Many Intelligent techniques were established during last decades to handle nonlinear, multimode, noisy, nondifferentiable problems and to obtain optimum solution(s). This paper presents improving and implementations for two recently intelligent techniques; Type-2 Fuzzy System (T2 FS) and Particle Swarm Optimization (PSO) and presents a new method to optimize parameters of the primary membership functions of T2 FS by PSO to improve the performance and increase the accuracy of T2 FS model. The implementation of the suggested method on mean blood pressure estimation has very successful rate. © 2007 IEEE
The type-2 fuzzy set (T2FS) is introduced to circumvent the limitations of the type-1 fuzzy set (T1F...
This paper proposes a modified particle swarm optimization (PSO) algorithm that can be used to solve...
This paper presents a novel fuzzy particle swarm optimization with cross-mutated (FPSOCM) operation,...
Optimization is essential for applications since it can improve the results provided in different ar...
A dynamic adjustment of parameters for the particle swarm optimization (PSO) utilizing an interval t...
The use of artificial intelligence techniques such as fuzzy logic, neural networks and evolutionary ...
In this paper, a comparison among Particle swarm optimization (PSO), Bee Colony Optimization (BCO) a...
In this paper, the optimal designs of type-1 and interval type-2 fuzzy systems for the classificatio...
This paper discusses a method for improving accuracy of fuzzy-rule-based classifiers using particle ...
A neuro fuzzy hybrid model (NFHM) is proposed as a new artificial intelligence method to classify bl...
An innovative hybrid stages particle swarm optimization (HSPSO) learning method, contains fuzzy c-me...
Blood pressure parameters; Systolic, Diastolic and Mean Blood Pressure, have high correlation relati...
Information about the status of disease (prognosis) for patients with hepatitis is important to dete...
This paper introduces a novel fuzzy adaptive optimization strategy (FAOPSO) for the particle swarm a...
This paper presents a novel fuzzy particle swarm optimization with cross-mutated operation (FPSOCM),...
The type-2 fuzzy set (T2FS) is introduced to circumvent the limitations of the type-1 fuzzy set (T1F...
This paper proposes a modified particle swarm optimization (PSO) algorithm that can be used to solve...
This paper presents a novel fuzzy particle swarm optimization with cross-mutated (FPSOCM) operation,...
Optimization is essential for applications since it can improve the results provided in different ar...
A dynamic adjustment of parameters for the particle swarm optimization (PSO) utilizing an interval t...
The use of artificial intelligence techniques such as fuzzy logic, neural networks and evolutionary ...
In this paper, a comparison among Particle swarm optimization (PSO), Bee Colony Optimization (BCO) a...
In this paper, the optimal designs of type-1 and interval type-2 fuzzy systems for the classificatio...
This paper discusses a method for improving accuracy of fuzzy-rule-based classifiers using particle ...
A neuro fuzzy hybrid model (NFHM) is proposed as a new artificial intelligence method to classify bl...
An innovative hybrid stages particle swarm optimization (HSPSO) learning method, contains fuzzy c-me...
Blood pressure parameters; Systolic, Diastolic and Mean Blood Pressure, have high correlation relati...
Information about the status of disease (prognosis) for patients with hepatitis is important to dete...
This paper introduces a novel fuzzy adaptive optimization strategy (FAOPSO) for the particle swarm a...
This paper presents a novel fuzzy particle swarm optimization with cross-mutated operation (FPSOCM),...
The type-2 fuzzy set (T2FS) is introduced to circumvent the limitations of the type-1 fuzzy set (T1F...
This paper proposes a modified particle swarm optimization (PSO) algorithm that can be used to solve...
This paper presents a novel fuzzy particle swarm optimization with cross-mutated (FPSOCM) operation,...