Search results for: Fuzzy Cognitive Map (FCM)
975 Classification and Resolving Urban Problems by Means of Fuzzy Approach
Authors: F. Habib, A. Shokoohi
Abstract:
Urban problems are problems of organized complexity. Thus, many models and scientific methods to resolve urban problems are failed. This study is concerned with proposing of a fuzzy system driven approach for classification and solving urban problems. The proposed study investigated mainly the selection of the inputs and outputs of urban systems for classification of urban problems. In this research, five categories of urban problems, respect to fuzzy system approach had been recognized: control, polytely, optimizing, open and decision making problems. Grounded Theory techniques were then applied to analyze the data and develop new solving method for each category. The findings indicate that the fuzzy system methods are powerful processes and analytic tools for helping planners to resolve urban complex problems. These tools can be successful where as others have failed because both incorporate or address uncertainty and risk; complexity and systems interacting with other systems.
Keywords: Classification, complexity, Fuzzy theory, urban problems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2097974 Multivalued Knowledge-Base based on Multivalued Datalog
Authors: Agnes Achs
Abstract:
The basic aim of our study is to give a possible model for handling uncertain information. This model is worked out in the framework of DATALOG. The concept of multivalued knowledgebase will be defined as a quadruple of any background knowledge; a deduction mechanism; a connecting algorithm, and a function set of the program, which help us to determine the uncertainty levels of the results. At first the concept of fuzzy Datalog will be summarized, then its extensions for intuitionistic- and interval-valued fuzzy logic is given and the concept of bipolar fuzzy Datalog is introduced. Based on these extensions the concept of multivalued knowledge-base will be defined. This knowledge-base can be a possible background of a future agent-model.
Keywords: Fuzzy-, intuitionistic-, bipolar datalog, multivalued knowledge-base
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1142973 Passenger Seat Vibration Control of Quarter Car System with MR Shock Absorber
Authors: Devdutt, M. L. Aggarwal
Abstract:
Semi-active Fuzzy control of quarter car system having three degrees of freedom and assembled with magneto-rheological (MR) shock absorber is studied in present paper. First, experimental work was performed on an MR shock absorber under different excitation conditions to obtain force-displacement and force-velocity curves. Then, for the application of experimental data in semi-active quarter car system, a polynomial model was selected. Finally, Fuzzy logic controller was designed having the combination of Forward fuzzy controller and Inverse fuzzy controller for integration in secondary suspension system of concerned model. The proposed controlled quarter car model was compared with uncontrolled system using simulation work under bump type of road excitation. Results obtained by simulation work shows the effectiveness of fuzzy controlled suspension system in improving the ride comfort and safety of travelling passengers compared to uncontrolled suspension system.
Keywords: MR shock absorber, three degrees of freedom, quarter car model, fuzzy controller.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3286972 Performance Evaluation of Hybrid Intelligent Controllers in Load Frequency Control of Multi Area Interconnected Power Systems
Authors: Surya Prakash, Sunil Kumar Sinha
Abstract:
This paper deals with the application of artificial neural network (ANN) and fuzzy based Adaptive Neuro Fuzzy Inference System(ANFIS) approach to Load Frequency Control (LFC) of multi unequal area hydro-thermal interconnected power system. The proposed ANFIS controller combines the advantages of fuzzy controller as well as quick response and adaptability nature of ANN. Area-1 and area-2 consists of thermal reheat power plant whereas area-3 and area-4 consists of hydro power plant with electric governor. Performance evaluation is carried out by using intelligent controller like ANFIS, ANN and Fuzzy controllers and conventional PI and PID control approaches. To enhance the performance of intelligent and conventional controller sliding surface is included. The performances of the controllers are simulated using MATLAB/SIMULINK package. A comparison of ANFIS, ANN, Fuzzy, PI and PID based approaches shows the superiority of proposed ANFIS over ANN & fuzzy, PI and PID controller for 1% step load variation.Keywords: Load Frequency Control (LFC), ANFIS, ANN & Fuzzy, PI, PID Controllers, Area Control Error (ACE), Tie-line, MATLAB / SIMULINK.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3648971 Aircraft Gas Turbine Engines Technical Condition Identification System
Authors: A. M. Pashayev, C. Ardil, D. D. Askerov, R. A. Sadiqov, P. S. Abdullayev
Abstract:
In this paper is shown that the probability-statistic methods application, especially at the early stage of the aviation gas turbine engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence is considered the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods. Training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. Thus for GTE technical condition more adequate model making are analysed dynamics of skewness and kurtosis coefficients' changes. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows to draw conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. For checking of models adequacy is considered the Fuzzy Multiple Correlation Coefficient of Fuzzy Multiple Regression. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-bystage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine temperature condition was made.
