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Solving Graph Coloring Problem by Fuzzy Clustering-Based Genetic Algorithm
[chapter]
2012
Lecture Notes in Computer Science
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coloring problem using a fuzzy clustering based evolutionary approach to reduce the cost of the eva1uation. ...
The graph coloring problem is one of famous combinatoria1 optimization problerns. ...
In this paper, we present a fuzzy clustering-based genetic algorithm to reduce the cost of coloring problem. ...
doi:10.1007/978-3-642-34859-4_35
fatcat:ild2e66u4zf7jp74kahwlkl7i4
Applying Hopfield Neural Networks To Solve CSP Problems
2020
International Journal of Advanced Trends in Computer Science and Engineering
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The first attempt to apply this type of neural network to solving the CSP problem was made by Hopfield himself, after which a number of modifications of the original algorithm took place. ...
The article reviews methods based on the Hopfield neural network for solving CSP and FCSP problems. ...
GENET and Fuzzy GENET The GENET algorithm was introduced to the world by Wang i Tsang in 1991 [6] and was a logical extension of GDS networks. As in GDS, here neurons are divided into clusters. ...
doi:10.30534/ijatcse/2020/77942020
fatcat:3tiavgn5djfdvjwdryqrdbwiv4
Using fuzzy c-means clustering algorithm for common lecturers timetabling among departments
2016
2016 6th International Conference on Computer and Knowledge Engineering (ICCKE)
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The problem's evaluation metric is evaluated via using fuzzy c-means clustering algorithm on common lecturer constraints within a multi agent system. ...
problem. ...
Another hybrid approach has also been proposed to solve UCTTP problem using genetic algorithm by [14] which reduces the cost of finding the number of minimum required colors to color a graph with this ...
doi:10.1109/iccke.2016.7802147
fatcat:mntq6ajp2beqbjaai2t2j3vmhi
Designing And Implementing A Distributed Genetic Algorithm For Optimizing Work Modes In Wireless Sensor Network
2014
Journal of Mathematics and Computer Science
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In this paper it is tried to present a solution for optimizing energy consumption in the sensors of wireless network by using distributed genetic algorithm and solving the famous problem of graph coloration ...
. this idea formed by modeling sensors of wireless network by the help of graph and posing the problems of graph coloration with the description of work groups in scheduling nodes in wireless sensor networks ...
In this model, sensor nodes are changed into different group to the graphs center coloration problem and to solve this problem, we use Genetic Algorithm. sensors nodes placing in one group, are placed ...
doi:10.22436/jmcs.011.04.04
fatcat:r7vqa5c2jjbnfcdguqzhxzxkze
A novel approach to classificatory problem using neuro-fuzzy architecture
2011
International Journal of Systems Control and Communications
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This algorithm is optimized by Genetic Algorithms. We tested the algorithm on the famous classificatory problem of picture learning. ...
The method is inspired from the neuro-fuzzy logic approach to problem solving. ...
The algorithms try to optimize the performance in clustering by designing various models based on the architecture of neuro-fuzzy systems [1, 2, 3, 16, 18 and 22] . ...
doi:10.1504/ijscc.2011.042432
fatcat:xbvtjanjgfbidcyxbt6vepbleq
A Review of Challenges in Clustering Techniques for Image Segmentation
2020
International Journal for Research in Applied Science and Engineering Technology
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This paper deals with the cluster based image segmentation methods as it gives a new way of mathematical pattern to identify regions in an image. ...
The paper presents an extensive review of clustering algorithms, which includes clustering algorithms and their improved versions. ...
This classification is obtained by solving the cluster problem by the objective function, which tells that if the appropriate partitioning is achieved or not. ...
doi:10.22214/ijraset.2020.32534
fatcat:y4bgxswtjfapxccqgh2sxue6vy
Cell Production System Design: A Literature Review
2021
International Journal of Innovation in Management, Economics and Social Sciences
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Cell production system design methods include clustering, graph theory, artificial intelligence, meta-heuristic, simulation, mathematical programming. ...
Methodology: To examine these methods, from 187 articles published in this field by authoritative scientific sources, based on the year of publication and the number of restrictions considered and close ...
They also used a genetic algorithm to solve the problem [84] . ...
doi:10.52547/ijimes.1.1.16
fatcat:4uqwiqqfd5e5po2xw4ii2spd5e
A genetically optimized graph-based people extraction method for embedded transportation systems real conditions
2014
17th International IEEE Conference on Intelligent Transportation Systems (ITSC)
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It is based on an image superpixel segmentation coupled with graph cuts binary clustering, initialized by a stateof-the-art foreground detection method. ...
Since many state-of-the-art methods can be considered in our three first blocks along with many associated parameters, a genetic algorithm is used to automatically find the best methods and parameters ...
