333,567 research outputs found
A Comparison between Fixed-Basis and Variable-Basis Schemes for Function Approximation and Functional Optimization
Fixed-basis and variable-basis approximation schemes are compared for the problems of function approximation and functional optimization (also known as infinite programming). Classes of problems are investigated for which variable-basis schemes with sigmoidal computational
units perform better than fixed-basis ones, in terms of the minimum number of computational units needed to achieve a desired error in function approximation or approximate optimization. Previously known bounds on the accuracy are extended, with better rates, to families o
On the Selection of Tuning Methodology of FOPID Controllers for the Control of Higher Order Processes
In this paper, a comparative study is done on the time and frequency domain
tuning strategies for fractional order (FO) PID controllers to handle higher
order processes. A new fractional order template for reduced parameter modeling
of stable minimum/non-minimum phase higher order processes is introduced and
its advantage in frequency domain tuning of FOPID controllers is also
presented. The time domain optimal tuning of FOPID controllers have also been
carried out to handle these higher order processes by performing optimization
with various integral performance indices. The paper highlights on the
practical control system implementation issues like flexibility of online
autotuning, reduced control signal and actuator size, capability of measurement
noise filtration, load disturbance suppression, robustness against parameter
uncertainties etc. in light of the above tuning methodologies.Comment: 27 pages, 10 figure
Binary Particle Swarm Optimization based Biclustering of Web usage Data
Web mining is the nontrivial process to discover valid, novel, potentially
useful knowledge from web data using the data mining techniques or methods. It
may give information that is useful for improving the services offered by web
portals and information access and retrieval tools. With the rapid development
of biclustering, more researchers have applied the biclustering technique to
different fields in recent years. When biclustering approach is applied to the
web usage data it automatically captures the hidden browsing patterns from it
in the form of biclusters. In this work, swarm intelligent technique is
combined with biclustering approach to propose an algorithm called Binary
Particle Swarm Optimization (BPSO) based Biclustering for Web Usage Data. The
main objective of this algorithm is to retrieve the global optimal bicluster
from the web usage data. These biclusters contain relationships between web
users and web pages which are useful for the E-Commerce applications like web
advertising and marketing. Experiments are conducted on real dataset to prove
the efficiency of the proposed algorithms
State-of-the-art in aerodynamic shape optimisation methods
Aerodynamic optimisation has become an indispensable component for any aerodynamic design over the past 60 years, with applications to aircraft, cars, trains, bridges, wind turbines, internal pipe flows, and cavities, among others, and is thus relevant in many facets of technology. With advancements in computational power, automated design optimisation procedures have become more competent, however, there is an ambiguity and bias throughout the literature with regards to relative performance of optimisation architectures and employed algorithms. This paper provides a well-balanced critical review of the dominant optimisation approaches that have been integrated with aerodynamic theory for the purpose of shape optimisation. A total of 229 papers, published in more than 120 journals and conference proceedings, have been classified into 6 different optimisation algorithm approaches. The material cited includes some of the most well-established authors and publications in the field of aerodynamic optimisation. This paper aims to eliminate bias toward certain algorithms by analysing the limitations, drawbacks, and the benefits of the most utilised optimisation approaches. This review provides comprehensive but straightforward insight for non-specialists and reference detailing the current state for specialist practitioners
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Artificial Immune Systems - Models, algorithms and applications
Copyright © 2010 Academic Research Publishing Agency.This article has been made available through the Brunel Open Access Publishing Fund.Artificial Immune Systems (AIS) are computational paradigms that belong to the computational intelligence family and are inspired by the biological immune system. During the past decade, they have attracted a lot of interest from researchers aiming to develop immune-based models and techniques to solve complex computational or engineering problems. This work presents a survey of existing AIS models and algorithms with a focus on the last five years.This article is available through the Brunel Open Access Publishing Fun
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