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Combining trust region and linesearch algorithm for equality constrained optimization
Zhensheng Yu,Changyu Wang,Jiguo Yu 한국전산응용수학회 2004 Journal of applied mathematics & informatics Vol.14 No.-
In this paper, a combining trust region and line search algorithm for equality constrained optimization is proposed. At each iteration, we only need to solve the trust region subproblem once, when the trust region trial step can not be accepted, we switch to line search to obtain the next iteration. Hence, the difficulty of repeated solving trust region subproblem in an iterate is avoided. In order to allow the direction of negative curvature, we add second correction step in trust region step and employ nonmonotone technique in line search. The global convergence and local superlinearly rate are established under certain assumptions. Some numerical examples are given to illustrate the efficiency of the proposed algorithm.
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COMBINING TRUST REGION AND LINESEARCH ALGORITHM FOR EQUALITY CONSTRAINED OPTIMIZATION
Yu, Zhensheng,Wang, Changyu,Yu, Jiguo 한국전산응용수학회 2004 Journal of applied mathematics & informatics Vol.14 No.1
In this paper, a combining trust region and line search algorithm for equality constrained optimization is proposed. At each iteration, we only need to solve the trust region subproblem once, when the trust region trial step can not be accepted, we switch to line search to obtain the next iteration. Hence, the difficulty of repeated solving trust region subproblem in an iterate is avoided. In order to allow the direction of negative curvature, we add second correction step in trust region step and employ nonmonotone technique in line search. The global convergence and local superlinearly rate are established under certain assumptions. Some numerical examples are given to illustrate the efficiency of the proposed algorithm.
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Tissue distribution of marbofloxacin in pigs after a single intramuscular injection
Fan Yang,Yiming Liu,Zhili Li,Yuqin Wang,Baobao Liu,Zhensheng Zhao,Bianhua Zhou,Guoyong Wang 대한수의학회 2017 Journal of Veterinary Science Vol.18 No.2
Tissue distribution of marbofloxacin was studied in pigs after a single intramuscular injection at 2.5 mg/kg body weight. Samples of plasma, muscle, liver, kidney, heart, lung, and muscle at the injection site were randomly collected from five pigs at 2, 6, 10, 24, 48, 72, and 96 h after administration. Marbofloxacin concentrations were determined by using high-performance liquid chromatography with ultraviolet detection and were subjected to non-compartmental analysis to obtain kinetic parameters. The elimination half-life (t1/2lz) of marbofloxacin at the injection site was 22.12 h, while those in kidney, plasma, liver, lung, heart, and muscle were 16.75, 21.48, 21.84, 24.00, 24.45, and 28.91 h, respectively. Areas under the concentration-time curve from 0 h to ∞ (AUC0–∞s) were calculated to be 31.17 hㆍmgㆍmL−1 for plasma and 32.97, 33.92, 34.78, 37.58, 42.02, and 98.80 hㆍmgㆍg−1 for heart, muscle, lung, liver, kidney, and injection site, respectively. The peak concentration (Cmax) of marbofloxacin was 1.62 µg/mL in plasma and 1.71, 1.74, 1.86, 1.93, 2.45, and 7.64 µg/g in heart, lung, muscle, kidney, liver, and injection site, respectively. The results show that marbofloxacin was fast absorbed, extensively distributed, and slowly eliminated from pigs after a single intramuscular administration.
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Chen Sifan,Chen Baihe,Shu Peng,Wang Zhensheng,Chen Chengbin 한국CDE학회 2023 Journal of computational design and engineering Vol.10 No.1
In recent years, unmanned aerial vehicle (UAV) autonomous flight technology has been applied in many fields. However, in the process of autonomous operation, the UAV may deviate from the set flight path due to various disturbance factors, which results in mission failure. In order to find the abnormal situation in time and take corresponding measures, it is necessary to monitor the operation state of the UAV. Predicting the UAV flight path is the main monitoring method at present; however, the accuracy and real-time of the existing prediction methods are limited. Therefore, this paper proposes an error compensation Bessel bidirectional long short-term memory real-time path prediction model deployed in ground stations. First, because of inconsistency of the units in all directions of the original positioning information provided by global positioning system, the Bessel geodetic coordinate transformation is introduced to unify the units of three-dimensional coordinate data, so as to improve the prediction accuracy. Second, considering the problems of poor data quality and data missing in the operation process, the least square fitting method is used to supplement and correct the positioning coordinate data to obtain more reliable and accurate path observation values as the model input. Finally, a deep learning path prediction model based on bi-directional long short-term memory (BiLSTM) network is constructed, and the appropriate network parameters are determined with the prediction accuracy and time as evaluation indicators. In order to further improve the prediction accuracy, a compensator based on proportional integral differential error control theory is designed according to the output characteristics of the BiLSTM network, which is used for providing compensation values for the prediction results of the model. The training and testing results using the actual flight data of UAV operation show that, under the experimental environment built, the model proposed in this paper can complete the UAV flight path prediction with root mean square error < 1 meter within 0.1 second, and has better performance and higher prediction accuracy than other neural network models.
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