Search results for: fuzzy reasoning
920 A Monte Carlo Fuzzy Logistic Regression Framework against Imbalance and Separation
Authors: Georgios Charizanos, Haydar Demirhan, Duygu Icen
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Two of the most impactful issues in classical logistic regression are class imbalance and complete separation. These can result in model predictions heavily leaning towards the imbalanced class on the binary response variable or over-fitting issues. Fuzzy methodology offers key solutions for handling these problems. However, most studies propose the transformation of the binary responses into a continuous format limited within [0,1]. This is called the possibilistic approach within fuzzy logistic regression. Following this approach is more aligned with straightforward regression since a logit-link function is not utilized, and fuzzy probabilities are not generated. In contrast, we propose a method of fuzzifying binary response variables that allows for the use of the logit-link function; hence, a probabilistic fuzzy logistic regression model with the Monte Carlo method. The fuzzy probabilities are then classified by selecting a fuzzy threshold. Different combinations of fuzzy and crisp input, output, and coefficients are explored, aiming to understand which of these perform better under different conditions of imbalance and separation. We conduct numerical experiments using both synthetic and real datasets to demonstrate the performance of the fuzzy logistic regression framework against seven crisp machine learning methods. The proposed framework shows better performance irrespective of the degree of imbalance and presence of separation in the data, while the considered machine learning methods are significantly impacted.Keywords: fuzzy logistic regression, fuzzy, logistic, machine learning
Procedia PDF Downloads 63919 A Development of Holonomic Mobile Robot Using Fuzzy Multi-Layered Controller
Authors: Seungwoo Kim, Yeongcheol Cho
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In this paper, a holonomic mobile robot is designed in omnidirectional wheels and an adaptive fuzzy controller is presented for its precise trajectories. A kind of adaptive controller based on fuzzy multi-layered algorithm is used to solve the big parametric uncertainty of motor-controlled dynamic system of 3-wheels omnidirectional mobile robot. The system parameters such as a tracking force are so time-varying due to the kinematic structure of omnidirectional wheels. The fuzzy adaptive control method is able to solve the problems of classical adaptive controller and conventional fuzzy adaptive controllers. The basic idea of new adaptive control scheme is that an adaptive controller can be constructed with parallel combination of robust controllers. This new adaptive controller uses a fuzzy multi-layered architecture which has several independent fuzzy controllers in parallel, each with different robust stability area. Out of several independent fuzzy controllers, the most suited one is selected by a system identifier which observes variations in the controlled system parameter. This paper proposes a design procedure which can be carried out mathematically and systematically from the model of a controlled system. Finally, the good performance of a holonomic mobile robot is confirmed through live tests of the tracking control task.Keywords: fuzzy adaptive control, fuzzy multi-layered controller, holonomic mobile robot, omnidirectional wheels, robustness and stability.
Procedia PDF Downloads 351918 Enhancement of MIMO H₂S Gas Sweetening Separator Tower Using Fuzzy Logic Controller Array
Authors: Muhammad M. A. S. Mahmoud
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Natural gas sweetening process is a controlled process that must be done at maximum efficiency and with the highest quality. In this work, due to complexity and non-linearity of the process, the H₂S gas separation and the intelligent fuzzy controller, which is used to enhance the process, are simulated in MATLAB – Simulink. The new design of fuzzy control for Gas Separator is discussed in this paper. The design is based on the utilization of linear state-estimation to generate the internal knowledge-base that stores input-output pairs. The obtained input/output pairs are then used to design a feedback fuzzy controller. The proposed closed-loop fuzzy control system maintains the system asymptotically-stability while it enhances the system time response to achieve better control of the concentration of the output gas from the tower. Simulation studies are carried out to illustrate the Gas Separator system performance.Keywords: gas separator, gas sweetening, intelligent controller, fuzzy control
Procedia PDF Downloads 463917 Case-Based Reasoning Approach for Process Planning of Internal Thread Cold Extrusion
Authors: D. Zhang, H. Y. Du, G. W. Li, J. Zeng, D. W. Zuo, Y. P. You
