This paper considers problems of the mathematical simulation of gas turbine engines and power plants.A program complex is presented which is capable of automatizing solutions of many problems concerning the theromo-ga...This paper considers problems of the mathematical simulation of gas turbine engines and power plants.A program complex is presented which is capable of automatizing solutions of many problems concerning the theromo-gas-dynamic calculation of the engine flow passage at the stages of design,development and service.A universal mathematical model is provided which real- izes all calculation for engines of different structure schemes (including test-bench) under different regimes.This program complex includes modules WHICGBH.It can solve problems of optimiza- tion,identification and diagnostics.Software is realized on the computer ES and PC(IBM PC). Kazan Aviation Institute K.Marx Str.10 Kazan 420111 Elousi,USSR展开更多
In this paper, based on the following theoretical framework: Evolutionary Algorithms + Program Structures = Automatic Programming , some results on complexity of automatic programming for function modeling is given, w...In this paper, based on the following theoretical framework: Evolutionary Algorithms + Program Structures = Automatic Programming , some results on complexity of automatic programming for function modeling is given, which show that the complexity of automatic programming is an exponential function of the problem dimension N , the size of operator set ｜F｜ and the height of the program parse tree H . Following this results, the difficulties of automatic programming are discussed. Some function models discovered automatically from database by evolutionary modeling method are given, too.展开更多
Unmanned aerial vehicles(UAVs) may play an important role in data collection and offloading in vast areas deploying wireless sensor networks, and the UAV’s action strategy has a vital influence on achieving applicabi...Unmanned aerial vehicles(UAVs) may play an important role in data collection and offloading in vast areas deploying wireless sensor networks, and the UAV’s action strategy has a vital influence on achieving applicability and computational complexity. Dynamic programming(DP) has a good application in the path planning of UAV, but there are problems in the applicability of special terrain environment and the complexity of the algorithm.Based on the analysis of DP, this paper proposes a hierarchical directional DP(DDP) algorithm based on direction determination and hierarchical model. We compare our methods with Q-learning and DP algorithm by experiments, and the results show that our method can improve the terrain applicability, meanwhile greatly reduce the computational complexity.展开更多
The existence of strongly polynomial algorithm for linear programming (LP) has been widely sought after for decades. Recently, a new approach called Gravity Sliding algorithm [1] has emerged. It is a gradient descendi...The existence of strongly polynomial algorithm for linear programming (LP) has been widely sought after for decades. Recently, a new approach called Gravity Sliding algorithm [1] has emerged. It is a gradient descending method whereby the descending trajectory slides along the inner surfaces of a polyhedron until it reaches the optimal point. In R3, a water droplet pulled by gravitational force traces the shortest path to descend to the lowest point. As the Gravity Sliding algorithm emulates the water droplet trajectory, it exhibits strongly polynomial behavior in R3. We believe that it could be a strongly polynomial algorithm for linear programming in Rn too. In fact, our algorithm can solve the Klee-Minty deformed cube problem in only two iterations, irrespective of the dimension of the cube. The core of gravity sliding algorithm is how to calculate the projection of the gravity vector g onto the intersection of a group of facets, which is disclosed in the same paper [1]. In this paper, we introduce a more efficient method to compute the gradient projections on complementary facets, and rename it the Sliding Gradient algorithm under the new projection calculation.展开更多
In this paper, the X-ray nondestructive test method of small defects in precision weldments with complex structure was presented. To resolve the difficulty of defect segmentation in variable grey image, the image proc...In this paper, the X-ray nondestructive test method of small defects in precision weldments with complex structure was presented. To resolve the difficulty of defect segmentation in variable grey image, the image processing based on Visual Basic programming method was adopted. The methods of automatic contrast and partial grey stretch were used to enhance the X-ray detection image which has relatively low contrast, then automatic threshold method was carried out to segment the two high intensity zones, and weld zones which contain the small defects was extracted. Smoothing and sharpen processing were proceeded on the extracted weld zones, and small defects in X-ray detection image of weldments with complex structure were segmented by using the method of background subtraction in the end. The effects of raster were eliminated, and because of that the image processing was only proceeded on the extracted weld zones, the calculated speed using the above provided algorithm was improved.展开更多
Based on the ideas of infeasible interior-point methods and predictor-corrector algorithms, two interior-point predictor-corrector algorithms for the second-order cone programming （SOCP） are presented. The two algor...Based on the ideas of infeasible interior-point methods and predictor-corrector algorithms, two interior-point predictor-corrector algorithms for the second-order cone programming （SOCP） are presented. The two algorithms use the Newton direction and the Euler direction as the predictor directions, respectively. The corrector directions belong to the category of the Alizadeh-Haeberly-Overton （AHO） directions. These algorithms are suitable to the cases of feasible and infeasible interior iterative points. A simpler neighborhood of the central path for the SOCP is proposed, which is the pivotal difference from other interior-point predictor-corrector algorithms. Under some assumptions, the algorithms possess the global, linear, and quadratic convergence. The complexity bound O（rln（εo/ε）） is obtained, where r denotes the number of the second-order cones in the SOCP problem. The numerical results show that the proposed algorithms are effective.展开更多
文摘This paper considers problems of the mathematical simulation of gas turbine engines and power plants.A program complex is presented which is capable of automatizing solutions of many problems concerning the theromo-gas-dynamic calculation of the engine flow passage at the stages of design,development and service.A universal mathematical model is provided which real- izes all calculation for engines of different structure schemes (including test-bench) under different regimes.This program complex includes modules WHICGBH.It can solve problems of optimiza- tion,identification and diagnostics.Software is realized on the computer ES and PC(IBM PC). Kazan Aviation Institute K.Marx Str.10 Kazan 420111 Elousi,USSR
基金Supported by National Nature Science Foundation of China(6 0 0 730 4370 0 710 42 )
文摘In this paper, based on the following theoretical framework: Evolutionary Algorithms + Program Structures = Automatic Programming , some results on complexity of automatic programming for function modeling is given, which show that the complexity of automatic programming is an exponential function of the problem dimension N , the size of operator set ｜F｜ and the height of the program parse tree H . Following this results, the difficulties of automatic programming are discussed. Some function models discovered automatically from database by evolutionary modeling method are given, too.
