An Image Enhancement Optimization Method Based on Differential Evolution Algorithm and Cuckoo Search Through Serial Coupled Mode

We propose a new optimization algorithm inspired by the formation and change of the cloud in nature, referred to as Cloud Particles Differential Evolution (CPDE) algorithm. The cloud is assumed to have three states in the proposed algorithm. Gaseous state represents the global exploration. Liquid state represents the intermediate process from the global exploration to the local exploitation. Solid state represents the local exploitation. The best solution found so far acts as a nucleus. In gaseous state, the nucleus leads the population to explore by condensation operation. In liquid state, cloud particles carry out macrolocal exploitation by liquefaction operation. A new mutation strategy called cloud differential mutation is introduced in order to solve a problem that the misleading effect of a nucleus may cause the premature convergence. In solid state, cloud particles carry out microlocal exploitation by solidification operation. The effectiveness of the algorithm is validated upon different benchmark problems. The results have been compared with eight well-known optimization algorithms. The statistical analysis on performance evaluation of the different algorithms on 10 benchmark functions and CEC2013 problems indicates that CPDE attains good performance.

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Gray Level Image Enhancement by Improved Differential Evolution Algorithm

Advances in Intelligent Systems and Computing - Proceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012) ◽

10.1007/978-81-322-1041-2_38 ◽

2012 ◽

pp. 443-453

Author(s):

Pravesh Kumar ◽

Sushil Kumar ◽

Millie Pant

Keyword(s):

Differential Evolution ◽

Image Enhancement ◽

Differential Evolution Algorithm ◽

Gray Level ◽

Gray Level Image ◽

Evolution Algorithm ◽

Improved Differential Evolution Algorithm

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Optimization of FLADE Variable Cycle Engine Performance Based on Improved Differential Evolution Algorithm

Volume 1: Compressors, Fans and Pumps; Turbines; Heat Transfer; Combustion, Fuels and Emissions ◽

10.1115/gtindia2017-4771 ◽

2017 ◽

Author(s):

Zhang Xiao-bo ◽

Wang Zhan-xue

Keyword(s):

Differential Evolution ◽

Differential Evolution Algorithm ◽

Engine Performance ◽

Optimization Method ◽

Performance Simulation ◽

De Algorithm ◽

Civil Aircraft ◽

Evolution Algorithm ◽

Improved Differential Evolution Algorithm ◽

Integrated Performance

In this paper, a double bypass variable cycle engine with FLADE (Fan on Blade) is considered. The FLADE VCE is one of the research hotspots for future military and civil aircraft power device, which shows outstanding performance advantages. Compared to the mixed-flow turbofan, FLADE VCE is more complex than conventional aero-engine for its multi-components and multi-variable parts, which make it difficult to modeling and optimization. For getting the performance of FLADE VCE, the model for engine performance simulation is researched. The method for FLADE performance simulation and the steady-state performance simulation model for FLADE VCE are developed. And a component-based engine performance simulation system is established based on object-oriented modeling method. For obtaining the optimal integrated performance of FLADE VCE, suitable optimization method is required. Unfortunately, the optimization of FLADE VCE is a non-linear non-differentiable problem, which makes it difficult to solve by conventional deterministic optimization method. In order to solve this problem, the differential evolution (DE) algorithm is considered. To overcome the limitations of original DE algorithm, an improved DE algorithm with modifying mutation operator is proposed by this paper. The FLADE VCE optimization problem is solved by employing the improved DE algorithm.

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