Keywords: Gas turbine engines, neural networks, fuzzy logic, fuzzy statistics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1889970 LabVIEW with Fuzzy Logic Controller Simulation Panel for Condition Monitoring of Oil and Dry Type Transformer
Authors: N. A. Muhamad, S.A.M. Ali
Abstract:
Condition monitoring of electrical power equipment has attracted considerable attention for many years. The aim of this paper is to use Labview with Fuzzy Logic controller to build a simulation system to diagnose transformer faults and monitor its condition. The front panel of the system was designed using LabVIEW to enable computer to act as customer-designed instrument. The dissolved gas-in-oil analysis (DGA) method was used as technique for oil type transformer diagnosis; meanwhile terminal voltages and currents analysis method was used for dry type transformer. Fuzzy Logic was used as expert system that assesses all information keyed in at the front panel to diagnose and predict the condition of the transformer. The outcome of the Fuzzy Logic interpretation will be displayed at front panel of LabVIEW to show the user the conditions of the transformer at any time.Keywords: LabVIEW, Fuzzy Logic, condition monitoring, oiltransformer, dry transformer, DGA, terminal values.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3217969 Evaluation Pattern of Cognitive Processes in Language in Written Comprehension
Authors: Agnès Garletti
Abstract:
Our research aims at helping the tutor on line to evaluate the student-s cognitive processes. The student is a learner in French as a Second Language who studies an on-line socio-cognitive scenario in written communication. In our method, these cognitive processes are defined. For that, the language abilities and learning tasks are associated to cognitive operation. Moreover, the found cognitive processes are named with specific terms. The result was to create an instrumental pattern to question the learner about the cognitive processes used to build an item of written comprehension. Our research follows the principles of the third historical generation of studies on the cognitive activity of the text comprehension. The strength of our instrumental pattern stands in the precision and the logical articulation of the questions to the learner. However, the learner-s answers can still be subjective but the precision of the instrument restricts it.Keywords: Cognitive processes, Evaluation pattern, French as asecond language, Socio-cognitive scenario, Written comprehension.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1482968 Towards Automatic Recognition and Grading of Ganoderma Infection Pattern Using Fuzzy Systems
Authors: Mazliham Mohd Su'ud, Pierre Loonis, Idris Abu Seman
Abstract:
This paper deals with the extraction of information from the experts to automatically identify and recognize Ganoderma infection in oil palm stem using tomography images. Expert-s knowledge are used as rules in a Fuzzy Inference Systems to classify each individual patterns observed in he tomography image. The classification is done by defining membership functions which assigned a set of three possible hypotheses : Ganoderma infection (G), non Ganoderma infection (N) or intact stem tissue (I) to every abnormalities pattern found in the tomography image. A complete comparison between Mamdani and Sugeno style,triangular, trapezoids and mixed triangular-trapezoids membership functions and different methods of aggregation and defuzzification is also presented and analyzed to select suitable Fuzzy Inference System methods to perform the above mentioned task. The results showed that seven out of 30 initial possible combination of available Fuzzy Inference methods in MATLAB Fuzzy Toolbox were observed giving result close to the experts estimation.
Keywords: Fuzzy Inference Systems, Tomography analysis, Modelizationof expert's information, Ganoderma Infection pattern recognition
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1818967 Stability Analysis of Impulsive BAM Fuzzy Cellular Neural Networks with Distributed Delays and Reaction-diffusion Terms
Authors: Xinhua Zhang, Kelin Li
Abstract:
In this paper, a class of impulsive BAM fuzzy cellular neural networks with distributed delays and reaction-diffusion terms is formulated and investigated. By employing the delay differential inequality and inequality technique developed by Xu et al., some sufficient conditions ensuring the existence, uniqueness and global exponential stability of equilibrium point for impulsive BAM fuzzy cellular neural networks with distributed delays and reaction-diffusion terms are obtained. In particular, the estimate of the exponential convergence rate is also provided, which depends on system parameters, diffusion effect and impulsive disturbed intention. It is believed that these results are significant and useful for the design and applications of BAM fuzzy cellular neural networks. An example is given to show the effectiveness of the results obtained here.
