A review on feature-mapping methods for structural optimization
نویسندگان
چکیده
منابع مشابه
A review on EEG based brain computer interface systems feature extraction methods
The brain – computer interface (BCI) provides a communicational channel between human and machine. Most of these systems are based on brain activities. Brain Computer-Interfacing is a methodology that provides a way for communication with the outside environment using the brain thoughts. The success of this methodology depends on the selection of methods to process the brain signals in each pha...
متن کاملA review on EEG based brain computer interface systems feature extraction methods
The brain – computer interface (BCI) provides a communicational channel between human and machine. Most of these systems are based on brain activities. Brain Computer-Interfacing is a methodology that provides a way for communication with the outside environment using the brain thoughts. The success of this methodology depends on the selection of methods to process the brain signals in each pha...
متن کاملSTRUCTURAL OPTIMIZATION USING BIG BANG-BIG CRUNCH ALGORITHM: A REVIEW
The big bang-big crunch (BB-BC) algorithm is a popular metaheuristic optimization technique proposed based on one of the theories for the evolution of the universe. The algorithm utilizes a two-phase search mechanism: big-bang phase and big-crunch phase. In the big-bang phase the concept of energy dissipation is considered to produce disorder and randomness in the candidate population while in ...
متن کاملStructural feature selection for wrapper methods
The wrapper approach to feature selection requires the assessment of several subset alternatives and the selection of the one which is expected to have the lowest generalization error. To tackle this problem, practitioners have often recourse to a search procedure in a very large space of subsets of features aiming to minimize a leave-one-out or more in general a cross-validation criterion. It ...
متن کاملFeature Selection in Structural Health Monitoring Big Data Using a Meta-Heuristic Optimization Algorithm
This paper focuses on the processing of structural health monitoring (SHM) big data. Extracted features of a structure are reduced using an optimization algorithm to find a minimal subset of salient features by removing noisy, irrelevant and redundant data. The PSO-Harmony algorithm is introduced for feature selection to enhance the capability of the proposed method for processing the measure...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Structural and Multidisciplinary Optimization
سال: 2020
ISSN: 1615-147X,1615-1488
DOI: 10.1007/s00158-020-02649-6