A Hybrid Optimization Method for Image Classification with Gravitational Search Algorithm

Shengsheng Wang; Bolou Bolou Dickson; Weilie Wang; Dong Liu; Long Feng

首页> 外文期刊>Journal of information and computational science >A Hybrid Optimization Method for Image Classification with Gravitational Search Algorithm

【24h】

A Hybrid Optimization Method for Image Classification with Gravitational Search Algorithm

机译：引力搜索算法的图像分类混合优化方法

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

For image classification systems, choosing the relevant image features and the parameters of classifier are the most important factors. However, previous systems focused on only one factor. The accuracy of image classification can be further improved if we consider these two factors together. The proposed algorithm combined gravitational search algorithm in feature extraction and almost simultaneously selecting the relevant features by quantum-binary gravitational search algorithm. It incorporates support vector machine to find a hyper-plane that yields the minimum number of errors in the process, keeping the constraint violation very low. To ascertain the efficiency of the algorithm, a process of experiment was conducted on two datasets.

机译：对于图像分类系统，选择相关的图像特征和分类器的参数是最重要的因素。但是，以前的系统仅关注一个因素。如果我们综合考虑这两个因素，可以进一步提高图像分类的准确性。提出的算法结合了重力搜索算法进行特征提取，并通过量子二进制重力搜索算法几乎同时选择了相关特征。它结合了支持向量机，可以找到在过程中产生最少错误的超平面，从而使约束违规率保持在极低水平。为了确定算法的效率，对两个数据集进行了实验过程。

著录项

来源
《Journal of information and computational science》 |2014年第17期|6393-6400|共8页
作者
Shengsheng Wang; Bolou Bolou Dickson; Weilie Wang; Dong Liu; Long Feng;
展开▼
作者单位

College of Computer Science and Technology, Jilin University, Changchun 130012, China;

College of Computer Science and Technology, Jilin University, Changchun 130012, China;

College of Computer Science and Technology, Jilin University, Changchun 130012, China;

College of Computer Science and Technology, Jilin University, Changchun 130012, China;

College of Computer Science and Technology, Jilin University, Changchun 130012, China;

展开▼
收录信息
原文格式 PDF
正文语种 eng
中图分类
关键词
Parameter Optimization; Quantum-binary Gravitational Search; Support Vector Machine Classifier;

机译：参数优化;量子二进制引力搜索;支持向量机分类器;

相似文献

外文文献
中文文献
专利

1. Facing the classification of binary problems with a hybrid system based on quantum-inspired binary gravitational search algorithm and K-NN method [J] . XiaoHong Han, Long Quan, XiaoYan Xiong, Engineering Applications of Artificial Intelligence . 2013,第10期

机译：基于量子启发式二进制重力搜索算法和K-NN方法的混合系统面临的二进制问题分类
2. A new design method for adaptive IIR system identification using hybrid particle swarm optimization and gravitational search algorithm [J] . Jiang Shanhe, Wang Yan, Ji Zhicheng Nonlinear dynamics . 2015,第4期

机译：混合粒子群优化和引力搜索算法的自适应IIR系统辨识的新设计方法
3. A Hybrid Algorithm Based on Gravitational Search and Particle Swarm Optimization Algorithm to Solve Function Optimization Problems [J] . Jie-Sheng Wang, Jiang-Di Song Engineering Letters . 2017,第1期

机译：基于引力搜索和粒子群算法的混合算法求解功能优化问题
4. A prototype optimization method for nearest neighbor classification by gravitational search algorithm [C] . Rezaei Mohadeseh, Nezamabadi-pour Hossein 2014 Iranian Conference on Intelligent Systems . 2014

机译：利用引力搜索算法进行最近邻分类的原型优化方法
5. AN EFFICIENT HYBRID OPTIMIZATION METHOD AND ITS ROLE IN COMPUTER-AIDED DESIGN (OPTIMIZATION, STRUCTURAL SYSTEMS, ACTIVE SET, QUASI-NEWTON METHODS, HYBRID ALGORITHM) [D] . THANEDAR, PRAMOD BHALCHANDRA. 1985

机译：一种有效的混合优化方法及其在计算机辅助设计中的作用（优化，结构系统，主动集，准牛顿方法，混合算法）
6. The Hybrid Feature Selection Algorithm Based on Maximum Minimum Backward Selection Search Strategy for Liver Tissue Pathological Image Classification [O] . Huiling Liu, Huiyan Jiang, Ruiping Zheng 2016

机译：基于最大最小向后选择搜索策略的肝组织病理图像混合特征选择算法
7. Hybrid Multiverse Optimization Algorithm With Gravitational Search Algorithm for Multithreshold Color Image Segmentation [O] . Heming Jia, Xiaoxu Peng, Wenlong Song, 2019

机译：具有多线程彩色图像分割的引力搜索算法混合多层优化算法

A Hybrid Optimization Method for Image Classification with Gravitational Search Algorithm

摘要

著录项

相似文献

相关主题

期刊订阅