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Application of Fuzzy Logic to Cognitive Radio Systems

2009 IEICE transactions on communications  
This paper reviews applications of fuzzy logic to telecommunications and proposes a novel fuzzy combining scheme for cooperative spectrum sensing in cognitive radio systems.  ...  A summary of previous applications of fuzzy logic to telecommunications is given outlining also potential applications of fuzzy logic in future cognitive radio systems.  ...  Acknowledgments This work has been carried out in the framework of the Cognitive and Opportunistic Wireless Communication Networks (COGNAC) project which is partially funded by the Finnish Funding Agency for  ... 
doi:10.1587/transcom.e92.b.3572 fatcat:ajwyrnzj4ndubdladsra4oo47a

INN: An Interpretable Neural Network for AI Incubation in Manufacturing

Xiaoyu Chen, Yingyan Zeng, Sungku Kang, Ran Jin
2022 ACM Transactions on Intelligent Systems and Technology  
In this research, we propose an interpretable neural network (INN) model with a center-adjustable Sigmoid activation function to efficiently optimize the rule-based systems.  ...  The proposed INN will be effective for supervised learning problems when rule-based systems are available.  ...  These human-crafted rules associated with the combination logic are then used to construct a rule-based system, which is composed of a rule-base (i.e., a collection of features and associated thresholds  ... 
doi:10.1145/3519313 fatcat:mh6ssslxcre27e3kvse25hr4mu

Performance Analysis of a Semiactive Suspension System with Particle Swarm Optimization and Fuzzy Logic Control

Abroon Jamal Qazi, Clarence W. de Silva, Afzal Khan, Muhammad Tahir Khan
2014 The Scientific World Journal  
A fuzzy logic controller is incorporated into the semi-active suspension system. It is able to handle nonlinearities through the use of heuristic rules.  ...  This paper uses a quarter model of an automobile having passive and semiactive suspension systems to develop a scheme for an optimal suspension controller.  ...  Sahar Noor for their  ... 
doi:10.1155/2014/174102 pmid:24574868 pmcid:PMC3915550 fatcat:3x7w4reez5bsvpu5zibt5uyqae


I. Khalifa, A. El-Assal, M. Saleh
1998 The International Conference on Electrical Engineering  
The paper presents a novel approach for the application of adaptive fuzzy logic control' algorithm.  ...  A real time nonlinear dynamic system is used to ensure the effectiveness of tAe proposed control scheme.  ...  1=1 i=1 for all / =1,2,...M where g ( ) is the desired output of the fuzzy logic system for input x(1), and f ( ) that is, we choose the number of rules in the optimal fuzzy logic system equal to the  ... 
doi:10.21608/iceeng.1998.60074 fatcat:teauzsm6lbeljp36wybwjq6ixy

Determination of Optimal Parameter in Deep Drawing Process by Using Fuzzy Logic Method

Pawan Ashok Ghormode
It is helpful for determine optimal combination of process parameters.  ...  This paper discusses flexible approaches for fuzzy optimization problems. Specifically, it presents a new solving method in deep drawing process.  ...  Optimal combination of process parameters for deep drawing based on fuzzy which gives accurate influencing parameter are as follows.  ... 
doi:10.18535/ijetst/v3i08.14 fatcat:ffyqxnwnnbf3bpwcenxn2pvvp4

Definition Of Optimal Drought-Oriented Reservoir Management Policies Combining Stochastic Programming And Fuzzy Logic

Hector Macian-Sorribes, Manuel Pulido-Velazquez
2016 Zenodo  
Mathematical representation of the system operating rules linking the system state (inputs) and the management decisions (outputs), providing a free environment Fuzzy Rule-Based system (FRB) METHODS  ...  Recursion REOPTIMIZATION Fuzzy inputs Fuzzy rules Fuzzy outputs Fuzzy system SIMULATION Comparison of results Storages Inflows Each discrete combination is a rule Discrete  ...  Drought economic impacts can be reduced by the adoption of improved operating policies based on stochastic programming (avoiding the perfect foresight) Fuzzy logic provides a flexible environment to  ... 
doi:10.5281/zenodo.49745 fatcat:d2rl2hlu4bgo3nbeu4dbmccmni

Fuzzy Logic Speech/Non-speech Discrimination for Noise Robust Speech Processing [chapter]

R. Culebras, J. Ramírez, J. M. Górriz, J. C. Segura
2006 Lecture Notes in Computer Science  
The fuzzy system is based on a Sugeno inference engine with membership functions defined as combination of two Gaussian functions.  ...  This paper shows a fuzzy logic speech/non-speech discrimination method for improving the performance of speech processing systems working in noise environments.  ...  This paper shows an effective VAD based on fuzzy logic rules for low-delay speech communications.  ... 
doi:10.1007/11758501_55 fatcat:kbwkem3kjncrnixzaibswrszlq

A framework for autonomic, ontology-based IT management

Fabian Meyer, Reinhold Kroeger
2015 2015 11th International Conference on Network and Service Management (CNSM)  
In this paper, dedicated solutions for each of those problems will be presented and combined into a comprehensive, ontology-based management framework.  ...  The proposed approach has been experimentally validated in a case study of a medium-sized management problem for an air traffic management system.  ...  It deploys a copy of the rule engine and the knowledge base, trying to optimize the configuration of the managed system by simulating and evaluating different action chains.  ... 
doi:10.1109/cnsm.2015.7367342 dblp:conf/cnsm/MeyerK15 fatcat:f6q5prm6obgcxa4bguhqtnc3wq

