Abstract: In the recent past Learning Classifier Systems have
been successfully used for data mining. Learning Classifier System
(LCS) is basically a machine learning technique which combines
evolutionary computing, reinforcement learning, supervised or
unsupervised learning and heuristics to produce adaptive systems. A
LCS learns by interacting with an environment from which it
receives feedback in the form of numerical reward. Learning is
achieved by trying to maximize the amount of reward received. All
LCSs models more or less, comprise four main components; a finite
population of condition–action rules, called classifiers; the
performance component, which governs the interaction with the
environment; the credit assignment component, which distributes the
reward received from the environment to the classifiers accountable
for the rewards obtained; the discovery component, which is
responsible for discovering better rules and improving existing ones
through a genetic algorithm. The concatenate of the production rules
in the LCS form the genotype, and therefore the GA should operate
on a population of classifier systems. This approach is known as the
'Pittsburgh' Classifier Systems. Other LCS that perform their GA at
the rule level within a population are known as 'Mitchigan' Classifier
Systems. The most predominant representation of the discovered
knowledge is the standard production rules (PRs) in the form of IF P
THEN D. The PRs, however, are unable to handle exceptions and do
not exhibit variable precision. The Censored Production Rules
(CPRs), an extension of PRs, were proposed by Michalski and
Winston that exhibit variable precision and supports an efficient
mechanism for handling exceptions. A CPR is an augmented
production rule of the form: IF P THEN D UNLESS C, where
Censor C is an exception to the rule. Such rules are employed in
situations, in which conditional statement IF P THEN D holds
frequently and the assertion C holds rarely. By using a rule of this
type we are free to ignore the exception conditions, when the
resources needed to establish its presence are tight or there is simply
no information available as to whether it holds or not. Thus, the IF P
THEN D part of CPR expresses important information, while the
UNLESS C part acts only as a switch and changes the polarity of D
to ~D. In this paper Pittsburgh style LCSs approach is used for
automated discovery of CPRs. An appropriate encoding scheme is
suggested to represent a chromosome consisting of fixed size set of
CPRs. Suitable genetic operators are designed for the set of CPRs
and individual CPRs and also appropriate fitness function is proposed
that incorporates basic constraints on CPR. Experimental results are
presented to demonstrate the performance of the proposed learning
classifier system.
Abstract: The paper deals with the estimation of amplitude and phase of an analogue multi-harmonic band-limited signal from irregularly spaced sampling values. To this end, assuming the signal fundamental frequency is known in advance (i.e., estimated at an independent stage), a complexity-reduced algorithm for signal reconstruction in time domain is proposed. The reduction in complexity is achieved owing to completely new analytical and summarized expressions that enable a quick estimation at a low numerical error. The proposed algorithm for the calculation of the unknown parameters requires O((2M+1)2) flops, while the straightforward solution of the obtained equations takes O((2M+1)3) flops (M is the number of the harmonic components). It is applied in signal reconstruction, spectral estimation, system identification, as well as in other important signal processing problems. The proposed method of processing can be used for precise RMS measurements (for power and energy) of a periodic signal based on the presented signal reconstruction. The paper investigates the errors related to the signal parameter estimation, and there is a computer simulation that demonstrates the accuracy of these algorithms.
Abstract: For stable bipedal gait generation on the level floor,
efficient restoring of mechanical energy lost by heel collision at
the ground is necessary. Parametric excitation principle is one of
the solutions. We dealt with the robot-s total center of mass as
an inverted pendulum to consider the total dynamics of the robot.
Parametrically excited walking requires the use of continuous target
trajectory that is close to discontinuous optimal trajectory. In this
paper, we proposed the new target trajectory based on a position
in the walking direction. We surveyed relations between walking
performance and the parameters that form the target trajectory via
numerical simulations. As a result, it was found that our target
trajectory has the similar characteristics of a parametrically excited
inverted pendulum.
Abstract: The extraction of meaningful information from image
could be an alternative method for time series analysis. In this paper,
we propose a graphical analysis of time series grouped into table
with adjusted colour scale for numerical values. The advantages of
this method are also discussed. The proposed method is easy to
understand and is flexible to implement the standard methods of
pattern recognition and verification, especially for noisy
environmental data.
Abstract: In this paper, the modified optimal sliding mode control with a proposed method to design a sliding surface is presented. Because of the inability of the previous approach of the sliding mode method to design a bounded and suitable input, the new variation is proposed in the sliding manifold to obviate problems in a structural system. Although the sliding mode control is a powerful method to reject disturbances and noises, the chattering problem is not good for actuators. To decrease the chattering phenomena, the optimal control is added to the sliding mode control. Not only the proposed method can decline the intense variations in the inputs of the system but also it can produce the efficient responses respect to the sliding mode control and optimal control that are shown by performing some numerical simulations.
Abstract: In this paper, a delayed physiological control system is investigated. The sufficient conditions for stability of positive equilibrium and existence of local Hopf bifurcation are derived. Furthermore, global existence of periodic solutions is established by using the global Hopf bifurcation theory. Finally, numerical examples are given to support the theoretical analysis.