Keywords: Bi-directional associative memory, fuzzy cellular neuralnetworks, reaction-diffusion, delays, impulses, global exponentialstability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1524966 Software Maintenance Severity Prediction with Soft Computing Approach
Authors: E. Ardil, Erdem Uçar, Parvinder S. Sandhu
Abstract:
As the majority of faults are found in a few of its modules so there is a need to investigate the modules that are affected severely as compared to other modules and proper maintenance need to be done on time especially for the critical applications. In this paper, we have explored the different predictor models to NASA-s public domain defect dataset coded in Perl programming language. Different machine learning algorithms belonging to the different learner categories of the WEKA project including Mamdani Based Fuzzy Inference System and Neuro-fuzzy based system have been evaluated for the modeling of maintenance severity or impact of fault severity. The results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The results show that Neuro-fuzzy based model provides relatively better prediction accuracy as compared to other models and hence, can be used for the maintenance severity prediction of the software.Keywords: Software Metrics, Fuzzy, Neuro-Fuzzy, SoftwareFaults, Accuracy, MAE, RMSE.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1568965 Modified Fuzzy PID Control for Networked Control Systems with Random Delays
Authors: Yong-can Cao, Wei-dong Zhang
Abstract:
To deal with random delays in Networked Control System (NCS), Modified Fuzzy PID Controller is introduced in this paper to implement real-time control adaptively. Via adjusting the control signal dynamically, the system performance is improved. In this paper, the design process and the ultimate simulation results are represented. Finally, examples and corresponding comparisons prove the significance of this method.
Keywords: Fuzzy Control, Networked Control System, PID, Random Delays
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1538964 Fuzzy PID Controller with Coupled Rules for a Nonlinear Quarter Car Model
Authors: Şaban Çetin, Özgür Demir
Abstract:
In this study, Fuzzy PID Control scheme is designed for an active suspension system. The main goal of an active suspension system for using in a vehicle model is reducing body deflections and handling high comfort for a passenger car. The present system was modelled as a two-degree-of-freedom (2-DOF) nonlinear vehicle model.Keywords: Active suspension system, Fuzzy PID controller, a nonlinear quarter car model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2381963 A Fuzzy Model and Tool to Analyze SIVD Diseases Using TMS
Authors: A. Faro, D. Giordano, M. Pennisi, G. Scarciofalo, C. Spampinato, F. Tramontana
Abstract:
The paper proposes a methodology to process the signals coming from the Transcranial Magnetic Stimulation (TMS) in order to identify the pathology and evaluate the therapy to treat the patients affected by demency diseases. In particular, a fuzzy model is developed to identify the demency of the patients affected by Subcortical Ischemic Vascular Dementia and to measure the positive effect, if any, of a repetitive TMS on their motor performances. A tool is also presented to support the mentioned analysis.
Keywords: TMS, SIVD, Electromiography , Fuzzy Logic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1560962 Automated Knowledge Engineering
Authors: Sandeep Chandana, Rene V. Mayorga, Christine W. Chan
Abstract:
This article outlines conceptualization and implementation of an intelligent system capable of extracting knowledge from databases. Use of hybridized features of both the Rough and Fuzzy Set theory render the developed system flexibility in dealing with discreet as well as continuous datasets. A raw data set provided to the system, is initially transformed in a computer legible format followed by pruning of the data set. The refined data set is then processed through various Rough Set operators which enable discovery of parameter relationships and interdependencies. The discovered knowledge is automatically transformed into a rule base expressed in Fuzzy terms. Two exemplary cancer repository datasets (for Breast and Lung Cancer) have been used to test and implement the proposed framework.Keywords: Knowledge Extraction, Fuzzy Sets, Rough Sets, Neuro–Fuzzy Systems, Databases
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1771961 Neuro-Fuzzy Network Based On Extended Kalman Filtering for Financial Time Series
Authors: Chokri Slim
Abstract:
The neural network's performance can be measured by efficiency and accuracy. The major disadvantages of neural network approach are that the generalization capability of neural networks is often significantly low, and it may take a very long time to tune the weights in the net to generate an accurate model for a highly complex and nonlinear systems. This paper presents a novel Neuro-fuzzy architecture based on Extended Kalman filter. To test the performance and applicability of the proposed neuro-fuzzy model, simulation study of nonlinear complex dynamic system is carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction of financial time series. A benchmark case studie is used to demonstrate that the proposed model is a superior neuro-fuzzy modeling technique.
