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Themain aim of this paper is to use fuzzy inference systems for controlling the relevant parameters within the equations of the FWA algorithm. In other words, parameters that are considered constant in the traditional FWA and are now made dynamic by using fuzzy logic. It is worth mentioning that we also made a small modification to the algorithm with the goal of having a better performance and the...
The main goal of the work presented in the paper is to introduce the use of fuzzy logic in the Grey Wolf Optimizer (GWO) algorithm specifically for dynamic simultaneous adaptation of the key parameters, which are crucial in the performance of the metaheuristic. The proposed approach for this modification of GWO using fuzzy logic is presented. In addition, a brief comparison between the traditional...
The software presented in this paper is an implementation of an intuitionistic fuzzy inference system. Such type of fuzzy inference systems provide an extra layer of uncertainty, called indeterminacy, that the user can integrate in the antecedents and consequents of the fuzzy system. The additional calculations required to make an inference in this type of system needs a negligible extra amount of...
In this article we propose the use of fuzzy systems for dynamic adjustment of parameters in the galactic swarm optimization (GSO) method. This algorithm is inspired by the movement of stars, galaxies and superclusters of galaxies under the force of gravity. GSO uses various cycles of exploration and exploitation phases to achieve a trade-off between the exploration of new solutions and exploitation...
Interactive evolutionary computation systems can be used to evolve advertisement texts. Google AdWords was used as the interface that users can use to see the advertisement texts, and have a chance of being persuaded by the text into clicking them. Interactive evolutionary computation systems use humans to perform fitness evaluation in the evolutionary process, which can be applied on a genetic algorithm...
In this work a new metaheuristic of optimization bio-inspired on the plants self-defense techniques applied to optimization problems is presented. Plants are living beings that are part of a habitat, and in some recent works the authors claim that plants are able to react to different external stimuli. In nature, plants are exposed to a variety of predatory animals such as bacteria, fungi, insect...
In this paper, a comparison of the Choquet and Sugeno integrals is presented. The proposed methods enable the calculation of the Choquet and Sugeno integrals to combine multiple source of information with a degree of uncertainty. The methods are used to combine the modules output of a modular neural network for face recognition and a comparison is performed. In this paper, the focus is on aggregation...
In this paper we consider the Differential Evolution (DE) algorithm by using fuzzy logic to make dynamic changes in the mutation parameter (F), and this modification of the algorithm we call the Fuzzy Differential Evolution algorithm (FDE). A comparison of the FDE algorithm using type 1 fuzzy logic and interval type-2 fuzzy logic is performed for a set of Benchmark functions.
In this paper we propose the use of fuzzy systems for dynamic adjustment of parameters of the imperialist competitive algorithm (ICA). This algorithm is inspired by the concept of imperialism; where powerful countries try to make a colony of other countries. We developed different fuzzy systems one with the Beta parameter and another using a combination with the Beta and Xi parameters to measure the...
Edge detection is an essential step used in image processing systems and can be applied to image sets before the training phase in pattern recognition systems to improve performance. An edge detector simplifies the analysis of the images; because, it reduces the data to be processed by highlighting the most important features. In this paper we show the advantage of using a fuzzy edge detector method...
An improved methodology for parameter adaptation in GSA (Gravitational Search Algorithm) is presented in where we use a fuzzy system to control the abilities of GSA to perform a global and local search. The results show that with our methodology GSA can outperform the quality of the results when compared with the original method and some other GSA improvements.
In this paper we propose a new method for dynamic parameter adaptation in the bat algorithm (BA). BA is a metaheuristic algorithm inspired by the behavior of micro bats, which has been applied to different optimization problems obtaining good results. In this paper we propose dynamic parameter adaptation of the BA using Interval Type-2 fuzzy logic. Simulation results show that the proposed method...
Google Adwords has a bidding price optimization scheme for its campaigns, where the user proposes the maximum bidding price, and then Adwords adapts the final bidding price according to the performance of a particular campaign. This paper proposes a bidding price controller based on a fuzzy system. Specifically, two approaches are considered: a type-1 fuzzy inference system, and an interval type-2...
In this article we use the Differential Evolution (DE) algorithm which using fuzzy logic has the mutation parameter (F) dynamic, this modification of the algorithm we call Fuzzy Differential Evolution algorithm (FDE), a comparison algorithm using type 1 fuzzy logic and interval type 2 fuzzy logic is performed by for a set of functions Benchmark.
In this paper we propose a new method based on an interval type-2 fuzzy logic system for dynamic parameter adaptation in the harmony search (HS) algorithm. The main contribution of this paper is an improvement of HS in its abilities to search in a global and local fashion, by dynamically changing some of its parameters using an interval type-2 fuzzy logic system. The fuzzy harmony search algorithm...
A hybrid system composed by a generalized Type-2 Fuzzy Logic System (GT2FLS) and a fuzzy Bee Colony Optimization (FBCO) algorithm for the dynamic adaptation in the alpha and beta parameters is presented in this paper. The Bee Colony Optimization meta-heuristic belongs to the class of Nature-Inspired Algorithms. The objective of the work is the analysis of the approach with Generalized Type-2 Fuzzy...
We describe in this paper the architecture of a modular neural network (MNN) for pattern recognition. More recently, the study of modular neural network techniques theory has been receiving significant attention. The design of a recognition system also requires careful attention. The paper aims to use the Ant Colony paradigm to optimize the architecture of this Modular Neural Network for pattern recognition...
This work describes a method to construct type-1 intuitionistic fuzzy inference systems. This type of systems is able to handle more uncertainty than a type-1 fuzzy inference system and performs faster than a type-2 fuzzy inference system. The concepts of intuitionistic membership, and intuitionistic center of area are proposed, in order to implement a system which is similar in design than the traditional...
The main goal of the paper is the use of fuzzy logic for dynamic parameter adaptation in the Grey Wolf Optimizer (GWO) algorithm. The proposed approach of a fuzzy GWO is compared with the traditional GWO algorithm with a set of benchmark functions. Simulation results show that there is a significant advantage of the proposed fuzzy GWO.
In this paper, a new classification method based on LVQ neural networks and Fuzzy Logic is presented. This new fuzzy LVQ method (FuzzLVQ) mainly focuses on distances between the input vector and the cluster centers, randomly generated, thus the fuzzy system in the FuzzLVQ method is used to determine the shortest distance, and with this information, the cluster center can be approached to input vector...
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