Host based Anomaly Detection using Fuzzy Genetic Approach (FGA)

Harjinder Kaur, Nivit Gill
2013 International Journal of Computer Applications  
The paper proposes to detect anomalous user behavior on a single machine based on the system log files using fuzzy logic and genetic algorithms.  ...  Intrusion is a fast growing security threat to the computers which fails the security of the system.  ...  Earlier combination of fuzzy logic and genetic algorithms has been used successfully for network based intrusion detection [6] .  ... 
doi:10.5120/13024-0026 fatcat:gfav4w23grfefh2t4avmuobhdq

Improving the Performance of Inconsistent Knowledge Bases via Combined Optimization Method [chapter]

Yong Ma, David C. Wilkins
1991 Machine Learning Proceedings 1991  
One of the important issues when designing effective expert systems is the validation and refinement of the acquired knowledge bases. bases both on the training sets and on the validation sets. 1  ...  Acknowledgements We like to thank Seth Hutchinson for providing Sun CPU time for our experiments. We also thank mous reviewers for comments and suggestions. anony- .  ...  A knowledge base refinement problem is a special kind of optimization problem whose objective is to optimize the system performance over a given set of cases, subject to certain constraints, e.g., syntactic  ... 
doi:10.1016/b978-1-55860-200-7.50009-x dblp:conf/icml/MaW91 fatcat:jhre3nz33zdglkcdyyiityjcqe

Progress in on-line adaptive, learning and evolutionary strategies for fuzzy logic control

Minrui Fei, S.L. Ho
1999 Proceedings of the IEEE 1999 International Conference on Power Electronics and Drive Systems. PEDS'99 (Cat. No.99TH8475)  
Hence a systematic way of combination and hybridizaticin of these strategies will be very useful for improving the learning capacity and performance of algorithms based on these strategies.  ...  It is concluded that the orientation of deep-going pathfinding in the generation and modification of fuzzy control rules or models which is principally based on neural networks combined with genetic algorithms  ...  Wen and et a1.(1998) introduced genetic algorithms to design an optimal fuzzy logic excitation controller for a generating unit.  ... 
doi:10.1109/peds.1999.792863 fatcat:wjwgvmbyzzcadm7d74gqh7onoe

An Optimal Fuzzy Logic System for a Nonlinear Dynamic System Using a Fuzzy Basis Function

SherifKamel Hussein, Mahmoud Hanafy Saleh
2016 International Journal of Computer Networks & Communications  
The impetus for this paper is the development of Fuzzy Basis Function "FBF" that assigns in an optimal fashion, a function approximation for a nonlinear dynamic system.  ...  error for the fuzzy rules.  ...  Fuzzy Logic System The Fuzzy-Logic Control " FLC" comprises three stages namely Fuzzifier, Rule-base and Defuzzifier.  ... 
doi:10.5121/ijcnc.2016.8215 fatcat:txyr64tgfzdxrnfmmbwn2oobsm

Genetic optimization of type-1, interval and intuitionistic fuzzy recognition systems

Patricia Melin
2018 Notes on Intuitionistic Fuzzy Sets  
In this paper a new method for fuzzy system optimization is presented.  ...  The results obtained show the effectiveness of the proposed method for designing optimal structures of fuzzy systems.  ...  The best fuzzy inference system for this case is using type-1 fuzzy logic, Sugeno type, using 12 fuzzy rules out of 20 possible fuzzy rules.  ... 
doi:10.7546/nifs.2018.24.2.106-128 fatcat:v2uooiwmyvhnfd56a5osr636gu

A Cooperative Spectrum Sensing Scheme Using Fuzzy Logic for Cognitive Radio Networks

Thuc Kieu-Xuan
2010 KSII Transactions on Internet and Information Systems  
A fuzzy logic rule -based inference system is proposed to estimate the presence possibility of the licensed user's signal based on the observed energy at each cognitive radio terminal.  ...  This paper proposes a novel scheme for cooperative spectrum sensing on distributed cognitive radio networks.  ...  In [8] , a new combining scheme for cognitive spectrum sensing based on fuzzy logic has been proposed.  ... 
doi:10.3837/tiis.2010.06.006 fatcat:6h6vexne7fajpemhxnjbzjhn2i

Design and Implementation of an Optimal Fuzzy Logic Controller Using Genetic Algorithm

Sheroz Khan, Salami Femi Abdulazeez, Lawal Wahab Adetunji, AHM Zahirul Alam, Momoh Jimoh E. Salami, Shihab Ahmed Hameed, Aisha Hasan Abdalla, Mohd Rafiqul Islam
2008 Journal of Computer Science  
Present study was based on a software approach which was focusing on an algorithmic approach for programming a PIC16F877A microcontroller, for eliminating altogether the parametric dependence issues while  ...  Said approach was first simulated using MATLAB/SIMULINK using the techniques of Proportional Derivative Fuzzy Logic Controller (PD-FLC) whose membership function, fuzzy logic rules and scaling gains were  ...  The GA-optimized fuzzy logic rules for the fuzzy inference system are shown in Table 5 .  ... 
doi:10.3844/jcssp.2008.799.806 fatcat:4ct5zumtofbpjf4fxktpi7qj64
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