Abstract: In this paper, genetic algorithm (GA) is proposed for
the design of an optimization algorithm to achieve the bandwidth
allocation of ATM network. In Broadband ISDN, the ATM is a highbandwidth;
fast packet switching and multiplexing technique. Using
ATM it can be flexibly reconfigure the network and reassign the
bandwidth to meet the requirements of all types of services. By
dynamically routing the traffic and adjusting the bandwidth
assignment, the average packet delay of the whole network can be
reduced to a minimum. M/M/1 model can be used to analyze the
performance.
Abstract: Feature and model selection are in the center of
attention of many researches because of their impact on classifiers-
performance. Both selections are usually performed separately but
recent developments suggest using a combined GA-SVM approach to
perform them simultaneously. This approach improves the
performance of the classifier identifying the best subset of variables
and the optimal parameters- values. Although GA-SVM is an
effective method it is computationally expensive, thus a rough
method can be considered. The paper investigates a joined approach
of Genetic Algorithm and kernel matrix criteria to perform
simultaneously feature and model selection for SVM classification
problem. The purpose of this research is to improve the classification
performance of SVM through an efficient approach, the Kernel
Matrix Genetic Algorithm method (KMGA).
Abstract: Unlike this study focused extensively on trading
behavior of option market, those researches were just taken their
attention to model-driven option pricing. For example, Black-Scholes
(B-S) model is one of the most famous option pricing models.
However, the arguments of B-S model are previously mentioned by
some pricing models reviewing. This paper following suggests the
importance of the dynamic character for option pricing, which is also
the reason why using the genetic algorithm (GA). Because of its
natural selection and species evolution, this study proposed a hybrid
model, the Genetic-BS model which combining GA and B-S to
estimate the price more accurate. As for the final experiments, the
result shows that the output estimated price with lower MAE value
than the calculated price by either B-S model or its enhanced one,
Gram-Charlier garch (G-C garch) model. Finally, this work would
conclude that the Genetic-BS pricing model is exactly practical.
Abstract: Microorganisms isolated from water and soil of
Kazakhstan to identify potential high-effective producers of the
arachidonic acid, exhibiting a wide range of physiological activity
and having practical applications were screened. Based on the results
of two independent tests (the test on the sensitivity of the growth
processes of microorganisms to acetylsalicylic acid - an irreversible
inhibitor of PGH-synthase involved in the metabolism of arachidonic
acid and its derivatives, the test for inhibition of peroxidase activity
of membrane-bounding fraction of PGH - synthase by acetylsalicylic
acid) were selected microbial cultures which are potential highproducer
of arachidonic acid. They are characterized by a stable
strong growth in the laboratory conditions. Identification of
microorganism cultures based on morphological, physiological,
biochemical and molecular genetic characteristics was performed.
Abstract: Two indica varieties, IR36 and ‘Suweon 258’ (“S”)
are middle-heading in southern Japan. 36U, also middle-heading, is
an isogenic line of IR36 carrying Ur1 (Undulate rachis-1) gene.
However, late-heading plants segregated in the F2 population from
the F1 of S × 36U, and so did in the following generations. The
concerning lateness gene is designated as Ex. From the F8 generation,
isogenic-line pair of early-heading and late-heading lines, denoted by
“E” (ex/ex) and “L” (Ex/Ex), were developed. Genetic analyses of
heading time were conducted, using F1s and F2s among L, E, S and
36U. The following inferences were drawn from the experimental
results: 1) L, and both of E and 36U harbor Ex and ex, respectively;
2) Besides Ex, S harbors an inhibitor gene to it, i.e. I-Ex which is a
novel finding of the present study. 3) Ex is a dominant allele at the
E1 locus.
Abstract: The main goal of this work is to propose a way for
combined use of two nontraditional algorithms by solving topological
problems on telecommunications concentrator networks. The
algorithms suggested are the Simulated Annealing algorithm and the
Genetic Algorithm. The Algorithm of Simulated Annealing unifies
the well known local search algorithms. In addition - Simulated
Annealing allows acceptation of moves in the search space witch lead
to decisions with higher cost in order to attempt to overcome any
local minima obtained. The Genetic Algorithm is a heuristic approach
witch is being used in wide areas of optimization works. In the last
years this approach is also widely implemented in
Telecommunications Networks Planning. In order to solve less or
more complex planning problem it is important to find the most
appropriate parameters for initializing the function of the algorithm.
Abstract: Several approaches such as linear programming, network
modeling, greedy heuristic and decision support system are well-known
approaches in solving irregular airline operation problem. This paper
presents an alternative approach based on Multi Objective Micro Genetic
Algorithm. The aim of this research is to introduce the concept of Multi
Objective Micro Genetic Algorithm as a tool to solve irregular airline
operation, combine and reroute problem. The experiment result indicated
that the model could obtain optimal solutions within a few second.
