Abstract: The objective of this paper is to a design of pattern
classification model based on the back-propagation (BP) algorithm for
decision support system. Standard BP model has done full connection
of each node in the layers from input to output layers. Therefore, it
takes a lot of computing time and iteration computing for good
performance and less accepted error rate when we are doing some
pattern generation or training the network.
However, this model is using exclusive connection in between
hidden layer nodes and output nodes. The advantage of this model is
less number of iteration and better performance compare with standard
back-propagation model. We simulated some cases of classification
data and different setting of network factors (e.g. hidden layer number
and nodes, number of classification and iteration). During our
simulation, we found that most of simulations cases were satisfied by
BP based using exclusive connection network model compared to
standard BP. We expect that this algorithm can be available to
identification of user face, analysis of data, mapping data in between
environment data and information.
Abstract: The purpose of this study is to find natural gait of
biped robot such as human being by analyzing the COG (Center Of
Gravity) trajectory of human being's gait. It is discovered that human
beings gait naturally maintain the stability and use the minimum
energy. This paper intends to find the natural gait pattern of biped
robot using the minimum energy as well as maintaining the stability by
analyzing the human's gait pattern that is measured from gait image on
the sagittal plane and COG trajectory on the frontal plane. It is not
possible to apply the torques of human's articulation to those of biped
robot's because they have different degrees of freedom. Nonetheless,
human and 5-link biped robots are similar in kinematics. For this, we
generate gait pattern of the 5-link biped robot by using the GA
algorithm of adaptation gait pattern which utilize the human's ZMP
(Zero Moment Point) and torque of all articulation that are measured
from human's gait pattern. The algorithm proposed creates biped
robot's fluent gait pattern as that of human being's and to minimize
energy consumption because the gait pattern of the 5-link biped robot
model is modeled after consideration about the torque of human's each
articulation on the sagittal plane and ZMP trajectory on the frontal
plane. This paper demonstrate that the algorithm proposed is superior
by evaluating 2 kinds of the 5-link biped robot applied to each gait
patterns generated both in the general way using inverse kinematics
and in the special way in which by considering visuality and
efficiency.
Abstract: IT infrastructures are becoming more and more
difficult. Therefore, in the first industrial IT systems, the P2P
paradigm has replaced the traditional client server and methods of
self-organization are gaining more and more importance. From the
past it is known that especially regular structures like grids may
significantly improve the system behavior and performance. This
contribution introduces a new algorithm based on a biologic
analogue, which may provide the growth of several regular structures
on top of anarchic grown P2P- or social network structures.
Abstract: This paper proposes a method of adaptively generating a gait pattern of biped robot. The gait synthesis is based on human's gait pattern analysis. The proposed method can easily be applied to generate the natural and stable gait pattern of any biped robot. To analyze the human's gait pattern, sequential images of the human's gait on the sagittal plane are acquired from which the gait control values are extracted. The gait pattern of biped robot on the sagittal plane is adaptively generated by a genetic algorithm using the human's gait control values. However, gait trajectories of the biped robot on the sagittal plane are not enough to construct the complete gait pattern because the biped robot moves on 3-dimension space. Therefore, the gait pattern on the frontal plane, generated from Zero Moment Point (ZMP), is added to the gait one acquired on the sagittal plane. Consequently, the natural and stable walking pattern for the biped robot is obtained.