Keywords: Neuro-fuzzy, Extended Kalman filter, nonlinear systems, financial time series.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2002960 Prediction Compressive Strength of Self-Compacting Concrete Containing Fly Ash Using Fuzzy Logic Inference System
Authors: O. Belalia Douma, B. Boukhatem, M. Ghrici
Abstract:
Self-compacting concrete (SCC) developed in Japan in the late 80s has enabled the construction industry to reduce demand on the resources, improve the work condition and also reduce the impact of environment by elimination of the need for compaction. Fuzzy logic (FL) approaches has recently been used to model some of the human activities in many areas of civil engineering applications. Especially from these systems in the model experimental studies, very good results have been obtained. In the present study, a model for predicting compressive strength of SCC containing various proportions of fly ash, as partial replacement of cement has been developed by using Fuzzy Inference System (FIS). For the purpose of building this model, a database of experimental data were gathered from the literature and used for training and testing the model. The used data as the inputs of fuzzy logic models are arranged in a format of five parameters that cover the total binder content, fly ash replacement percentage, water content, superplasticizer and age of specimens. The training and testing results in the fuzzy logic model have shown a strong potential for predicting the compressive strength of SCC containing fly ash in the considered range.
Keywords: Self-compacting concrete, fly ash, strength prediction, fuzzy logic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2837959 Aerial Firefighting Aircraft Selection with Standard Fuzzy Sets using Multiple Criteria Group Decision Making Analysis
Authors: C. Ardil
Abstract:
Aircraft selection decisions can be challenging due to their multidimensional and interdisciplinary nature. They involve multiple stakeholders with conflicting objectives and numerous alternative options with uncertain outcomes. This study focuses on the analysis of aerial firefighting aircraft that can be chosen for the Air Fire Service to extinguish forest fires. To make such a selection, the characteristics of the fire zones must be considered, and the capability to manage the logistics involved in such operations, as well as the purchase and maintenance of the aircraft, must be determined. The selection of firefighting aircraft is particularly complex because they have longer fleet lives and require more demanding operation and maintenance than scheduled passenger air service. This paper aims to use the fuzzy proximity measure method to select the most appropriate aerial firefighting aircraft based on decision criteria using multiple attribute decision making analysis. Following fuzzy decision analysis, the most suitable aerial firefighting aircraft is ranked and determined for the Air Fire Service.
Keywords: Aerial firefighting aircraft selection, multiple criteria decision making, fuzzy sets, standard fuzzy sets, determinate fuzzy sets, indeterminate fuzzy sets, proximity measure method, Minkowski distance family function, Hausdorff distance function, MCDM, PMM, PMM-F
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 360958 Parameter Selections of Fuzzy C-Means Based on Robust Analysis
Authors: Kuo-Lung Wu
Abstract:
The weighting exponent m is called the fuzzifier that can have influence on the clustering performance of fuzzy c-means (FCM) and mÎ[1.5,2.5] is suggested by Pal and Bezdek [13]. In this paper, we will discuss the robust properties of FCM and show that the parameter m will have influence on the robustness of FCM. According to our analysis, we find that a large m value will make FCM more robust to noise and outliers. However, if m is larger than the theoretical upper bound proposed by Yu et al. [14], the sample mean will become the unique optimizer. Here, we suggest to implement the FCM algorithm with mÎ[1.5,4] under the restriction when m is smaller than the theoretical upper bound.Keywords: Fuzzy c-means, robust, fuzzifier.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1637957 Fuzzy Logic Based Coordinated Voltage Control for Distribution Network with Distributed Generations
Authors: T. Juhana Hashim, A. Mohamed
Abstract:
This paper discusses the implementation of a fuzzy logic based coordinated voltage control for a distribution system connected with distributed generations (DGs). The connection of DGs has created a challenge for the distribution network operators to keep the voltage in the system within its acceptable limits. Intelligent centralized or coordinated voltage control schemes have proven to be more reliable due to its ability to provide more control and coordination with the communication with other network devices. In this work, voltage control using fuzzy logic by coordinating three methods of control, power factor control, on load tap changer and generation curtailment is implemented on a distribution network test system. The results show that the fuzzy logic based coordination is able to keep the voltage within its allowable limits.
