of the elements are optimized for LPDA array. The results show that the main parameters, such as gain and pattern, have been improved apparently; and the high back lobe level of LPDA can be reduced greatly, therefore, GA is a very competent method for optimizing the linear array as well as in other fields.
基金the National Natural Science Foundation of China (No. 50677062)the New Century Excellent Talents in Uni-versity of China (No. NCET-07-0745)the Natural Science Foundation of Zhejiang Province, China (No. R107062)
文摘In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of fault sections is developed in the forward model and the message passing interface (MPI) approach is chosen to parallel the genetic algorithms by global sin-gle-population master-slave method (GPGAs). The proposed approach is applied to a sample system consisting of 28 sections, 84 protective relays and 40 circuit breakers. Simulation results show that the new model based on GPGAs can achieve very fast computation in online applications of large-scale power systems.
文摘Performance parameter prediction technology is the core research content of aeroengine health management,and more and more machine learning algorithms have been applied in the field.Regularized extreme learning machine(RELM)is one of them.However,the regularization parameter determination of RELM consumes computational resources,which makes it unsuitable in the field of aeroengine performance parameter prediction with a large amount of data.This paper uses the forward and backward segmentation(FBS)algorithms to improve the RELM performance,and introduces an adaptive step size determination method and an improved solution mechanism to obtain a new machine learning algorithm.While maintaining good generalization,the new algorithm is not sensitive to regularization parameters,which greatly saves computing resources.The experimental results on the public data sets prove the above conclusions.Finally,the new algorithm is applied to the prediction of aero-engine performance parameters,and the excellent prediction performance is achieved.
文摘Objective： To evaluate the clinical efficacy and quality of life of combined warming needle and patented Chinese medicine for patients with irritable bowel syndrome （IBS） due to liver-qi stagnation with spleen deficiency. Method： Sixty IBS cases were randomized into a treatment or control group by single-blind method. Warming needles on Tianshu （ST 25） and Dachangshu （BL 25） combined with patented Chinese medicine were adopted for cases in the treatment group, whereas the patented Chinese medicine alone was adopted in the control group. Results： The therapeutic efficacies in the two groups did not show substantial differences. The main symptoms were significantly improved after the treatment （P〈0.01）. After 2 weeks of treatment, the cases in the treatment group obtained a better improvement than the control group （P〈0.01, P〈0.05） in the severity or frequency of abdominal pain, abdominal distension, restlessness, insomnia, anxiety, suspiciousness, and loose stools with a sense of incomplete emptying. The patient＇s quality of life was improved in both groups （P〈0.01）. Conclusion： Both treatment methods could improve the clinical symptoms and increase the patient＇s quality of life. The total effective rate in the treatment group was slightly higher than the control group. Also, the combined warming needle and Chinese herbs could improve the main symptoms in a faster way.
