Fuzzy Segmentation Driven by Modified ABC Algorithm Using Cartilage Features Completed by Spatial Aggregation: Modeling of Early Cartilage Loss

2018 ◽  
pp. 479-488 ◽  
Author(s):  
Jan Kubicek ◽  
Iveta Bryjova ◽  
Marek Penhaker ◽  
David Oczka ◽  
Martin Augustynek ◽  
...  
Keyword(s):  
Spatial Aggregation ◽  
Cartilage Loss ◽  
Abc Algorithm ◽  
Fuzzy Segmentation

Family History, Smoking Promote Cartilage Loss

2007 ◽  
Vol 37 (17) ◽  
pp. 38
Author(s):  
Melinda Tanzola
Keyword(s):  
Family History ◽  
Cartilage Loss

Fuzzy segmentation of urban areas in panchromatic remote sensing images

2009 ◽  
Vol 28 (12) ◽  
pp. 3112-3115
Author(s):  
Yan CHEN ◽  
Shou-hong WAN ◽  
Yu-chang GONG
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Remote Sensing Images ◽  
Fuzzy Segmentation

A quasi-affine transformation artificial bee colony algorithm for global optimization

2021 ◽  
pp. 1-18
Author(s):  
Baohua Zhao ◽  
Tien-Wen Sung ◽  
Xin Zhang
Keyword(s):  
Affine Transformation ◽  
Artificial Bee Colony ◽  
Triangular Matrix ◽  
Convergence Speed ◽  
Test Set ◽  
Abc Algorithm ◽  
Bee Colony ◽  
Search Mechanism ◽  
Multiple Dimensions ◽  
Collaborative Search

The artificial bee colony (ABC) algorithm is one of the classical bioinspired swarm-based intelligence algorithms that has strong search ability, because of its special search mechanism, but its development ability is slightly insufficient and its convergence speed is slow. In view of its weak development ability and slow convergence speed, this paper proposes the QABC algorithm in which a new search equation is based on the idea of quasi-affine transformation, which greatly improves the cooperative ability between particles and enhances its exploitability. During the process of location updating, the convergence speed is accelerated by updating multiple dimensions instead of one dimension. Finally, in the overall search framework, a collaborative search matrix is introduced to update the position of particles. The collaborative search matrix is transformed from the lower triangular matrix, which not only ensures the randomness of the search, but also ensures its balance and integrity. To evaluate the performance of the QABC algorithm, CEC2013 test set and CEC2014 test set are used in the experiment. After comparing with the conventional ABC algorithm and some famous ABC variants, QABC algorithm is proved to be superior in efficiency, development ability, and robustness.

scholarly journals The Simulation Design of Microwave Absorption Performance for the Multi-Layered Carbon-Based Nanocomposites Using Intelligent Optimization Algorithm

Nanomaterials ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1951
Author(s):  
Danfeng Zhang ◽  
Congai Han ◽  
Haiyan Zhang ◽  
Bi Zeng ◽  
Yun Zheng ◽  
...  
Keyword(s):  
Layer Structure ◽  
Optimal Solution ◽  
Single Layer ◽  
Simulation Design ◽  
Wide Bandwidth ◽  
Abc Algorithm ◽  
Bee Colony ◽  
Absorbing Material ◽  
Important Means ◽  
Carbon Based

The optimal design objectives of the microwave absorbing (MA) materials are high absorption, wide bandwidth, light weight and thin thickness. However, it is difficult for single-layer MA materials to meet all of these requirements. Constructing multi-layer structure absorbing coating is an important means to improve performance of MA materials. The carbon-based nanocomposites are excellent MA materials. In this paper, genetic algorithm (GA) and artificial bee colony algorithm (ABC) are used to optimize the design of multi-layer materials. We selected ten kinds of materials to construct the multi-layer absorbing material and optimize the performance. Two algorithms were applied to optimize the two-layer MA material with a total thickness of 3 mm, and it was found that the optimal bandwidth was 8.12 GHz and reflectivity was −53.4 dB. When three layers of MA material with the same thickness are optimized, the ultra-wide bandwidth was 10.6 GHz and ultra-high reflectivity was −84.86 dB. The bandwidth and reflectivity of the optimized material are better than the single-layer material without optimization. Comparing the GA and the ABC algorithm, the ABC algorithm can obtain the optimal solution in the shortest time and highest efficiency. At present, no such results have been reported.

scholarly journals ESTIMATING BORDER EFFECTS:THE IMPACT OF SPATIAL AGGREGATION

2021 ◽  
Author(s):  
CLETUS C. COUGHLINAND ◽  
DENNIS NOVY
Keyword(s):  
Spatial Aggregation
Sign in / Sign up

Export Citation Format

Share Document