Keywords: Coordinated control, Distributed generation, Fuzzy logic, Voltage control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3016956 Supervisory Fuzzy Learning Control for Underwater Target Tracking
Authors: C.Kia, M.R.Arshad, A.H.Adom, P.A.Wilson
Abstract:
This paper presents recent work on the improvement of the robotics vision based control strategy for underwater pipeline tracking system. The study focuses on developing image processing algorithms and a fuzzy inference system for the analysis of the terrain. The main goal is to implement the supervisory fuzzy learning control technique to reduce the errors on navigation decision due to the pipeline occlusion problem. The system developed is capable of interpreting underwater images containing occluded pipeline, seabed and other unwanted noise. The algorithm proposed in previous work does not explore the cooperation between fuzzy controllers, knowledge and learnt data to improve the outputs for underwater pipeline tracking. Computer simulations and prototype simulations demonstrate the effectiveness of this approach. The system accuracy level has also been discussed.Keywords: Fuzzy logic, Underwater target tracking, Autonomous underwater vehicles, Artificial intelligence, Simulations, Robot navigation, Vision system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1880955 Evolution of Performance Measurement Methods in Conditions of Uncertainty: The Implementation of Fuzzy Sets in Performance Measurement
Authors: E. A. Tkachenko, E. M. Rogova, V. V. Klimov
Abstract:
One of the basic issues of development management is connected with performance measurement as a prerequisite for identifying the achievement of development objectives. The aim of our research is to develop an improved model of assessing a company’s development results. The model should take into account the cyclical nature of development and the high degree of uncertainty in dealing with numerous management tasks. Our hypotheses may be formulated as follows: Hypothesis 1. The cycle of a company’s development may be studied from the standpoint of a project cycle. To do that, methods and tools of project analysis are to be used. Hypothesis 2. The problem of the uncertainty when justifying managerial decisions within the framework of a company’s development cycle can be solved through the use of the mathematical apparatus of fuzzy logic. The reasoned justification of the validity of the hypotheses made is given in the suggested article. The fuzzy logic toolkit applies to the case of technology shift within an enterprise. It is proven that some restrictions in performance measurement that are incurred to conventional methods could be eliminated by implementation of the fuzzy logic apparatus in performance measurement models.
Keywords: Fuzzy logic, fuzzy sets, performance measurement, project analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1064954 Identification of MIMO Systems Using Neuro-Fuzzy Models with a Shuffled Frog Leaping Algorithm
Authors: Sana Bouzaida, Anis Sakly, Faouzi M'Sahli
Abstract:
In this paper, a TSK-type Neuro-fuzzy Inference System that combines the features of fuzzy sets and neural networks has been applied for the identification of MIMO systems. The procedure of adapting parameters in TSK model employs a Shuffled Frog Leaping Algorithm (SFLA) which is inspired from the memetic evolution of a group of frogs when seeking for food. To demonstrate the accuracy and effectiveness of the proposed controller, two nonlinear systems have been considered as the MIMO plant, and results have been compared with other learning methods based on Particle Swarm Optimization algorithm (PSO) and Genetic Algorithm (GA).Keywords: Identification, Shuffled frog Leaping Algorithm (SFLA), TSK-type neuro-fuzzy model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1758953 Performance Analysis of ERA Using Fuzzy Logic in Wireless Sensor Network
Authors: Kamalpreet Kaur, Harjit Pal Singh, Vikas Khullar
Abstract:
In Wireless Sensor Network (WSN), the main limitation is generally inimitable energy consumption during processing of the sensor nodes. Cluster head (CH) election is one of the main issues that can reduce the energy consumption. Therefore, discovering energy saving routing protocol is the focused area for research. In this paper, fuzzy-based energy aware routing protocol is presented, which enhances the stability and network lifetime of the network. Fuzzy logic ensures the well-organized selection of CH by taking four linguistic variables that are concentration, energy, centrality, and distance to base station (BS). The results show that the proposed protocol shows better results in requisites of stability and throughput of the network.
