scholarly journals Research on Hyperbola Fitting Algorithm for Turbulence Level Measurement Test Data

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Yufeng Du ◽  
Long Wu ◽  
Xunnian Wang ◽  
Jun Lin ◽  
Neng Xiong
Keyword(s):  
Test Data ◽  
Optimization Problem ◽  
Flow Characteristics ◽  
Wind Tunnels ◽  
Turbulence Level ◽  
Constrained Optimization Problem ◽  
Level Measurement ◽  
Fitting Algorithm ◽  
The Stability ◽  
Fitting Parameters

Hyperbola fitting of test data is an extremely important process in turbulence level measurement test in wind tunnels. The solution of the overdetermined equations (SOE) method is often used to solve hyperbola fitting parameters to obtain turbulence level. However, due to unsteady flow characteristics, the SOE method often results in overfitting phenomena, which makes it impossible to solve turbulence level accurately. This paper proposes using the constrained least-squares (CLS) method to convert the problem of hyperbola fitting of test data into the inequality constrained optimization problem and then using the Lagrange programming neural network (LPNN) method to solve turbulence level iteratively. The stability of the LPNN method is analysed, and three sets of typical turbulence level measurement test data are processed using the LPNN method. The results verify the feasibility of applying the LPNN method to iteratively solve the turbulence level of wind tunnels.

scholarly journals MODERN MONETARY CIRCUIT THEORY, STABILITY OF INTERCONNECTED BANKING NETWORK, AND BALANCE SHEET OPTIMIZATION FOR INDIVIDUAL BANKS

2016 ◽  
Vol 19 (06) ◽  
pp. 1650034 ◽  
Author(s):  
ALEXANDER LIPTON
Keyword(s):  
Optimization Problem ◽  
Balance Sheet ◽  
Banking System ◽  
Circuit Theory ◽  
Bank Capital ◽  
Constrained Optimization Problem ◽  
Money Creation ◽  
The Stability ◽  
Monetary Circuit

A modern version of monetary circuit theory with a particular emphasis on stochastic underpinning mechanisms is developed. It is explained how money is created by the banking system as a whole and by individual banks. The role of central banks as system stabilizers and liquidity providers is elucidated. It is shown how in the process of money creation banks become naturally interconnected. A novel extended structural default model describing the stability of the Interconnected banking network is proposed. The purpose of bank capital and liquidity is explained. Multi-period constrained optimization problem for bank balance sheet is formulated and solved in a simple case. Both theoretical and practical aspects are covered.

scholarly journals Transmission Scheduling Schemes of Industrial Wireless Sensors for Heterogeneous Multiple Control Systems

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4284 ◽  
Author(s):  
Bongsang Park ◽  
Junghyo Nah ◽  
Jang-Young Choi ◽  
Ick-Jae Yoon ◽  
Pangun Park
Keyword(s):  
Constrained Optimization ◽  
Control Systems ◽  
Optimization Problem ◽  
Random Access ◽  
Transmission Scheduling ◽  
Constrained Optimization Problem ◽  
Multiple Control ◽  
Scheduling Scheme ◽  
Control Stability ◽  
The Stability

The transmission scheduling scheme of wireless networks for industrial control systems is a crucial design component since it directly affects the stability of networked control systems. In this paper, we propose a novel transmission scheduling framework to guarantee the stability of heterogeneous multiple control systems over unreliable wireless channels. Based on the explicit control stability conditions, a constrained optimization problem is proposed to maximize the minimum slack of the stability constraint for the heterogeneous control systems. We propose three transmission scheduling schemes, namely centralized stationary random access, distributed random access, and Lyapunov-based scheduling scheme, to solve the constrained optimization problem with a low computation cost. The three proposed transmission scheduling schemes were evaluated on heterogeneous multiple control systems with different link conditions. One interesting finding is that the proposed centralized Lyapunov-based approach provides almost ideal performance in the context of control stability. Furthermore, the distributed random access is still useful for the small number of links since it also reduces the operational overhead without significantly sacrificing the control performance.

scholarly journals Latency-Optimal Computational Offloading Strategy for Sensitive Tasks in Smart Homes

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2347
Author(s):  
Yanyan Wang ◽  
Lin Wang ◽  
Ruijuan Zheng ◽  
Xuhui Zhao ◽  
Muhua Liu
Keyword(s):  
Queue Length ◽  
Optimization Problem ◽  
Time Slot ◽  
Smart Homes ◽  
Back Pressure ◽  
Smart Devices ◽  
Smart Device ◽  
Simulation Results ◽  
Computational Offloading ◽  
The Stability