Abstract: The electromagnetic imaging of inhomogeneous
dielectric cylinders buried in a slab medium by transverse electric
(TE) wave illumination is investigated. Dielectric cylinders of
unknown permittivities are buried in second space and scattered a
group of unrelated waves incident from first space where the scattered
field is recorded. By proper arrangement of the various unrelated
incident fields, the difficulties of ill-posedness and nonlinearity are
circumvented, and the permittivity distribution can be reconstructed
through simple matrix operations. The algorithm is based on the
moment method and the unrelated illumination method. Numerical
results are given to demonstrate the capability of the inverse
algorithm. Good reconstruction is obtained even in the presence of
additive Gaussian random noise in measured data. In addition, the
effect of noise on the reconstruction result is also investigated.
Abstract: In this paper, the issue of pth moment exponential stability of stochastic recurrent neural network with distributed time delays is investigated. By using the method of variation parameters, inequality techniques, and stochastic analysis, some sufficient conditions ensuring pth moment exponential stability are obtained. The method used in this paper does not resort to any Lyapunov function, and the results derived in this paper generalize some earlier criteria reported in the literature. One numerical example is given to illustrate the main results.
Abstract: The presented article deals with the description of a
numerical model of a corridor at a Central Interim Spent Fuel Storage
Facility (hereinafter CISFSF). The model takes into account the
effect of air flows on the temperature of stored waste. The
computational model was implemented in the ANSYS/CFX
programming environment in the form of a CFD task solution, which
was compared with an approximate analytical calculation. The article
includes a categorization of the individual alternatives for the
ventilation of such underground systems. The aim was to evaluate a
ventilation system for a CISFSF with regard to its stability and
capacity to provide sufficient ventilation for the removal of heat
produced by stored casks with spent nuclear fuel.
Abstract: The purpose of this paper is to elucidate the flow unsteady behavior for moving plug in convergent-divergent variable thrust nozzle. Compressible axisymmetric Navier-Stokes equations are used to study this physical phenomenon. Different velocities are set for plug to investigate the effect of plug movement on flow unsteadiness. Variation of mass flow rate and thrust are compared under two conditions: First, the plug is placed at different positions and flow is simulated to reach the steady state (quasi steady simulation) and second, the plug is moved with assigned velocity and flow simulation is coupled with plug movement (unsteady simulation). If plug speed is high enough and its movement time scale is at the same order of the flow time scale, variation of the mass flow rate and thrust level versus plug position demonstrate a vital discrepancy under the quasi steady and unsteady conditions. This phenomenon should be considered especially from response time viewpoints in thrusters design.
Abstract: In the present paper some recommendations for the
use of software package “Mathematica" in a basic numerical analysis
course are presented. The methods which are covered in the course
include solution of systems of linear equations, nonlinear equations
and systems of nonlinear equations, numerical integration,
interpolation and solution of ordinary differential equations. A set of
individual assignments developed for the course covering all the
topics is discussed in detail.
Abstract: The Eulerian numerical method is proposed to analyze
the explosion in tunnel. Based on this method, an original software
M-MMIC2D is developed by Cµ program language. With this
software, the explosion problem in the tunnel with three
expansion-chambers is numerically simulated, and the results are
found to be in full agreement with the observed experimental data.
Abstract: Feeder is one of the airships of the Multibody Advanced Airship for Transport (MAAT) system, under development within the EU FP7 project. MAAT is based on a modular concept composed of two different parts that have the possibility to join; respectively they are the so-called Cruiser and Feeder, designed on the lighter than air principle. Feeder, also named ATEN (Airship Transport Elevator Network), is the smaller one which joins the bigger one, Cruiser, also named PTAH (Photovoltaic modular Transport Airship for High altitude),envisaged to happen at 15km altitude. During the MAAT design phase, the aerodynamic studies of the both airships and their interactions are analyzed. The objective of these studies is to understand the aerodynamic behavior of all the preselected configurations, as an important element in the overall MAAT system design. The most of these configurations are only simulated by CFD, while the most feasible one is experimentally analyzed in order to validate and thrust the CFD predictions. This paper presents the numerical and experimental investigation of the Feeder “conical like" shape configuration. The experiments are focused on the aerodynamic force coefficients and the pressure distribution over the Feeder outer surface, while the numerical simulation cover also the analysis of the velocity and pressure distribution. Finally, the wind tunnel experiment is compared with its CFD model in order to validate such specific simulations with respective experiments and to better understand the difference between the wind tunnel and in-flight circumstances.
Abstract: By taking advantage of computer-s processing power, an unlimited number of variations and parameters in both spatial and environmental can be provided while following the same set of rules and constraints. This paper focuses on using the tools of parametric urbanism towards a more responsive environmental and sustainable urban morphology. It presents an understanding to Parametric Urban Comfort Envelope (PUCE) as an interactive computational assessment urban model. In addition, it investigates the applicability potentials of this model to generate an optimized urban form to Borg El Arab city (a new Egyptian Community) concerning the human comfort values specially wind and solar envelopes. Finally, this paper utilizes its application outcomes -both visual and numerical- to extend the designer-s limitations by decrease the concern of controlling and manipulation of geometry, and increase the designer-s awareness about the various potentials of using the parametric tools to create relationships that generate multiple geometric alternatives.