Keywords: ERA, fuzzy logic, network model, WSN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 865952 Characteristics of Cognitive Functions among Polish Adolescence with Spelling Disorders
Authors: Izabela Pietras
Abstract:
The level of visual abilities, language, memory processes and intellectual functioning development affects the quality of a written text. The following analysis will present the results of diagnostic tests indicating the most common criterion for a group and stating whether a person has been diagnosed with having cognitive developmental level below the group-s average or not.The study-s aim is to determine whether there are specific patterns of cognitive deficits, which can be distinguished among the group of young people with spelling disorders.Keywords: cognitive deficits, cognitive functions, spellingdisorders
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1374951 Application of Intuitionistic Fuzzy Cross Entropy Measure in Decision Making for Medical Diagnosis
Authors: Shikha Maheshwari, Amit Srivastava
Abstract:
In medical investigations, uncertainty is a major challenging problem in making decision for doctors/experts to identify the diseases with a common set of symptoms and also has been extensively increasing in medical diagnosis problems. The theory of cross entropy for intuitionistic fuzzy sets (IFS) is an effective approach in coping uncertainty in decision making for medical diagnosis problem. The main focus of this paper is to propose a new intuitionistic fuzzy cross entropy measure (IFCEM), which aid in reducing the uncertainty and doctors/experts will take their decision easily in context of patient’s disease. It is shown that the proposed measure has some elegant properties, which demonstrates its potency. Further, it is also exemplified in detail the efficiency and utility of the proposed measure by using a real life case study of diagnosis the disease in medical science.
Keywords: Intuitionistic fuzzy cross entropy (IFCEM), intuitionistic fuzzy set (IFS), medical diagnosis, uncertainty.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2031950 Reliability Analysis of k-out-of-n : G System Using Triangular Intuitionistic Fuzzy Numbers
Authors: Tanuj Kumar, Rakesh Kumar Bajaj
Abstract:
In the present paper, we analyze the vague reliability of k-out-of-n : G system (particularly, series and parallel system) with independent and non-identically distributed components, where the reliability of the components are unknown. The reliability of each component has been estimated using statistical confidence interval approach. Then we converted these statistical confidence interval into triangular intuitionistic fuzzy numbers. Based on these triangular intuitionistic fuzzy numbers, the reliability of the k-out-of-n : G system has been calculated. Further, in order to implement the proposed methodology and to analyze the results of k-out-of-n : G system, a numerical example has been provided.
Keywords: Vague set, vague reliability, triangular intuitionistic fuzzy number, k-out-of-n : G system, series and parallel system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2970949 Complex Condition Monitoring System of Aircraft Gas Turbine Engine
Authors: A. M. Pashayev, D. D. Askerov, C. Ardil, R. A. Sadiqov, P. S. Abdullayev
Abstract:
Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE workand output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.Keywords: aviation gas turbine engine, technical condition, fuzzy logic, neural networks, fuzzy statistics
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2522948 Improved C-Fuzzy Decision Tree for Intrusion Detection
Authors: Krishnamoorthi Makkithaya, N. V. Subba Reddy, U. Dinesh Acharya
Abstract:
As the number of networked computers grows, intrusion detection is an essential component in keeping networks secure. Various approaches for intrusion detection are currently being in use with each one has its own merits and demerits. This paper presents our work to test and improve the performance of a new class of decision tree c-fuzzy decision tree to detect intrusion. The work also includes identifying best candidate feature sub set to build the efficient c-fuzzy decision tree based Intrusion Detection System (IDS). We investigated the usefulness of c-fuzzy decision tree for developing IDS with a data partition based on horizontal fragmentation. Empirical results indicate the usefulness of our approach in developing the efficient IDS.Keywords: Data mining, Decision tree, Feature selection, Fuzzyc- means clustering, Intrusion detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1564947 A Type-2 Fuzzy Model for Link Prediction in Social Network
Authors: Mansoureh Naderipour, Susan Bastani, Mohammad Fazel Zarandi
Abstract:
Predicting links that may occur in the future and missing links in social networks is an attractive problem in social network analysis. Granular computing can help us to model the relationships between human-based system and social sciences in this field. In this paper, we present a model based on granular computing approach and Type-2 fuzzy logic to predict links regarding nodes’ activity and the relationship between two nodes. Our model is tested on collaboration networks. It is found that the accuracy of prediction is significantly higher than the Type-1 fuzzy and crisp approach.Keywords: Social Network, link prediction, granular computing, Type-2 fuzzy sets.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1560946 Strict Stability of Fuzzy Differential Equations with Impulse Effect
Authors: Sanjay K.Srivastava, Bhanu Gupta
Abstract:
In this paper some results on strict stability heve beeb extended for fuzzy differential equations with impulse effect using Lyapunov functions and Razumikhin technique.
Keywords: Fuzzy differential equations, Impulsive differential equations, Strict stability, Lyapunov function, Razumikhin technique.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1456