scholarly journals A New Feature Selection Method for Hyperspectral Image Classification Based on Simulated Annealing Genetic Algorithm and Choquet Fuzzy Integral

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Hongmin Gao ◽  
Lizhong Xu ◽  
Chenming Li ◽  
Aiye Shi ◽  
Fengchen Huang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Feature Selection ◽  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Hyperspectral Image ◽  
Selection Method ◽  
Hyperspectral Images ◽  
Fuzzy Integral ◽  
High Dimensions ◽  
Simulated Annealing Genetic Algorithm

Hyperspectral remote sensing technology is a rapidly developing new integrated technology that is widely used in numerous areas. Rich spectral information from hyperspectral images can aid in the classification and recognition of the ground objects. However, the high dimensions of hyperspectral images cause redundancy in information. Hence, the high dimensions of hyperspectral data must be reduced. This paper proposes a hybrid feature selection strategy based on the simulated annealing genetic algorithm (SAGA) and the Choquet fuzzy integral (CFI). The band selection method is proposed from subspace decomposition, which combines the simulated annealing algorithm with the genetic algorithm in choosing different cross-over and mutation probabilities, as well as mutation individuals. Then, the selecting bands are further refined by CFI. Experimental results show that the proposed method can achieve higher classification accuracy than traditional methods.

GMDH Network Model Based on Simulated Annealing and Genetic Algorithm

2013 ◽  
Vol 380-384 ◽  
pp. 1370-1373
Author(s):  
Xiao Ling Zhang ◽  
Li Kun Zou
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Network Model ◽  
Simulated Annealing Algorithm ◽  
Least Square Method ◽  
Least Square ◽  
Model Based ◽  
Simulated Annealing Genetic Algorithm ◽  
Global And Local ◽  
Combined Algorithm

According to the traditional UMDH network modeling with the least square method to recognize parameters ,it's easy to fall into local minimum ,and with the result that the prediction effect is not ideal. This paper puts forward to combine the simulated annealing algorithm and genetic algorithm, and introduces the combined algorithm to the UMDH network which is used to identify some of its description type coefficient. In this paper ,it describes the simulated annealing genetic algorithm ,and constructs the UMDH network model based on this algorithm, and the model is applied to the simulation of debris flow prediction research ,forecast average relative error reached 3. 54%. The results show that the algorithm not only ensuring the global optimization but also preventing premature convergence, improve the UMDH network model of global and local searching optimal ability further.

A Novel Camera Calibration Method Based on Simulated Annealing Genetic Algorithm

2015 ◽  
Vol 719-720 ◽  
pp. 1184-1190
Author(s):  
Shuang Ran ◽  
Long Ye ◽  
Jing Ling Wang ◽  
Qin Zhang
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Camera Calibration ◽  
Simulated Annealing Algorithm ◽  
Image Plane ◽  
Calibration Method ◽  
Simulated Annealing Genetic Algorithm ◽  
Extrinsic Parameters ◽  
Annealing Algorithm ◽  
Intrinsic And Extrinsic Parameters

The optimization of the camera’s intrinsic and extrinsic parameters is a key step after obtaining the initialized parameters’ state by considering the homography between the board space plane and the image plane in Zhengyou Zhang method. In this paper, we proposed a camera calibration optimization algorithm by adopting genetic algorithm and the simulated annealing algorithm. The experiment results demonstrate that our algorithm can improve the precision of the camera calibration to a certain extent.

Analysis on Factors Affecting the Employment of Landless Peasants Based on Simulated Annealing Genetic Algorithm

2014 ◽  
Vol 533 ◽  
pp. 536-543
Author(s):  
Zhong Hao Zhu
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Vulnerable Groups ◽  
National Plan ◽  
Land Expropriation ◽  
Factors Affecting ◽  
Simulated Annealing Genetic Algorithm ◽  
Process Of Urbanization ◽  
Annealing Algorithm

In national plan of twelfth five-year, orchestrating city-country development and accelerating process of urbanization will be one of the leading strategies. Large areas of farmland turn to non-agricultural irreversibly in the process of accelerating urbanization, the existing land expropriation system running by planned economic system damage farmers’ rights and incomes. Therefore, as vulnerable groups, landless peasants’ employments need more concern. The study takes Zhenjiang city for an example, proposes a factor selecting method based on the simulated annealing genetic algorithm (SAGA). The factor selecting method is proposed from each subspace, which combines the simulated annealing algorithm with the genetic algorithm in choosing different cross-over and mutation probabilities, as well as mutation individuals. Experimental results show that achieving a significant increase in the employment rate is possible using SAGA obtained from the proposed approach.

scholarly journals A novel edge server selection method based on combined genetic algorithm and simulated annealing algorithm

Automatika ◽  
2020 ◽  
Vol 62 (1) ◽  
pp. 32-43
Author(s):  
Yi-wen Zhang ◽  
Wen-ming Zhang ◽  
Kai Peng ◽  
Deng-cheng Yan ◽  
Qi-lin Wu
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Selection Method ◽  
Server Selection ◽  
Annealing Algorithm
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