Abstract: A time-domain numerical model within the
framework of transmission line modeling (TLM) is developed to
simulate electromagnetic pulse propagation inside multiple
microcavities forming photonic crystal (PhC) structures. The model
developed is quite general and is capable of simulating complex
electromagnetic problems accurately. The field quantities can be
mapped onto a passive electrical circuit equivalent what ensures that
TLM is provably stable and conservative at a local level.
Furthermore, the circuit representation allows a high level of
hybridization of TLM with other techniques and lumped circuit
models of components and devices. A photonic crystal structure
formed by rods (or blocks) of high-permittivity dieletric material
embedded in a low-dielectric background medium is simulated as an
example. The model developed gives vital spatio-temporal
information about the signal, and also gives spectral information over
a wide frequency range in a single run. The model has wide
applications in microwave communication systems, optical
waveguides and electromagnetic materials simulations.
Abstract: In this paper, we propose a new algorithm for joint time-delay and direction-of-arrival (DOA) estimation, here called two-dimensional code acquisition, in an asynchronous directsequence code-division multiple-access (DS-CDMA) array system. This algorithm depends on eigenvector-eigenvalue decomposition of sample correlation matrix, and requires to know desired user-s training sequence. The performance of the algorithm is analyzed both analytically and numerically in uncorrelated and coherent multipath environment. Numerical examples show that the algorithm is robust with unknown number of coherent signals.
Abstract: Numerical studies have been carried out using a
validated two-dimensional RNG k-epsilon turbulence model for the
design optimization of a thrust vector control system using shock
induced supersonic secondary jet. Parametric analytical studies have
been carried out with various secondary jets at different divergent
locations, jet interaction angles, jet pressures. The results from the
parametric studies of the case on hand reveal that the primary nozzle
with a small divergence angle, downstream injections with a distance
of 2.5 times the primary nozzle throat diameter from the primary
nozzle throat location warrant higher efficiency over a certain range
of jet pressures and jet angles. We observed that the supersonic
secondary jet opposing the core flow with jets interaction angle of
40o to the axis far downstream of the nozzle throat facilitates better
thrust vectoring than the secondary jet with same direction as that of
core flow with various interaction angles. We concluded that fixing
of the supersonic secondary jet nozzle pointing towards the throat
direction with suitable angle at a distance 2 to 4 times of the primary
nozzle throat diameter, as the case may be, from the primary nozzle
throat location could facilitate better thrust vectoring for the
supersonic aerospace vehicles.
Abstract: The optimal grid spacing and turbulence model for the
2D numerical analysis of a vertical-axis water turbine (VAWaterT)
operating in a 2 m/s freestream current has been investigated. The
results of five different spatial domain discretizations and two
turbulence models (k-ω SST and k-ε RNG) have been compared, in
order to gain the optimal y+ parameter distribution along the blade
walls during a full rotor revolution. The resulting optimal mesh has
appeared to be quite similar to that obtained for the numerical
analysis of a vertical-axis wind turbine.
Abstract: Air bending is one of the important metal forming
processes, because of its simplicity and large field application.
Accuracy of analytical and empirical models reported for the analysis
of bending processes is governed by simplifying assumption and do
not consider the effect of dynamic parameters. Number of researches
is reported on the finite element analysis (FEA) of V-bending, Ubending,
and air V-bending processes. FEA of bending is found to be
very sensitive to many physical and numerical parameters. FE
models must be computationally efficient for practical use. Reported
work shows the 3D FEA of air bending process using Hyperform LSDYNA
and its comparison with, published 3D FEA results of air
bending in Ansys LS-DYNA and experimental results. Observing the
planer symmetry and based on the assumption of plane strain
condition, air bending problem was modeled in 2D with symmetric
boundary condition in width. Stress-strain results of 2D FEA were
compared with 3D FEA results and experiments. Simplification of
air bending problem from 3D to 2D resulted into tremendous
reduction in the solution time with only marginal effect on stressstrain
results. FE model simplification by studying the problem
symmetry is more efficient and practical approach for solution of
more complex large dimensions slow forming processes.
Abstract: This study presents a hybrid neural network and Gravitational Search Algorithm (HNGSA) method to solve well known Wessinger's equation. To aim this purpose, gravitational search algorithm (GSA) technique is applied to train a multi-layer perceptron neural network, which is used as approximation solution of the Wessinger's equation. A trial solution of the differential equation is written as sum of two parts. The first part satisfies the initial/ boundary conditions and does not contain any adjustable parameters and the second part which is constructed so as not to affect the initial/boundary conditions. The second part involves adjustable parameters (the weights and biases) for a multi-layer perceptron neural network. In order to demonstrate the presented method, the obtained results of the proposed method are compared with some known numerical methods. The given results show that presented method can introduce a closer form to the analytic solution than other numerical methods. Present method can be easily extended to solve a wide range of problems.