Abstract: Data mining uses a variety of techniques each of which
is useful for some particular task. It is important to have a deep
understanding of each technique and be able to perform sophisticated
analysis. In this article we describe a tool built to simulate a variation
of the Kohonen network to perform unsupervised clustering and
support the entire data mining process up to results visualization. A
graphical representation helps the user to find out a strategy to
optimize classification by adding, moving or delete a neuron in order
to change the number of classes. The tool is able to automatically
suggest a strategy to optimize the number of classes optimization, but
also support both tree classifications and semi-lattice organizations of
the classes to give to the users the possibility of passing from one
class to the ones with which it has some aspects in common.
Examples of using tree and semi-lattice classifications are given to
illustrate advantages and problems. The tool is applied to classify
macroeconomic data that report the most developed countries- import
and export. It is possible to classify the countries based on their
economic behaviour and use the tool to characterize the commercial
behaviour of a country in a selected class from the analysis of
positive and negative features that contribute to classes formation.
Possible interrelationships between the classes and their meaning are
also discussed.
Abstract: A direct search approach to determine optimal reservoir operating is proposed with ant colony optimization for continuous domains (ACOR). The model is applied to a system of single reservoir to determine the optimum releases during 42 years of monthly steps. A disadvantage of ant colony based methods and the ACOR in particular, refers to great amount of computer run time consumption. In this study a highly effective procedure for decreasing run time has been developed. The results are compared to those of a GA based model.
Abstract: One of the approaches enabling people with amputated
limbs to establish some sort of interface with the real world includes
the utilization of the myoelectric signal (MES) from the remaining
muscles of those limbs. The MES can be used as a control input to a
multifunction prosthetic device. In this control scheme, known as the
myoelectric control, a pattern recognition approach is usually utilized
to discriminate between the MES signals that belong to different
classes of the forearm movements. Since the MES is recorded using
multiple channels, the feature vector size can become very large. In
order to reduce the computational cost and enhance the generalization
capability of the classifier, a dimensionality reduction method is
needed to identify an informative yet moderate size feature set. This
paper proposes a new fuzzy version of the well known Fisher-s
Linear Discriminant Analysis (LDA) feature projection technique.
Furthermore, based on the fact that certain muscles might contribute
more to the discrimination process, a novel feature weighting scheme
is also presented by employing Particle Swarm Optimization (PSO)
for estimating the weight of each feature. The new method, called
PSOFLDA, is tested on real MES datasets and compared with other
techniques to prove its superiority.
Abstract: This paper proposes an improved approach based on
conventional particle swarm optimization (PSO) for solving an
economic dispatch(ED) problem with considering the generator
constraints. The mutation operators of the differential evolution (DE)
are used for improving diversity exploration of PSO, which called
particle swarm optimization with mutation operators (PSOM). The
mutation operators are activated if velocity values of PSO nearly to
zero or violated from the boundaries. Four scenarios of mutation
operators are implemented for PSOM. The simulation results of all
scenarios of the PSOM outperform over the PSO and other existing
approaches which appeared in literatures.
Abstract: Since supply chains highly impact the financial
performance of companies, it is important to optimize and analyze
their Key Performance Indicators (KPI). The synergistic combination
of Particle Swarm Optimization (PSO) and Monte Carlo simulation is
applied to determine the optimal reorder point of warehouses in
supply chains. The goal of the optimization is the minimization of the
objective function calculated as the linear combination of holding and
order costs. The required values of service levels of the warehouses
represent non-linear constraints in the PSO. The results illustrate that
the developed stochastic simulator and optimization tool is flexible
enough to handle complex situations.
Abstract: In this paper, Novel method, Particle Swarm Optimization (PSO) algorithm, based technique is proposed to estimate and analyze the steady state performance of self-excited induction generator (SEIG). In this novel method the tedious job of deriving the complex coefficients of a polynomial equation and solving it, as in previous methods, is not required. By comparing the simulation results obtained by the proposed method with those obtained by the well known mathematical methods, a good agreement between these results is obtained. The comparison validates the effectiveness of the proposed technique.
