In this study, basic methodologies of the GA and the scaling
procedures are summarized, the scaling criteria of real time history
records to satisfy the Syrian design code are discussed. The
traditional time domain scaling procedures and the scali
ng
procedures using GA are utilized to scale a number of the available
real records to match the Syrian design spectra. The resulting time histories of the procedures are investigated and compared in terms of meeting criteria.
The goal of this study is to model human body correctly, according to the principles and the standards
used to calculate the humanoid parameters. The model is built by using VN software and then it was
implemented in Matlab Simulink, in order to bu
ild a control system for simulating the humanoid balance
during standing. Precise and robust balance was reached by using PID controller with parameters
optimized by using genetic algorithm (GA). The control performance was tested by applying external
disturbance to the humanoid, the results show that the humanoid can retrieve its balance effectively.
Cold formed steel (CFS) has many advantages over other construction materials.
CFS members are lightweight. They weigh up to 30-35% less than their wood
counterparts.. This makes CFS members economical and the same time very easy to erect
and inst
all. They may be shaped (cold-bent) to nearly any open cross section. This allows
for the use of optimization technique’s to find optimal shapes for the members’ cross
sections.
The research aims to show the genetic algorithm's ability in determining the optimum
dimensions cold formed C section. To do so, the optimum design mathematical
formulation was formulated by adding the manufacturing constraints that reflect the
section folding operations in addition the geometrical and structural constraints.
The research found that the genetic algorithm is effective tool in finding the best
solution to this issue, as it showed its ability to deal with asymmetric section through
reaching solutions conform to the basic principles of mechanics of material.
The algorithm is adjustable, so that it can implement the design restrictions which are
compatible with any codes or any manufacturing requirements imposed by modulation
techniques.
In the Multi-objective Traveling Salesman Problem (moTSP)
simultaneous optimization of more than one objective functions is
required. This paper proposes hybrid algorithm to solve the multiobjectives
Traveling Salesman problem through the integration of
the ant colony optimization algorithm with the Genetic algorithm.
This study has reached to that ANN (5-9-1) (five neurons in input
layer_nine neurons in hidden layer _ one neuron in output layer) is the
optimum artificial network that hybrid system has reached to it with
mean squared error equals (1*10^-4) (0.7
m3/sec), where this software
has summed up millions of experiments in one step and in limited time, it
has also given a zero value of a number of network connections, such as
some connections related of relative humidity input because of the lake
of impact this parameter on the runoff when other parameters are
avaliable.
This study recommend to use this technique in forecasting of
evaporation and other climatic elements.
Thin walled Steel products are very much used in the construction industry, where it
is cold formed from uniform thickness steel plates. This study aims at determining the
optimal section of cold formed thin walled lipped C compressed member under
the effect
of several levels of axial force using Genetic Algorithm.
The research found that the genetic algorithm is able to resolve the issue of the
optimal design of studied column with high efficiency, accuracy. Also it found that the
torsional flexural buckling constraint and the overall buckling constraint in x-direction are
the effective constraints in case of long height.
The study recommends restudying the same issue as a multi objective optimization
problem by adding additional objective functions which are the overall buckling in x&y
directions.
This paper aims to reduce the power losses and to enhance the
voltage profile of the power system while maintaining the loading of the
transmission lines within the allowable limits, through the optimal
placement of the Unified Power Flow Controller (UPFC).
The main objective of this research is to present a study on the design optimization of the 6-RUS Stewart platform.
The geometric and kinematic models are calculated and the singular positions are determined, then its translation and orientation wor
kspace are determining. The direct geometric model of the studied platform was determined by using a proposed hybrid method.
In this research, a hybrid system was proposed between the
genetic algorithm and the fuzzy Kohonen clustering network ,
where the genetic algorithm is one of the methods of artificial
intelligence is one of the modern methods.
In this paper, it has
merged two techniques of the artificial intelligent, they are the
ants colony optimization algorithm and the genetic algorithm, to
The recurrent reinforcement learning trading system
optimization. The proposed trading system
is based on an ant
colony optimization algorithm and the genetic algorithm to
select an optimal group of technical indicators, and fundamental
indicators.
