Optimal design of channel cross-section is an important task in the hydraulic design of open channels. The traditional methods and models which neglect the frost heave are trial procedures and may result in failure of...
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Optimal design of channel cross-section is an important task in the hydraulic design of open channels. The traditional methods and models which neglect the frost heave are trial procedures and may result in failure of channels in design of irrigation channels. To improve the total cost, reliability and effectiveness, the model which is used in this study, is not only minimizing the cost of land acquisition but also the cost of concrete lining considering cost as the objective function. The constrained optimization model which considers values of thickness of channel concrete slab constraint simultaneously along with the objective of minimization of cost is propounded and solved using a recent global optimization technique, namely catswarmoptimization (CSO). The optimized channel section not only satisfies the optimal hydraulic cross-section but guarantees the safety and stability of the side walls so that both the amount of the concrete lining and the land acquisition are optimized. Finally, we take a main channel of Qinghe Irrigated Area of Farm 853 in Heilongjiang Province as a study area. The results obtained using the CSO approach are satisfaction and the method can be used for reliable design of artificial open channels. Furthermore, we compare the CSO algorithm with a genetic algorithm (GA) and the particle swarmoptimization (PSO) to verify the effectiveness of the catswarmalgorithm in the channel section optimization.
In view of solving multi-objective path planning in the static environment, there are some faults for ant colony optimization(ACO), such as the long computation and easy to fall into local optimum. To solve these prob...
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ISBN:
(纸本)9781467399043
In view of solving multi-objective path planning in the static environment, there are some faults for ant colony optimization(ACO), such as the long computation and easy to fall into local optimum. To solve these problems, the ACO based on catswarmoptimization (CSO) algorithm searching model (CSOACO) is presented. In this algorithm, the introduction of CSO algorithm search pattern realizes the local search in the current solution for ant colony individuals, which not only enrich the diversity of solution, but improve the accuracy of the algorithm. Finally, the new algorithm is simulated in MATLAB for picking robot multi-objective path planning problem. Through the simulation analysis, not only set the parameters, but compare CSOACO with other algorithms. Simulation results show that the algorithm can accelerate the convergence speed, search to the global optimal solution and realize the multi-objective path planning of picking robot.
In view of solving multi-objective path planning in the static environment,there are some faults for ant colony optimization(ACO),such as the long computation and easy to fall into local *** solve these problems,the A...
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In view of solving multi-objective path planning in the static environment,there are some faults for ant colony optimization(ACO),such as the long computation and easy to fall into local *** solve these problems,the ACO based on catswarmoptimization(CSO) algorithm searching model(CSOACO) is *** this algorithm,the introduction of CSO algorithm search pattern realizes the local search in the current solution for ant colony individuals,which not only enrich the diversity of solution,but improve the accuracy of the ***,the new algorithm is simulated in MATLAB for picking robot multi-objective path planning *** the simulation analysis,not only set the parameters,but compare CSOACO with other *** results show that the algorithm can accelerate the convergence speed,search to the global optimal solution and realize the multiobjective path planning of picking robot.
Low frequency oscillations are observed when large power systems are interconnected by relatively weak tie-lines. Power System Stabilizers (PSS) are incorporated in the excitation system of the generators to enhance d...
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ISBN:
(纸本)9781479976782
Low frequency oscillations are observed when large power systems are interconnected by relatively weak tie-lines. Power System Stabilizers (PSS) are incorporated in the excitation system of the generators to enhance damping of these low frequency oscillations. In this paper, the design of multiple PSS in a multi-machine power system (MMPS) using catswarmoptimization (CSO) algorithm has been proposed. The design problem of the PSS has been formulated as an optimization problem and CSO has been employed to search for optimal controller parameters. It has been shown that the stability performance of the system can be improved by minimizing the eigenvalue based objective function comprising of the damping factor and the damping ratio of the poorly damped electromechanical modes. Eigenvalue analysis and nonlinear simulation results have also been presented for various loading conditions and system configurations to show the effectiveness and robustness of the proposed controllers and their ability to provide efficient damping of low frequency oscillations.
Embedding secret data into a cover image using simple least-significant-bit substitution can degrade the image quality dramatically, especially when a large number of bits are substituted. The exhaustive least-signifi...
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Embedding secret data into a cover image using simple least-significant-bit substitution can degrade the image quality dramatically, especially when a large number of bits are substituted. The exhaustive least-significant-bit substitution method is proposed to solve this problem. However, the idea has no practical application due to its long computation time. This paper adopts the catswarmoptimization (CSO) strategy to obtain the optimal or near optimal solution of the stego-image quality problem. The CSO strategy is generated by observing the behavior of cats, which has been proved to achieve better performance on finding the best global solutions. We revised the CSO strategy in our proposed scheme to make it practicable and suitable to solve the mentioned problem. The experimental results show that the proposed scheme can obtain a better solution with less computation time. (C) 2010 Elsevier Inc. All rights reserved.
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