Abstract: Information hiding for authenticating and verifying the content integrity of the multimedia has been exploited extensively in the last decade. We propose the idea of using genetic algorithm and non-deterministic dependence by involving the un-watermarkable coefficients for digital image authentication. Genetic algorithm is used to intelligently select coefficients for watermarking in a DCT based image authentication scheme, which implicitly watermark all the un-watermarkable coefficients also, in order to thwart different attacks. Experimental results show that such intelligent selection results in improvement of imperceptibility of the watermarked image, and implicit watermarking of all the coefficients improves security against attacks such as cover-up, vector quantization and transplantation.
Abstract: The nearly 21-year-old Jiujiang Bridge, which is suffering from uneven line shape, constant great downwarping of the main beam and cracking of the box girder, needs reinforcement and cable adjustment. It has undergone cable adjustment for twice with incomplete data. Therefore, the initial internal force state of the Jiujiang Bridge is identified as the key for the cable adjustment project. Based on parameter identification by means of static force test data, this paper suggests determining the initial internal force state of the cable-stayed bridge according to the cable force-displacement relationship parameter identification method. That is, upon measuring the displacement and the change in cable forces for twice, one can identify the parameters concerned by means of optimization. This method is applied to the cable adjustment, replacement and reinforcement project for the Jiujiang Bridge as a guidance for the cable adjustment and reinforcement project of the bridge.
Abstract: This paper proposes a meta-heuristic called Ant Colony Optimization to solve multi-objective production problems. The multi-objective function is to minimize lead time and work in process. The problem is related to the decision variables, i.e.; distance and process time. According to decision criteria, the mathematical model is formulated. In order to solve the model an ant colony optimization approach has been developed. The proposed algorithm is parameterized by the number of ant colonies and the number of pheromone trails. One example is given to illustrate the effectiveness of the proposed model. The proposed formulations; Max-Min Ant system are then used to solve the problem and the results evaluate the performance and efficiency of the proposed algorithm using simulation.
Abstract: We propose a control design scheme that aims to
prevent undesirable liquid outpouring and suppress sloshing during
the forward and backward tilting phases of the pouring process, for
the case of liquid containers carried by manipulators. The proposed
scheme combines a partial inverse dynamics controller with a PID
controller, tuned with the use of a “metaheuristic" search algorithm.
The “metaheuristic" search algorithm tunes the PID controller based
on simulation results of the plant-s linearization around the operating
point corresponding to the critical tilting angle, where outpouring
initiates. Liquid motion is modeled using the well-known pendulumtype
model. However, the proposed controller does not require
measurements of the liquid-s motion within the tank.
Abstract: This paper focuses on cost and profit analysis of
single-server Markovian queuing system with two priority classes. In
this paper, functions of total expected cost, revenue and profit of the
system are constructed and subjected to optimization with respect to
its service rates of lower and higher priority classes. A computing
algorithm has been developed on the basis of fast converging
numerical method to solve the system of non linear equations formed
out of the mathematical analysis. A novel performance measure of
cost and profit analysis in view of its economic interpretation for the
system with priority classes is attempted to discuss in this paper. On
the basis of computed tables observations are also drawn to enlighten
the variational-effect of the model on the parameters involved
therein.
Abstract: This paper aims to select the optimal location and
setting parameters of TCSC (Thyristor Controlled Series
Compensator) controller using Particle Swarm Optimization (PSO)
and Genetic Algorithm (GA) to mitigate small signal oscillations in a
multimachine power system. Though Power System Stabilizers
(PSSs) are prime choice in this issue, installation of FACTS device
has been suggested here in order to achieve appreciable damping of
system oscillations. However, performance of any FACTS devices
highly depends upon its parameters and suitable location in the
power network. In this paper PSO as well as GA based techniques are
used separately and compared their performances to investigate this
problem. The results of small signal stability analysis have been
represented employing eigenvalue as well as time domain response in
face of two common power system disturbances e.g., varying load
and transmission line outage. It has been revealed that the PSO based
TCSC controller is more effective than GA based controller even
during critical loading condition.
Abstract: At the previous study of new metal gasket, contact
width and contact stress were important design parameter for
optimizing metal gasket performance. However, the range of contact
stress had not been investigated thoroughly. In this study, we
conducted a gasket design optimization based on an elastic and plastic
contact stress analysis considering forming effect using FEM. The
gasket model was simulated by using two simulation stages which is
forming and tightening simulation. The optimum design based on an
elastic and plastic contact stress was founded. Final evaluation was
determined by helium leak quantity to check leakage performance of
both type of gaskets. The helium leak test shows that a gasket based
on the plastic contact stress design better than based on elastic stress
design.