In smart homes, the computational offloading technology of edge cloud computing (ECC) can effectively deal with the large amount of computation generated by smart devices. In this paper, we propose a computational offloading strategy for minimizing delay based on the back-pressure algorithm (BMDCO) to get the offloading decision and the number of tasks that can be offloaded. Specifically, we first construct a system with multiple local smart device task queues and multiple edge processor task queues. Then, we formulate an offloading strategy to minimize the queue length of tasks in each time slot by minimizing the Lyapunov drift optimization problem, so as to realize the stability of queues and improve the offloading performance. In addition, we give a theoretical analysis on the stability of the BMDCO algorithm by deducing the upper bound of all queues in this system. The simulation results show the stability of the proposed algorithm, and demonstrate that the BMDCO algorithm is superior to other alternatives. Compared with other algorithms, this algorithm can effectively reduce the computation delay.

scholarly journals Nonconvex constrained optimization by a filtering branch and bound

2020 ◽  
Author(s):  
Gabriele Eichfelder ◽  
Kathrin Klamroth ◽  
Julia Niebling
Keyword(s):  
Constrained Optimization ◽  
Optimization Problem ◽  
Feasible Solution ◽  
Constrained Optimization Problem ◽  
Numerical Tests ◽  
Nonconvex Constrained Optimization ◽  
Objective Value ◽  
Feasible Solutions ◽  
Quality Guarantee ◽  
Single Objective

AbstractA major difficulty in optimization with nonconvex constraints is to find feasible solutions. As simple examples show, the $$\alpha $$ α BB-algorithm for single-objective optimization may fail to compute feasible solutions even though this algorithm is a popular method in global optimization. In this work, we introduce a filtering approach motivated by a multiobjective reformulation of the constrained optimization problem. Moreover, the multiobjective reformulation enables to identify the trade-off between constraint satisfaction and objective value which is also reflected in the quality guarantee. Numerical tests validate that we indeed can find feasible and often optimal solutions where the classical single-objective $$\alpha $$ α BB method fails, i.e., it terminates without ever finding a feasible solution.

Test Data Generation and Selection Using Levy Flight-Based Firefly Algorithm

2021 ◽  
Vol 9 (2) ◽  
pp. 18-34
Author(s):  
Abhishek Pandey ◽  
Soumya Banerjee
Keyword(s):  
Test Data ◽  
Firefly Algorithm ◽  
Optimization Problem ◽  
Structural Testing ◽  
Software Test ◽  
Testing Time ◽  
Test Data Generation ◽  
Data Generation ◽  
Test Suite Optimization ◽  
Test Optimization

This article discusses the application of an improved version of the firefly algorithm for the test suite optimization problem. Software test optimization refers to optimizing test data generation and selection for structural testing criteria for white box testing. This will subsequently reduce the two most costly activities performed during testing: time and cost. Recently, various search-based approaches proved very interesting results for the software test optimization problem. Also, due to no free lunch theorem, scientists are continuously searching for more efficient and convergent methods for the optimization problem. In this paper, firefly algorithm is modified in a way that local search ability is improved. Levy flights are incorporated into the firefly algorithm. This modified algorithm is applied to the software test optimization problem. This is the first application of Levy-based firefly algorithm for software test optimization. Results are shown and compared with some existing metaheuristic approaches.

Segmentation of Certificate With Connected Component Labeling Method

2020 ◽  
Vol 8 (2) ◽  
pp. 119
Author(s):  
Cokorda Gde Teresna Jaya ◽  
I Gede Arta Wibawa
Keyword(s):  
Test Data ◽  
Optimization Problem ◽  
Initial Step ◽  
Connected Component ◽  
Important Data ◽  
Connected Component Labeling ◽  
Time Optimization ◽  
Segmentation Process ◽  
Verification Process ◽  
Labeling Method

Certificate is one of the documents that can be used as evidence of ownership or an event. For example, when certificate used as requirement to participate in an event. If a document is made as a requirement, of course the file verification process will be done. Seeing the time optimization problem when verifying the file, the authors carry out research by segmenting important data contained in a certificate as an initial step in the development of an automatic document verification system. The segmentation process carried out in this study uses the Connected Component Labeling method in determining the area to be segmented and Automatic Cropping to cut the results of the segmentation process. By using these two methods obtained an accuracy of 60% with a total of 15 pieces of test data

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