Intelligent identification of Sequence stratigraphy constrained by multi‐population genetic algorithm and dynamic time warping technique: A case study of Lower Cretaceous Qingshuihe Formation in hinterland of Junggar Basin (NW China)

2021 ◽  
Author(s):  
Bingbing Shi ◽  
Xiangchun Chang ◽  
Zhongquan Liu ◽  
Yumao Pang ◽  
Youde Xu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Lower Cretaceous ◽  
Dynamic Time Warping ◽  
Population Genetic ◽  
Junggar Basin ◽  
Time Warping ◽  
Nw China ◽  
Dynamic Time ◽  
Population Genetic Algorithm

scholarly journals Cam Mechanisms Reverse Engineering Based on Evolutionary Algorithms

Electronics ◽  
2021 ◽  
Vol 10 (24) ◽  
pp. 3073
Author(s):  
Monica Tiboni ◽  
Cinzia Amici ◽  
Roberto Bussola
Keyword(s):  
Genetic Algorithm ◽  
Reverse Engineering ◽  
Dynamic Time Warping ◽  
Automated Manufacturing ◽  
Time Warping ◽  
Planning Techniques ◽  
Innovative Method ◽  
Cam Follower ◽  
Cam Profile ◽  
Dynamic Time

Cam follower mechanisms are widely used in automated manufacturing machinery to transform a rotary stationary motion into a more general required movement. Reverse engineering of cams has been studied, and some solutions based on different approaches have been identified in the literature. This article proposes an innovative method based on the use of an evolutionary algorithm for the identification of a law of motion that allows for approximating in the best way the motion or the sampled profile on the physical device. Starting from the acquired data, through a genetic algorithm, a representation of the movement (and therefore of the cam profile) is identified based on a type of motion law traditionally used for this purpose, i.e., the modified trapezoidal (better known as modified seven segments). With this method it is possible to estimate the coefficients of the parametric motion law, thus allowing the designer to further manipulate them according to the usual motion planning techniques. In a first phase, a study of the method based on simulations is carried out, considering sets of simulated experimental measures, obtained starting from different laws of motion, and verifying whether the developed genetic algorithm allows for identifying the original law or approximating one. For the computation of the objective function, the Euclidean norm and the Dynamic Time Warping (DTW) algorithm are compared. The performed analysis establishes in which situations each of them is more appropriate. Implementation of the method on experimental data validates its effectiveness.

scholarly journals Sequoia: An interactive visual analytics platform for interpretation and feature extraction from nanopore sequencing datasets

2019 ◽  
Author(s):  
Ratanond Koonchanok ◽  
Swapna Vidhur Daulatabad ◽  
Quoseena Mir ◽  
Khairi Reda ◽  
Sarath Chandra Janga
Keyword(s):  
Visual Analytics ◽  
Dynamic Time Warping ◽  
Visualization Tool ◽  
Web Interface ◽  
Time Warping ◽  
Front End ◽  
Oxford Nanopore ◽  
Dynamic Time ◽  
Oxford Nanopore Technologies

AbstractSequoia is a visualization tool that allows biologists to explore characteristics of signals generated by the Oxford Nanopore Technologies (ONT) in detail. From Fast5 files generated by ONT, the tool displays relative similarities between signals using the dynamic time warping and the t-SNE algorithms. Raw signals can be visualized through mouse actions while particular signals of interest can also be exported as a CSV file for further analysis. Sequoia consists of two major components: the command-line back-end that performs necessary computations using Python and the front-end that displays the visualization through a web interface. Two datasets are used to conduct a case study in order to illustrate the usability of the tool.

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