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In this study integer genetic algorithm is applied for path planning of mobile robot in the grid form environment. The novel representation is proposed for definition of chromosome which reduced the computational complexity of genetic algorithm that was used before for path planning. Comparison with other encoding of chromosome is done to show the capability of proposed algorithm. Mamadani fuzzy rule...
There are many features that make music composition a challenging task for computer science. In this paper we investigate the suitability of using genetic algorithms and Kohonen musical grammar for task of music composition, and ability of these systems to cope with challenging aspects of music. Genetic algorithms are used as a tool to combine musical ideas which models the combination-theory of creativity...
This paper has developed a sliding mode controller (SMC) based on a radial basis function model for control of magnetic levitation system. Adaptive neural networks controllers need plant's Jacobain, but here this problem solved by sliding surface and generalized learning rule in case to eliminate Jacobain problem. The simulation results show that this method is feasible and more effective for magnetic...
Creativity has a fundamental role in music composition. One of the theories, which exist about creativity, is combination-theory. In this paper the suitability of genetic algorithms and recurrent neural networks for modeling this theory is considered. We discuss that two phases of combination occurs: one at the genetic algorithm level, and the other at the network level. One important challenge in...
In this study integer genetic algorithm is applied for path planning of mobile robot in the grid form environment. The novel representation is proposed for definition of chromosome which reduced the computational complexity of genetic algorithm which was used before for path planning. Comparison with other encoding of chromosome is done to show the capability of proposed algorithm. Another genetic...
In this study a strain gage load cell as a S model has been designed which is used for measuring weight of elevator. Four methods of fixing and balancing Whetstone Bridge were considered and one way was achieved eventually which was given the best Whetstone Bridge's output. For amplifying and measuring of changing resistance and voltage in Whetstone Bridge four current ways of amplifying and measuring...
In this study, a new group method of data handling (GMDH) method, based on adaptive neurofuzzy inference system (ANFIS) structure, called ANFIS-GMDH and its application for diabetes mellitus forecasting is presented. Conventional neurofuzzy GMDH (NF-GMDH) uses radial basis network (RBF) as the partial descriptions. In this study the RBF partial descriptions are replaced with two input ANFIS structures...
In this paper designing of multi-objective PID controller for load frequency control (LFC) based on adaptive weighted particle swarm optimization (AWPSO) has been proposed. Conventional methods such as Ziegler-Nichols and Cohen-Coon are based on trial-and-error and their best performances are achieved for first-order process. Single-objective population based methods such as genetic algorithm (GA)...
In this study, using a model reference adaptation law, a stable fuzzy neural control system is developed. Despite the advantages of Model reference control design technique, which is mainly its power to exactly set trajectories of the system under control, this method is designed for linear system. In this study using fuzzy neural systems, a stable model reference controller for nonlinear systems...
This paper introduces a new hybrid approach for training the adaptive network based fuzzy inference system (ANFIS) and a new type of particle swarm optimizers (PSO). The previous works emphasized on gradient base method or least square (LS) based method. This study applied one of the swarm intelligent branches, PSO. The hybrid method composes fuzzy PSO with recursive least square (RLS) for training...
Premature ventricular contraction (PVC) beats are of great importance in evaluating and predicting life threatening ventricular arrhythmias. The aim of this study is to improve the diagnosis level of detection of Premature Ventricular Contraction arrhythmia from ECG signals. This improvement is based on an appropriate choice of features for the selected task. We extracted fourteen features including,...
Using the SOA would be as an economic dynamo to transform the legacy business processes to the matured and unbundled E-Services. While there are some differences in between the definitions of E-things in Developing Countries and Developed Countries, the concept of SOA is inferred as the same. The SOA is being used in the e-governments, e-governances, e-commerce, and e-businesses projects and plans...
The non-dominate sorting genetic algorithmic-II (NSGA-II) is a relatively recent technique for finding or approximating the Pareto-optimal set for multi-objective optimization problems. In different studies NSGA-II has shown good performance in comparison to other multi-objective evolutionary algorithms (Deb et al., 2002). In this paper an improved version which is named Niching-NSGA-II (n-NSGA-II)...
Use of multi-objective particle swarm optimization for designing of planar multilayered electromagnetic absorbers and finding optimal Pareto front is described. The achieved Pareto presents optimal possible trade offs between thickness and reflection coefficient of absorbers. Particle swarm optimization method in comparison with most of optimization algorithms such as genetic algorithms is simple...
Swarm intelligence, as demonstrated by natural biological swarm, such as ant colony, has numerous powerful properties desirable in many engineering systems, specially network routing. Efficient routing in communication network is becoming increasingly difficult due to the increasing size, rapidly changing topology, and complexity of communication networks. The complexity involved in the networks may...
In this study a new combination of nonlinear backstepping scheme with off-line fuzzy system is presented for controlling a rotary inverted pendulum system to achieve better performance in nonlinear controller. The inverted pendulum, a popular mechatronic application, exists in many different forms. The common thread among these systems is their goal: to balance a link on end using feedback control...
In this paper a decoupled sliding-mode with fuzzy neural network controller for a nonlinear system is presented. To divided into two subsystems to achieve asymptotic stability by decoupled method for a class of three order nonlinear system. The fuzzy neural network (FNN) is the main regulator controller, which is used to approximate an ideal computational controller. The compensation controller is...
According to the non-stationary characteristics of ball bearing fault vibration signals, a ball bearing fault diagnosis method based on wavelet and empirical mode decomposition (EMD), energy entropy mean is put forward in this paper. Firstly, original acceleration vibration signals are decomposed into a finite number of stationary intrinsic mode functions (IMFs) and wavelet components, then the concept...
In this article particle swarm optimization that is a population-based method is applied to train the matrix parameters that are standard deviation and centers of radial basis function fuzzy neural network. We have applied least square and recursive least square in training the weights of this fuzzy neural network.There are four sets of data used to examine and prove that particle swarm optimization...
This paper introduces a new hybrid approach for training the adaptive network based fuzzy inference system (ANFIS).This approach based on multi objective optimization mechanism for training parameters in antecedent part. It considers two cost functions as the objectives which are the maximum difference measurements between the real nonlinear system and the nonlinear model, and training mean square...
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