Abstract: This paper suggests a new internal architecture of
holon based on feature selection model using the combination of
Bees Algorithm (BA) and Artificial Neural Network (ANN). BA is
used to generate features while ANN is used as a classifier to
evaluate the produced features. Proposed system is applied on the
Wine dataset, the statistical result proves that the proposed system is
effective and has the ability to choose informative features with high
accuracy.
Abstract: Feature selection has been used in many fields such as
classification, data mining and object recognition and proven to be
effective for removing irrelevant and redundant features from the
original dataset. In this paper, a new design of distributed intrusion
detection system using a combination feature selection model based
on bees and decision tree. Bees algorithm is used as the search
strategy to find the optimal subset of features, whereas decision tree
is used as a judgment for the selected features. Both the produced
features and the generated rules are used by Decision Making Mobile
Agent to decide whether there is an attack or not in the networks.
Decision Making Mobile Agent will migrate through the networks,
moving from node to another, if it found that there is an attack on one
of the nodes, it then alerts the user through User Interface Agent or
takes some action through Action Mobile Agent. The KDD Cup 99
dataset is used to test the effectiveness of the proposed system. The
results show that even if only four features are used, the proposed
system gives a better performance when it is compared with the
obtained results using all 41 features.
Abstract: This paper presents a new meta-heuristic bio-inspired
optimization algorithm which is called Cuttlefish Algorithm (CFA).
The algorithm mimics the mechanism of color changing behavior of
the cuttlefish to solve numerical global optimization problems. The
colors and patterns of the cuttlefish are produced by reflected light
from three different layers of cells. The proposed algorithm considers
mainly two processes: reflection and visibility. Reflection process
simulates light reflection mechanism used by these layers, while
visibility process simulates visibility of matching patterns of the
cuttlefish. To show the effectiveness of the algorithm, it is tested with
some other popular bio-inspired optimization algorithms such as
Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and
Bees Algorithm (BA) that have been previously proposed in the
literature. Simulations and obtained results indicate that the proposed
CFA is superior when compared with these algorithms.
Abstract: In this paper, a new approach is introduced to solve
Blasius equation using parameter identification of a nonlinear
function which is used as approximation function. Bees Algorithm
(BA) is applied in order to find the adjustable parameters of
approximation function regarding minimizing a fitness function
including these parameters (i.e. adjustable parameters). These
parameters are determined how the approximation function has to
satisfy the boundary conditions. In order to demonstrate the
presented method, the obtained results are compared with another
numerical method. Present method can be easily extended to solve a
wide range of problems.
Abstract: In this paper, a novel method using Bees Algorithm is proposed to determine the optimal allocation of FACTS devices for maximizing the Available Transfer Capability (ATC) of power transactions between source and sink areas in the deregulated power system. The algorithm simultaneously searches the FACTS location, FACTS parameters and FACTS types. Two types of FACTS are simulated in this study namely Thyristor Controlled Series Compensator (TCSC) and Static Var Compensator (SVC). A Repeated Power Flow with FACTS devices including ATC is used to evaluate the feasible ATC value within real and reactive power generation limits, line thermal limits, voltage limits and FACTS operation limits. An IEEE30 bus system is used to demonstrate the effectiveness of the algorithm as an optimization tool to enhance ATC. A Genetic Algorithm technique is used for validation purposes. The results clearly indicate that the introduction of FACTS devices in a right combination of location and parameters could enhance ATC and Bees Algorithm can be efficiently used for this kind of nonlinear integer optimization.