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Fuzzy neuro-genetic approach for feature selection and image classification in augmented reality systems

Rajendra Thilahar C., Sivaramakrishnan R.
2019 IAES International Journal of Robotics and Automation  
For this purpose, we propose a three layer fuzzy neural network that has been implemented based on weight adjustments using fuzzy rules in the convolutional neural networks with genetic algorithm for effective  ...  For feature detection, extraction and selection, the proposed model uses a fuzzy logic based incremental feature selection algorithm which has been proposed in this work in order to recognize the important  ...  In image processing applications, fuzzy temporal rules can be combined with genetic algorithms for performing optimization in the process of feature selection and thus reducing the classification time  ... 
doi:10.11591/ijra.v8i3.pp194-204 fatcat:fkszhgmdh5eexp3hbkwycfbbqa

Genetic-fuzzy rule mining approach and evaluation of feature selection techniques for anomaly intrusion detection

Chi-Ho Tsang, Sam Kwong, Hanli Wang
2007 Pattern Recognition  
In addition, the proposed system can also act as a genetic feature selection wrapper to search for an optimal feature subset for dimensionality reduction.  ...  The proposed fuzzy rule-based system is evolved from an agent-based evolutionary framework and multi-objective optimization.  ...  Acknowlegment The work described in this paper was supported by a grant from City University Strategic Grant 7001955.  ... 
doi:10.1016/j.patcog.2006.12.009 fatcat:m3spcbzhgjd7jnp2jy4f2pjdzq

Intelligent feature selection and classification techniques for intrusion detection in networks: a survey

Sannasi Ganapathy, Kanagasabai Kulothungan, Sannasy Muthurajkumar, Muthusamy Vijayalakshmi, Palanichamy Yogesh, Arputharaj Kannan
2013 EURASIP Journal on Wireless Communications and Networking  
In addition to the survey on existing intelligent techniques for intrusion detection systems, two new algorithms namely intelligent rule-based attribute selection algorithm for effective feature selection  ...  In this paper, a survey on intelligent techniques for feature selection and classification for intrusion detection in networks based on intelligent software agents, neural networks, genetic algorithms,  ...  In addition, a new feature selection algorithm called Intelligent Rule based Attribute Selection algorithm and a novel classification algorithm named Intelligent Rule-based Enhanced Multiclass Support  ... 
doi:10.1186/1687-1499-2013-271 fatcat:njt5czb7mzhuzlnovhha376kpq

A Classifier Model based on the Features Quantitative Analysis for Facial Expression Recognition

Amir Jamshidnezhad, Md Jan Nordin
2011 International Journal on Advanced Science, Engineering and Information Technology  
In this paper, quantitative analysis is used in order to find the most effective features movements between the selected facial feature points.  ...  In recent decades computer technology has considerable developed in use of intelligent systems for classification.  ...  The knowledge base (KB) is divided into two components: Fuzzy rule base and Genetic Algorithm.  Fuzzy Rule Based System Rule base is made based on the empirical studies of changing the feature extracted  ... 
doi:10.18517/ijaseit.1.4.81 fatcat:pwsauhv5abbbdm6eruhxlc4xxi

Sign Gesture Recognition Using Modified Region Growing Algorithm and Adaptive Genetic Fuzzy Classifier

Rajesh Kaluri, Pradeep Ch
2016 International Journal of Intelligent Engineering and Systems  
We have used Genetic algorithm with Fuzzy classifier to find out the optimal rules generated by Fuzzy classifier.  ...  Modified Region Growing Algorithm (MRGA), feature extraction and recognition using Adaptive Genetic Fuzzy Classifier (AGFC).  ...  In our proposed system, the fuzzy rules are formulated based on the feature vector values and these rules are further subjected to optimization for better classification.  ... 
doi:10.22266/ijies2016.1231.24 fatcat:fuobyoemi5c6pica7mplcdjed4

Mining traffic accident features by evolutionary fuzzy rules

Pavel Kromer, Tibebe Beshah, Dejene Ejigu, Vaclav Snasel, Jan Platos, Ajith Abraham
2013 2013 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS)  
In this study, we investigate a data set describing traffic accidents in Ethiopia and use a machine learning method based on artificial evolution and fuzzy systems to mine symbolic description of selected  ...  features of the data set.  ...  There are simple fuzzy classifiers as well as complex rule-based fuzzy classification systems that usually build and maintain sophisticated rule bases.  ... 
doi:10.1109/civts.2013.6612287 dblp:conf/civts/KromerBESPA13 fatcat:2bw5enbxfrcbnjkfol3vqjzkry

Breast Tumors Diagnosis Using Fuzzy Inference System and Fuzzy C-Means Clustering

Ahmed Shihab Ahmed, Omer Nather Basheer, Hussein Ali Salah
2021 International Scientific Journal of Computing  
In this paper the robust classification method is presented, that attempts to classify the tissue suspicion region as normal or not normal by using a Fuzzy Inference System (FIS) using the Fuzzy C-Mean  ...  based on normal DB case, 243 rules based on benign case, 243 rules based on malignant case), after that the best Eighteen rules are selected (best 6 rules based on normal DB case, best 6 rules based on  ...  In this work, a fuzzy system hybrid with fuzzy mean clustering along with a genetic algorithm is used to match shapes.  ... 
doi:10.47839/ijc.20.4.2443 fatcat:bw2h5gf5ijcwbmdzpm5wrry6gq

Computational Intelligence for Network Intrusion Detection: Recent Contributions [chapter]