基金supported by the National Natural Science Foundation of China(91648204 61601486)+1 种基金State Key Laboratory of High Performance Computing Project Fund(1502-02)Research Programs of National University of Defense Technology(ZDYYJCYJ140601)
文摘Unmanned aerial vehicles(UAVs) may play an important role in data collection and offloading in vast areas deploying wireless sensor networks, and the UAV’s action strategy has a vital influence on achieving applicability and computational complexity. Dynamic programming(DP) has a good application in the path planning of UAV, but there are problems in the applicability of special terrain environment and the complexity of the algorithm.Based on the analysis of DP, this paper proposes a hierarchical directional DP(DDP) algorithm based on direction determination and hierarchical model. We compare our methods with Q-learning and DP algorithm by experiments, and the results show that our method can improve the terrain applicability, meanwhile greatly reduce the computational complexity.
文摘The existence of strongly polynomial algorithm for linear programming (LP) has been widely sought after for decades. Recently, a new approach called Gravity Sliding algorithm [1] has emerged. It is a gradient descending method whereby the descending trajectory slides along the inner surfaces of a polyhedron until it reaches the optimal point. In R3, a water droplet pulled by gravitational force traces the shortest path to descend to the lowest point. As the Gravity Sliding algorithm emulates the water droplet trajectory, it exhibits strongly polynomial behavior in R3. We believe that it could be a strongly polynomial algorithm for linear programming in Rn too. In fact, our algorithm can solve the Klee-Minty deformed cube problem in only two iterations, irrespective of the dimension of the cube. The core of gravity sliding algorithm is how to calculate the projection of the gravity vector g onto the intersection of a group of facets, which is disclosed in the same paper [1]. In this paper, we introduce a more efficient method to compute the gradient projections on complementary facets, and rename it the Sliding Gradient algorithm under the new projection calculation.
文摘In this paper, the X-ray nondestructive test method of small defects in precision weldments with complex structure was presented. To resolve the difficulty of defect segmentation in variable grey image, the image processing based on Visual Basic programming method was adopted. The methods of automatic contrast and partial grey stretch were used to enhance the X-ray detection image which has relatively low contrast, then automatic threshold method was carried out to segment the two high intensity zones, and weld zones which contain the small defects was extracted. Smoothing and sharpen processing were proceeded on the extracted weld zones, and small defects in X-ray detection image of weldments with complex structure were segmented by using the method of background subtraction in the end. The effects of raster were eliminated, and because of that the image processing was only proceeded on the extracted weld zones, the calculated speed using the above provided algorithm was improved.
基金supported by the National Natural Science Foundation of China (Nos. 71061002 and 11071158)the Natural Science Foundation of Guangxi Province of China (Nos. 0832052 and 2010GXNSFB013047)
文摘Based on the ideas of infeasible interior-point methods and predictor-corrector algorithms, two interior-point predictor-corrector algorithms for the second-order cone programming （SOCP） are presented. The two algorithms use the Newton direction and the Euler direction as the predictor directions, respectively. The corrector directions belong to the category of the Alizadeh-Haeberly-Overton （AHO） directions. These algorithms are suitable to the cases of feasible and infeasible interior iterative points. A simpler neighborhood of the central path for the SOCP is proposed, which is the pivotal difference from other interior-point predictor-corrector algorithms. Under some assumptions, the algorithms possess the global, linear, and quadratic convergence. The complexity bound O（rln（εo/ε）） is obtained, where r denotes the number of the second-order cones in the SOCP problem. The numerical results show that the proposed algorithms are effective.