Abstract: This paper describes a new approach of classification
using genetic programming. The proposed technique consists of
genetically coevolving a population of non-linear transformations on
the input data to be classified, and map them to a new space with a
reduced dimension, in order to get a maximum inter-classes
discrimination. The classification of new samples is then performed
on the transformed data, and so become much easier. Contrary to the
existing GP-classification techniques, the proposed one use a
dynamic repartition of the transformed data in separated intervals, the
efficacy of a given intervals repartition is handled by the fitness
criterion, with a maximum classes discrimination. Experiments were
first performed using the Fisher-s Iris dataset, and then, the KDD-99
Cup dataset was used to study the intrusion detection and
classification problem. Obtained results demonstrate that the
proposed genetic approach outperform the existing GP-classification
methods [1],[2] and [3], and give a very accepted results compared to
other existing techniques proposed in [4],[5],[6],[7] and [8].
Abstract: In the control theory one attempts to find a controller
that provides the best possible performance with respect to some
given measures of performance. There are many sorts of controllers
e.g. a typical PID controller, LQR controller, Fuzzy controller etc. In
the paper will be introduced polynomial controller with novel tuning
method which is based on the special pole placement encoding
scheme and optimization by Genetic Algorithms (GA). The examples
will show the performance of the novel designed polynomial
controller with comparison to common PID controller.
Abstract: Transmission network expansion planning (TNEP) is a basic part of power system planning that determines where, when and how many new transmission lines should be added to the network. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, lines adequacy rate has not been considered at the end of planning horizon, i.e., expanded network misses adequacy after some times and needs to be expanded again. In this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and inserting investment cost into the fitness function constraints using genetic algorithm. Expanded network will possess a maximum adequacy to provide load demand and also the transmission lines overloaded later. Finally, adequacy index could be defined and used to compare some designs that have different investment costs and adequacy rates. In this paper, the proposed idea has been tested on the Garvers network. The results show that the network will possess maximum efficiency economically.
Abstract: A lot of recent research have spoken on the relation
between the increase of the homocysteinemia and some kinds of
cancer . For that, our study was based on the research of a possible
relation between the increase of the concentration of this amino-acid
in the plasma and the appearance of the disease of the Acute
Lymphoblastic Leukaemia in a part of Algerian children with Berber
origin in the East of Algeria . The study has done on 47 ill persons
with an average age of (09±06 ) years , with whom the disease has
diagnosed by blood and marrow examination in the hospital of blood
diseases in the CHU of Batna, and on 194 healthy witnesses of the
same age. The two groups were benefited by a dosage of the
concentration of the homocysteine vitamin B9 ,vitamin B12 , and
also of the study of special polymorphisms of indispensable enzymes
in the metabolism of this acid , and that by the use of the method (
Light cycler ) Real time PCR , on the following enzymes : MS (
C2756G ), MSR ( A66G ) ,MTHFR1 ( C677T ) and MTHFR2
(A1298C). The obtained results have revealed that the rate of the
homozygote muted genotype is the less frequent in the two groups ,
and that exist at list one genotype of each enzyme in the ill group and
in which the percentage exceed with remarkable way the same
genotype in the healthy group and we notice specially the muted
genotype GG of -the methionine synthetase-and the form TT of the
enzyme – methyline tetra hydrofolate reductase – We notice the
existence of considerable number of genotypes in the ill group lied
with characteristic increase of this Amino-acid ,and that for the
reduction of the biologic activity of these enzymes which become
inefficient in the transfer of the homocysteine into the methionine
and cause the diminution of the biologic activity of these enzymes
and with consequence the reduction of the percentage of methylic
radicals in the DNA of studied genes and that lead to the increase of
the activity and the capacity of transcription , and it-s so probably
that this last one is one of the factors of this disease especially if we
know that the specific check-up of vitamins is normal and similar in
the two groups , which ovoid the hypothesis of the reduction of
vitamins . We notice also that the heterozygote genotype is the less in
the sick category except the MTHFR2. Wild genotype is more
frequent in the witness group except MSR. Even these results are
partials; they open a new way in the genetic diagnosis of this
malicious disease which allow a precocious diagnosis and the use of
an effective and appropriated treatment in the same time.
Abstract: In this paper, genetic algorithm (GA) opmization technique is applied to design Flexible AC Transmission System (FACTS)-based damping controllers. Two types of controller structures, namely a proportional-integral (PI) and a lead-lag (LL) are considered. The design problem of the proposed controllers is formulated as an optimization problem and GA is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The proposed controllers are tested on a weakly connected power system subjected to different disturbances. The non-linear simulation results are presented to show the effectiveness of the proposed controller and their ability to provide efficient damping of low frequency oscillations. It is also observed that the proposed SSSC-based controllers improve greatly the voltage profile of the system under severe disturbances. Further, the dynamic performances of both the PI and LL structured FACTS-controller are analyzed at different loading conditions and under various disturbance condition as well as under unbalanced fault conditions..