• Step of graph-cut clustering: L 1 norm based on the RGB color information. ...
doi:10.1109/itsc.2014.6957920
dblp:conf/itsc/ConiglioMLB14
fatcat:yjwa7c4ejfht7ahdlh6zybvif4
A Survey on Color Image Enhancement Techniques
2013
IOSR Journal of Engineering
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When fuzzy concepts are used for color image enhancement it creates visual artifacts. ...
Improving visual clarity of an image is conveniently achieved by various contrast enhancement techniques. Histogram equalization results in excess contrast enhancement. ...
Dorigo has defined Ant Colony Optimization (ACO) meta-heuristic by applying first to solve the problem of travelling salesman problem to find minimal length Hamiltonian circuit on the graph. ...
doi:10.9790/3021-03222024
fatcat:rpia3u7hmjfvnks54bhasskxya
MMFO: modified moth flame optimization algorithm for region based RGB color image segmentation
2020
International Journal of Electrical and Computer Engineering (IJECE)
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The region-based color image segmentation has faced the problem of multidimensionality. ...
This paper introduced an improved algorithm MMFO (Modified Moth Flame Optimization) Algorithm for RGB color image Segmentation which is based on bio-inspired techniques for color image segmentation. ...
The Genetic-based clustering algorithm cluster the different color by draw graph of the 'a*'and 'b*' values of pixels that were segmented into different colors. ...
doi:10.11591/ijece.v10i1.pp196-201
fatcat:tbdjwggpwnesfiriffgmivhfiy
OPTIMIZING FUZZY CLUSTER ENSEMBLE IN STRING REPRESENTATION
2013
International journal of pattern recognition and artificial intelligence
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The de¯ned nonlinear model can be solved by every nonlinear optimizer; however; we used genetic algorithm to solve it. ...
In this paper, we present a novel optimization-based method for the combination of cluster ensembles. The information among the ensemble is formulated in 0-1 bit strings. ...
Acknowledgments This work was supported in part by the Research Institute for ICTÀITRC grant program. We would like to appreciate the ITRC for this support. ...
doi:10.1142/s0218001413500055
fatcat:5jywkjrf5vekvc52xsogppen6q
A CLUSTERED WIRELESS SENSOR NETWORK BASED AIR POLLUTION MONITORING SYSTEM WITH SWARM INTELLIGENCE BASED DATA AGGREGATION
2016
Jurnal Teknologi
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The data aggregation using the hybrid genetic algorithm is also proposed in this paper for efficient data transmission by reducing the communication overhead. ...
The sensor nodes in the networks are grouped into clusters and the cluster head is selected using the optimization algorithm such as firefly algorithm. ...
Optimal Path Selection Using Hybrid Genetic Algorithm Based on Fuzzy Logic
Traditional Genetic Algorithm The traditional genetic algorithm is used to resolve the problems in many fields. ...
doi:10.11113/jt.v78.5742
fatcat:xd75op4gard4bg37jgzyfvj5am
An Analytical Study for the Role of Fuzzy Logic in Improving Metaheuristic Optimization Algorithms
2019
Journal of Automation, Mobile Robotics & Intelligent Systems
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Since neuro fuzzy logic poses feasible options for solving numerous research problems, hence a section is also included by the authors to present an analytical study regarding research in it. ...
Also, the top 3 fuzzy evolutionary algorithms are extracted and their top research papers are mentioned along with their topmost research domain. ...
Lee, A Fuzzy Genetic Algorithm Based on Binary Encoding for Solving Multidimensional Knapsack Problems. Journal of Applied Mathematics, 2012, DOI: 10.1155/2012/703601. [82] A.R. Babaei, M. ...
doi:10.14313/jamris_4-2018/22
fatcat:xtpnt4iccrd4jau6eni5qujere
A Review on Image Segmentation Techniques and Performance Measures
2018
Zenodo
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It remains a fundamental problem in computer vision. ...
To justify the relevance of our analysis, recent algorithms of segmentation are presented through the proposed classification. ...
Constructing a graph with an image can solve the segmentation problem by using techniques for graph cuts in graph theory [18] .
L. ...
doi:10.5281/zenodo.2579975
fatcat:4e7i5u3lyjbltec2qrdqppwkui
Image Segmentation based on Fuzzy Genetic Algorithm
2016
International Journal of Engineering and Technology
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In this paper a new Fuzzy Genetic (FG) algorithm is introduce. ...
Fuzzy c-means (FCM) is unsupervised segmentation technique that has been successfully applied to future analysis, clustering, and classification but the FCM and its derivative algorithms suffer from various ...
Various techniques are used to enhance the original image without losing its original properties. steps in solving a problem by using Fuzzy genetic algorithm are: 1) Chromosome representation 2) Population ...
doi:10.21817/ijet/2016/v8i4/160804404
fatcat:agey25mgxradpekmd43nr5swea
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