Unsupervised Case Memory Organization: Analysing Computational Time and Soft Computing Capabilities

2006 ◽  
pp. 241-255 ◽  
Author(s):  
A. Fornells ◽  
E. Golobardes ◽  
D. Vernet ◽  
G. Corral
Keyword(s):  
Soft Computing ◽  
Computational Time ◽  
Memory Organization

scholarly journals Performance enhancement of shunt active power filter using soft computing techniques

2021 ◽  
Vol 10 (3) ◽  
pp. 253
Author(s):  
Annu Govind ◽  
Vijay Kumar Tayal ◽  
Prakash Kumar
Keyword(s):  
Soft Computing ◽  
Gravitational Search Algorithm ◽  
Active Power Filter ◽  
Active Power ◽  
Voltage Source ◽  
Computational Time ◽  
Shunt Active Power Filter ◽  
Filter Performance ◽  
Power Filter ◽  
Soft Computing Techniques

Nowadays, active power filter (APF) is the most popular device for harmonic compensation. This paper presents the soft computing techniques for compensation of currents harmonics using a shunt active power filter (SAPF). The method includes a 3-phase supply system with a current-controlled voltage source converter (CC-VSC) having an input coupling inductor and output tank capacitor for a self-supported DC bus. The performance of the active power filter can be enhanced by using soft computing techniques such as artificial neural network (ANN) controller and gravitational search algorithm (GSA) for generating control signals of the SAPF. The current reference is calculated to compensate source current THD with synchronous reference frame (SRF) technique with proportional integrator (PI) controller. From the result, it is evident that both the soft computing techniques reduce the computational time & fast convergence which improves the filter performance during the transient period and makes it self-tuned. The proposed structure is simulated using MATLAB/Simulink and subsequently experimentally verified. The presentation of the system is originated to be suitable for numerous features of power quality enhancement structure.

Symmetric Multistep Methods Revisited: II. Numerical Experiments

1999 ◽  
Vol 173 ◽  
pp. 309-314 ◽  
Author(s):  
T. Fukushima
Keyword(s):  
Multistep Methods ◽  
Computational Time ◽  
Integration Time ◽  
Implicit Methods ◽  
Symmetric Methods ◽  
Celestial Bodies ◽  
The Stability ◽  
Predictor Corrector ◽  
Symmetric Multistep Methods ◽  
Integration Errors

AbstractBy using the stability condition and general formulas developed by Fukushima (1998 = Paper I) we discovered that, just as in the case of the explicit symmetric multistep methods (Quinlan and Tremaine, 1990), when integrating orbital motions of celestial bodies, the implicit symmetric multistep methods used in the predictor-corrector manner lead to integration errors in position which grow linearly with the integration time if the stepsizes adopted are sufficiently small and if the number of corrections is sufficiently large, say two or three. We confirmed also that the symmetric methods (explicit or implicit) would produce the stepsize-dependent instabilities/resonances, which was discovered by A. Toomre in 1991 and confirmed by G.D. Quinlan for some high order explicit methods. Although the implicit methods require twice or more computational time for the same stepsize than the explicit symmetric ones do, they seem to be preferable since they reduce these undesirable features significantly.

Soft Computing in Electromagnetics

2015 ◽  
Author(s):  
Balamati Choudhury ◽  
Rakesh Mohan Jha
Keyword(s):  
Soft Computing

Masked Translation Priming Effects With Highly Proficient Simultaneous Bilinguals

2010 ◽  
Vol 57 (2) ◽  
pp. 98-107 ◽  
Author(s):  
Jon Andoni Duñabeitia ◽  
Manuel Perea ◽  
Manuel Carreiras
Keyword(s):  
Lexical Decision ◽  
Hierarchical Model ◽  
Priming Effect ◽  
Masked Priming ◽  
The Other ◽  
Memory Organization ◽  
Priming Effects ◽  
Bilingual Memory ◽  
Translation Priming ◽  
Masked Translation Priming

One essential issue for models of bilingual memory organization is to what degree the representation from one of the languages is shared with the other language. In this study, we examine whether there is a symmetrical translation priming effect with highly proficient, simultaneous bilinguals. We conducted a masked priming lexical decision experiment with cognate and noncognate translation equivalents. Results showed a significant masked translation priming effect for both cognates and noncognates, with a greater priming effect for cognates. Furthermore, the magnitude of the translation priming was similar in the two directions. Thus, highly fluent bilinguals do develop symmetrical between-language links, as predicted by the Revised Hierarchical model and the BIA+ model. We examine the implications of these results for models of bilingual memory.

Who, What, When, and Where? Memory Organization of Event Descriptions

1992 ◽  
Author(s):  
Holly A. Taylor ◽  
Barbara Tversky
Keyword(s):  
Memory Organization

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

MACHINE LEARNING FOR SOFTWARE

2019 ◽  
pp. 251-255
Author(s):  
Shafagat Mahmudova
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Soft Computing ◽  
Computing Technology

The study machine learning for software based on Soft Computing technology. It analyzes Soft Computing components. Their use in software, their advantages and challenges are studied. Machine learning and its features are highlighted. The functions and features of neural networks are clarified, and recommendations were given.

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