Abstract: In this paper, a new Genetic Algorithm (GA) based
methodology is proposed to optimize the Degree of Hybridization
(DOH) in a passenger parallel hybrid car. At first step, target
parameters for the vehicle are decided and then using ADvanced
VehIcle SimulatOR (ADVISOR) software, the variation pattern of
these target parameters, across the different DOHs, is extracted. At
the next step, a suitable cost function is defined and is optimized
using GA. In this paper, also a new technique has been proposed for
deciding the number of battery modules for each DOH, which leads
to a great improvement in the vehicle performance. The proposed
methodology is so simple, fast and at the same time, so efficient.
Abstract: Load managing method on road became necessary
since overloaded vehicles occur damage on road facilities and existing
systems for preventing this damage still show many
problems.Accordingly, efficient managing system for preventing
overloaded vehicles could be organized by using the road itself as a
scale by applying genetic algorithm to analyze the load and the drive
information of vehicles.Therefore, this paper organized Ubiquitous
sensor network system for development of intelligent overload vehicle
regulation system, also in this study, to use the behavior of road, the
transformation was measured by installing underground box type
indoor model and indoor experiment was held using genetic algorithm.
And we examined wireless possibility of overloaded vehicle
regulation system through experiment of the transmission and
reception distance.If this system will apply to road and bridge, might
be effective for economy and convenience through establishment of
U-IT system..
Abstract: MMR vaccine failure had been reported globally and
here we report that it occurs now in India. Samples were collected from clinically suspected mumps cases were subjected for anti
mumps antibodies, virus isolation, RT-PCR, sequencing and
phylogenetic tree analysis. 56 samples collected from men and women belonging to various age groups. 30 had been vaccinated and
the status of 26 patients was unknown. 28 out of 30 samples were
found to be symptomatic and positive for Mumps IgM, indicating
active mumps infection in 93.4% of the vaccinated population. A
phylogenetic tree comparison of the clinical isolate is shown to be genotype C which is distinct from vaccine strain. Our study clearly sending warning signs that MMR vaccine is a failure and it needs to be revamped for the human use by increasing its efficacy and efficiency.
Abstract: This paper presents a systematic approach for
designing Static Synchronous Series Compensator (SSSC) based
supplementary damping controllers for damping low frequency
oscillations in a single-machine infinite-bus power system. The
design problem of the proposed controller is formulated as an
optimization problem and RCGA is employed to search for optimal
controller parameters. By minimizing the time-domain based
objective function, in which the deviation in the oscillatory rotor
speed of the generator is involved; stability performance of the
system is improved. Simulation results are presented and compared
with a conventional method of tuning the damping controller
parameters to show the effectiveness and robustness of the proposed
design approach.
Abstract: In this paper, we focus on the use of knowledge bases
in two different application areas – control of systems with unknown
or strongly nonlinear models (i.e. hardly controllable by the classical
methods), and robot motion planning in eight directions. The first
one deals with fuzzy logic and the paper presents approaches for
setting and aggregating the rules of a knowledge base. Te second one
is concentrated on a case-based reasoning strategy for finding the
path in a planar scene with obstacles.
Abstract: Several optimization algorithms specifically applied to
the problem of Operation Planning of Hydrothermal Power Systems
have been developed and are used. Although providing solutions to
various problems encountered, these algorithms have some
weaknesses, difficulties in convergence, simplification of the original
formulation of the problem, or owing to the complexity of the
objective function. Thus, this paper presents the development of a
computational tool for solving optimization problem identified and to
provide the User an easy handling. Adopted as intelligent
optimization technique, Genetic Algorithms and programming
language Java. First made the modeling of the chromosomes, then
implemented the function assessment of the problem and the
operators involved, and finally the drafting of the graphical interfaces
for access to the User. The program has managed to relate a coherent
performance in problem resolution without the need for
simplification of the calculations together with the ease of
manipulating the parameters of simulation and visualization of output
results.
Abstract: The Resource-Constrained Project Scheduling
Problem (RCPSP) is concerned with single-item or small batch
production where limited resources have to be allocated to dependent
activities over time. Over the past few decades, a lot of work has
been made with the use of optimal solution procedures for this basic
problem type and its extensions. Brucker and Knust[1] discuss, how
timetabling problems can be modeled as a RCPSP. Authors discuss
high school timetabling and university course timetabling problem as
an example. We have formulated two mathematical formulations of
course timetabling problem in a new way which are the prototype of
single-mode RCPSP. Our focus is to show, how course timetabling
problem can be transformed into RCPSP. We solve this
transformation model with genetic algorithm.
Abstract: Supply chain consists of all stages involved, directly
or indirectly, includes all functions involved in fulfilling a customer
demand. In two stage transportation supply chain problem,
transportation costs are of a significant proportion of final product
costs. It is often crucial for successful decisions making approaches
in two stage supply chain to explicit account for non-linear
transportation costs. In this paper, deterministic demand and finite
supply of products was considered. The optimized distribution level
and the routing structure from the manufacturing plants to the
distribution centres and to the end customers is determined using
developed mathematical model and solved by proposed particle
swarm optimization based genetic algorithm. Numerical analysis of
the case study is carried out to validate the model.