Asim Karim
2005 Lecture Notes in Computer Science  
These contributions present the success and potential of computational intelligence in network intrusion detection systems for tasks such as feature selection, signature generation, anomaly detection,  ...  classification, and clustering.  ...  The generation of fuzzy rules or signatures from anomaly traffic is described in [9] . These rules serve as negative selectors in an immunity-based intrusion detection system.  ... 
doi:10.1007/11596448_25 fatcat:n6vcx2x5gbbk7dzqaf5bb5hoxq

Design of a Fuzzy-based Decision Support System for Coronary Heart Disease Diagnosis

Adel Lahsasna, Raja Noor Ainon, Roziati Zainuddin, Awang Bulgiba
2012 Journal of medical systems  
In the present paper, a fuzzy rule-based system (FRBS) is designed to serve as a decision support system for Coronary heart disease (CHD) diagnosis that not only considers the decision accuracy of the  ...  Furthermore, employing ECS has specifically improved the ability of FRBS to detect patients with CHD which is desirable feature for any CHD diagnosis system.  ...  Fuzzy Optimization This step aims at: (1) maximize the classification accuracy and (2) minimize the number of fuzzy rules in the fuzzy rule-based system.  ... 
doi:10.1007/s10916-012-9821-7 pmid:22252606 fatcat:e5uiqhfpd5fvvpog2dlgy5xmum

A Training Model For Fuzzy Classification System

Amir Jamshid Nezhad
2011 Zenodo  
Also, with the purpose of making better performance of fuzzy rule based system, Genetic learning Processes designed for parameter optimization to improve the accuracy and robustness of the system under  ...  The core of expression recognition system is a Mamdani-type fuzzy rule based system to model mathematically the natural conditions.  ...  Fuzzy Rule Based System Rule base is made based on the empirical studies of changing the feature extracted from neutral to one emotion expression.  ... 
doi:10.5281/zenodo.812101 fatcat:oggsgvv7hbghpekwshryifga2y

Data Mining, Soft Computing, Machine Learning and BioInspired Computing for Heart Disease Classification/ Prediction – A Review

M. Rathi, B. Narasimhan
2017 International Journal of Advanced Research in Computer Science and Software Engineering  
Several mechanisms namely apriori algorithm, frequent itemset mining, support vector machine, neural network, classification and regression trees, fuzzy rule-based clinical decision support system, k-nearest  ...  neighbor, genetic algorithm, scoring system, nature language processing (NLP) techniques, type-2 fuzzy logic system, decision tree and statistical methods are used to classify heart disease prediction  ...  Soft computing is a fusion of research in evolutionary algorithms and genetic programming, neural science and neural net systems, fuzzy set theory and fuzzy systems, and chaos theory and chaotic systems  ... 
doi:10.23956/ijarcsse/v7i4/0156 fatcat:6umrnxncxve55ejgzpkhaeoxpy

Hybrid soft computing systems for electromyographic signals analysis: a review

Hong-Bo Xie, Tianruo Guo, Siwei Bai, Socrates Dokos
2014 BioMedical Engineering OnLine  
Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis.  ...  in EMG analysis.  ...  The use of fixed geometric-shaped membership functions in fuzzy logic limits system knowledge more in the rule base than in the membership function base, resulting in requiring more system memory and processing  ... 
doi:10.1186/1475-925x-13-8 pmid:24490979 pmcid:PMC3922626 fatcat:uifnqy6tmfe4nbnkif2fwmun44

A Multiobjective Genetic Algorithm for Feature Selection and Data Base Learning in Fuzzy-Rule Based Classification Systems [chapter]

O. Cordón, F. Herrera, M.J. del Jesus, L. Magdalena, A.M. Sánchez, P. Villar
2003 Intelligent Systems for Information Processing  
In this contribution, we propose a genetic process to select an appropiate set of features in a Fuzzy Rule-Based Classification System (FRBCS) and to automatically learn the whole Data Base definition.  ...  An FRBCS is an automatic classification system that uses fuzzy rules as knowledge representation tool. Two different components are distinguished within it: 1. The KB, composed of:  ...  The works proposed in [6, 7, 8] use Simulated Annealing and GAs to learn an appropiate DB in a Fuzzy Rule-Based System.  ... 
doi:10.1016/b978-044451379-3/50026-1 fatcat:hujxjp4dirbddoubtn66ud4x5i

A Hybrid Nested Genetic-Fuzzy Algorithm Framework for Intrusion Detection and Attacks

Ramy Elhefnawy, Hassan Abounaser, Amr Badr
2020 IEEE Access  
INDEX TERMS Intrusion detection system, evolutionary computation, fuzzy logic systems, genetic algorithms, hybrid intelligent systems, classification algorithms. 98218 This work is licensed under a Creative  ...  The outer is to evolve fuzzy sets and the inner is to evolve fuzzy rules.  ...  Fuzzy Logic Systems (FLS) or Fuzzy Rule-Based Systems (FRBS) have robust features that tolerate imprecision and uncertainty, and therefore, perform rule-based classification efficiently and effectively  ... 
doi:10.1109/access.2020.2996226 fatcat:noalfy4tqfbrpcff34374khiii

Selecting fuzzy if-then rules for classification problems using genetic algorithms

H. Ishibuchi, K. Nozaki, N. Yamamoto, H. Tanaka
1995 IEEE transactions on fuzzy systems  
This paper proposes a genetic-algorithm-based method for selecting a small number of significant fuzzy if-then rules to construct a compact fuzzy classification system with high classification power.  ...  Genetic algorithms are applied to this problem. A set of fuzzy if-then rules is coded into a string and treated as an individual in genetic algorithms.  ...  CONCLUDING REMARKS In this paper, we proposed a genetic-algorithm-based method for selecting significant fuzzy if-then rules to construct a compact fuzzy classification system with high classification  ... 
doi:10.1109/91.413232 fatcat:wcu5mmugdzcvnfirj6264neb4i
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