A New Spacecraft Impact Damage Feature Extraction Algorithm Based on Dynamic Multi-Objective Optimization Method

2019 ◽  
Author(s):  
Ting Xue ◽  
Chun Yin ◽  
Xuegang Huang ◽  
Sara Dadras ◽  
Yuhua Cheng ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Impact Damage ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Feature Extraction Algorithm ◽  
Extraction Algorithm

scholarly journals Automatically extracting features for face classification using multi-objective genetic programming

2021 ◽  
Author(s):  
Ying Bi ◽  
Bing Xue ◽  
Mengjie Zhang
Keyword(s):  
Feature Extraction ◽  
Genetic Programming ◽  
Classification Accuracy ◽  
Multi Objective ◽  
Face Classification ◽  
Feature Extraction Algorithm ◽  
Extraction Algorithm

© 2020 Owner/Author. This paper proposes a new multi-objective feature extraction algorithm using genetic programming (GP) for face classification. The new multi-objective GP-based feature extraction algorithm with the idea of non-dominated sorting, which aims to maximise the objective of the classification accuracy and minimise the objective of the number of extracted features. The results show that the proposed algorithm achieves significantly better performance than the baseline methods on two different face classification datasets.

scholarly journals Automatically extracting features for face classification using multi-objective genetic programming

2021 ◽  
Author(s):  
Ying Bi ◽  
Bing Xue ◽  
Mengjie Zhang
Keyword(s):  
Feature Extraction ◽  
Genetic Programming ◽  
Classification Accuracy ◽  
Multi Objective ◽  
Face Classification ◽  
Feature Extraction Algorithm ◽  
Extraction Algorithm

© 2020 Owner/Author. This paper proposes a new multi-objective feature extraction algorithm using genetic programming (GP) for face classification. The new multi-objective GP-based feature extraction algorithm with the idea of non-dominated sorting, which aims to maximise the objective of the classification accuracy and minimise the objective of the number of extracted features. The results show that the proposed algorithm achieves significantly better performance than the baseline methods on two different face classification datasets.

Student Admission Assesment using Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA)

2018 ◽  
Author(s):  
Rivalri Kristianto Hondro ◽  
Mesran Mesran ◽  
Andysah Putera Utama Siahaan
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Selection Process ◽  
Initial Step ◽  
Optimization Method ◽  
Ratio Analysis ◽  
Multi Objective Optimization ◽  
Prospective Students ◽  
Multi Objective

Procurement selection process in the acceptance of prospective students is an initial step undertaken by private universities to attract superior students. However, sometimes this selection process is just a procedural process that is commonly done by universities without grouping prospective students from superior students into a class that is superior compared to other classes. To process the selection results can be done using the help of computer systems, known as decision support systems. To produce a better, accurate and objective decision result is used a method that can be applied in decision support systems. Multi-Objective Optimization Method by Ratio Analysis (MOORA) is one of the MADM methods that can perform calculations on the value of criteria of attributes (prospective students) that helps decision makers to produce the right decision in the form of students who enter into the category of prospective students superior.

Corresponding Feature Extraction Algorithm between Infrared and Visible Images Using MSER

2011 ◽  
Vol 33 (7) ◽  
pp. 1625-1631 ◽  
Author(s):  
Lin Lian ◽  
Guo-hui Li ◽  
Hai-tao Wang ◽  
hao Tian ◽  
Shu-kui Xu
Keyword(s):  
Feature Extraction ◽  
Feature Extraction Algorithm ◽  
Extraction Algorithm ◽  
Visible Images

Multi-objective optimization of optimal capacitor allocation in radial distribution systems

2020 ◽  
Vol 21 (3) ◽  
Author(s):  
Sayed Mir Shah Danish ◽  
Mikaeel Ahmadi ◽  
Atsushi Yona ◽  
Tomonobu Senjyu ◽  
Narayanan Krishna ◽  
...  
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Reactive Power ◽  
Stability Index ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Size ◽  
Multi Objective Optimization ◽  
Multi Objective

AbstractThe optimal size and location of the compensator in the distribution system play a significant role in minimizing the energy loss and the cost of reactive power compensation. This article introduces an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using multi-objective optimization method. A new objective function different from literature is adapted to enhance the overall system voltage stability index, minimize power loss, and to achieve maximum net yearly savings. However, the capacitor sizes are assumed as discrete known variables, which are to be placed on the buses such that it reduces the losses of the distribution system to a minimum. Load sensitive factor (LSF) has been used to predict the most effective buses as the best place for installing compensator devices. IEEE 34-bus and 118-bus test distribution systems are utilized to validate and demonstrate the applicability of the proposed method. The simulation results obtained are compared with previous methods reported in the literature and found to be encouraging.

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