Abstract: In the present work, we introduce the particle swarm optimization called (PSO in short) to avoid the Runge-s phenomenon occurring in many numerical problems. This new approach is tested with some numerical examples including the generalized integral quadrature method in order to solve the Volterra-s integral equations
Abstract: The process parameters, temperature, pH and
substrate concentration, were optimized for the production of
gentamicin using Micromonouspora echinospora. Experiments were
carried out according to central composite design in response surface
method. The optimum conditions for the maximum production of
gentamicin were found to be: temperature – 31.7oC, pH – 6.8 and
substrate concentration – 3%. At these optimized conditions the
production of gentamicin was found to be – 1040 mg/L. The R2 value
of 0.9465 indicates a good fitness of the model.
Abstract: Symbolic Circuit Analysis (SCA) is a technique used
to generate the symbolic expression of a network. It has become a
well-established technique in circuit analysis and design. The
symbolic expression of networks offers excellent way to perform
frequency response analysis, sensitivity computation, stability
measurements, performance optimization, and fault diagnosis. Many
approaches have been proposed in the area of SCA offering different
features and capabilities. Numerical Interpolation methods are very
common in this context, especially by using the Fast Fourier
Transform (FFT). The aim of this paper is to present a method for
SCA that depends on the use of Wavelet Transform (WT) as a
mathematical tool to generate the symbolic expression for large
circuits with minimizing the analysis time by reducing the number of
computations.
Abstract: This paper present an efficient and reliable technique of optimization which combined fuel cost economic optimization and emission dispatch using the Sigmoid Decreasing Inertia Weight Particle Swarm Optimization algorithm (PSO) to reduce the cost of fuel and pollutants resulting from fuel combustion by keeping the output of generators, bus voltages, shunt capacitors and transformer tap settings within the security boundary. The performance of the proposed algorithm has been demonstrated on IEEE 30-bus system with six generating units. The results clearly show that the proposed algorithm gives better and faster speed convergence then linearly decreasing inertia weight.
Abstract: In this paper, optimal generation expansion planning (GEP) is investigated considering purchase prices, profits of independent power producers (IPPs) and reliability criteria using a new method based on hybrid coded Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). In this approach, optimal purchase price of each IPP is obtained by HCGA and reliability criteria are calculated by PSO technique. It should be noted that reliability criteria and the rate of carbon dioxide (CO2) emission have been considered as constraints of the GEP problem. Finally, the proposed method has been tested on the case study system. The results evaluation show that the proposed method can simply obtain optimal purchase prices of IPPs and is a fast method for calculation of reliability criteria in expansion planning. Also, considering the optimal purchase prices and profits of IPPs in generation expansion planning are caused that the expansion costs are decreased and the problem is solved more exactly.
Abstract: Inconel 718, a nickel based super-alloy is an
extensively used alloy, accounting for about 50% by weight of
materials used in an aerospace engine, mainly in the gas turbine
compartment. This is owing to their outstanding strength and
oxidation resistance at elevated temperatures in excess of 5500 C.
Machining is a requisite operation in the aircraft industries for the
manufacture of the components especially for gas turbines. This
paper is concerned with optimization of the surface roughness when
turning Inconel 718 with cermet inserts. Optimization of turning
operation is very useful to reduce cost and time for machining. The
approach is based on Response Surface Method (RSM). In this work,
second-order quadratic models are developed for surface roughness,
considering the cutting speed, feed rate and depth of cut as the cutting
parameters, using central composite design. The developed models
are used to determine the optimum machining parameters. These
optimized machining parameters are validated experimentally, and it
is observed that the response values are in reasonable agreement with
the predicted values.
Abstract: The problem of bin-packing in two dimensions (2BP) consists in placing a given set of rectangular items in a minimum number of rectangular and identical containers, called bins. This article treats the case of objects with a free orientation of 90Ôùª. We propose an approach of resolution combining optimization by colony of ants (ACO) and the heuristic method IMA to resolve this NP-Hard problem.