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For the difficult issues of process selection, case-based reasoning technology is applied to computer aided process planning system for cold form tapping of internal threads on the basis of similarity in the process. A model is established based on the analysis of process planning. Case representation and similarity computing method are given. Confidence degree is used to evaluate the case. Rule-based reuse strategy is presented. The scheme is illustrated and verified by practical application. The case shows the design results with the proposed method are effective.Keywords: case-based reasoning, internal thread, cold extrusion, process planning
Procedia PDF Downloads 504916 Interval Type-2 Fuzzy Vibration Control of an ERF Embedded Smart Structure
Authors: Chih-Jer Lin, Chun-Ying Lee, Ying Liu, Chiang-Ho Cheng
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The main objective of this article is to present the semi-active vibration control using an electro-rheological fluid embedded sandwich structure for a cantilever beam. ER fluid is a smart material, which cause the suspended particles polarize and connect each other to form chain. The stiffness and damping coefficients of the ER fluid can be changed in 10 micro seconds; therefore, ERF is suitable to become the material embedded in the tunable vibration absorber to become a smart absorber. For the ERF smart material embedded structure, the fuzzy control law depends on the experimental expert database and the proposed self-tuning strategy. The electric field is controlled by a CRIO embedded system to implement the real application. This study investigates the different performances using the Type-1 fuzzy and interval Type-2 fuzzy controllers. The Interval type-2 fuzzy control is used to improve the modeling uncertainties for this ERF embedded shock absorber. The self-tuning vibration controllers using Type-1 and Interval Type-2 fuzzy law are implemented to the shock absorber system. Based on the resulting performance, Internal Type-2 fuzzy is better than the traditional Type-1 fuzzy control for this vibration control system.Keywords: electro-rheological fluid, semi-active vibration control, shock absorber, type 2 fuzzy control
Procedia PDF Downloads 442915 An Investigation into Fraud Detection in Financial Reporting Using Sugeno Fuzzy Classification
Authors: Mohammad Sarchami, Mohsen Zeinalkhani
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Always, financial reporting system faces some problems to win public ear. The increase in the number of fraud and representation, often combined with the bankruptcy of large companies, has raised concerns about the quality of financial statements. So, investors, legislators, managers, and auditors have focused on significant fraud detection or prevention in financial statements. This article aims to investigate the Sugeno fuzzy classification to consider fraud detection in financial reporting of accepted firms by Tehran stock exchange. The hypothesis is: Sugeno fuzzy classification may detect fraud in financial reporting by financial ratio. Hypothesis was tested using Matlab software. Accuracy average was 81/80 in Sugeno fuzzy classification; so the hypothesis was confirmed.Keywords: fraud, financial reporting, Sugeno fuzzy classification, firm
Procedia PDF Downloads 243914 Interactive Solutions for the Multi-Objective Capacitated Transportation Problem with Mixed Constraints under Fuzziness
Authors: Aquil Ahmed, Srikant Gupta, Irfan Ali
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In this paper, we study a multi-objective capacitated transportation problem (MOCTP) with mixed constraints. This paper is comprised of the modelling and optimisation of an MOCTP in a fuzzy environment in which some goals are fractional and some are linear. In real life application of the fuzzy goal programming (FGP) problem with multiple objectives, it is difficult for the decision maker(s) to determine the goal value of each objective precisely as the goal values are imprecise or uncertain. Also, we developed the concept of linearization of fractional goal for solving the MOCTP. In this paper, imprecision of the parameter is handled by the concept of fuzzy set theory by considering these parameters as a trapezoidal fuzzy number. α-cut approach is used to get the crisp value of the parameters. Numerical examples are used to illustrate the method for solving MOCTP.Keywords: capacitated transportation problem, multi objective linear programming, multi-objective fractional programming, fuzzy goal programming, fuzzy sets, trapezoidal fuzzy number
Procedia PDF Downloads 430913 Knowledge Representation Based on Interval Type-2 CFCM Clustering
Authors: Lee Myung-Won, Kwak Keun-Chang
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This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homogeneity between the clustered patterns from the IT2 contexts produced in the output space. Furthermore, we can obtain the automatic knowledge representation in the design of Radial Basis Function Networks (RBFN), Linguistic Model (LM), and Adaptive Neuro-Fuzzy Networks (ANFN) from the numerical input-output data pairs. We shall focus on a design of ANFN in this paper. The experimental results on an estimation problem of energy performance reveal that the proposed method showed a good knowledge representation and performance in comparison with the previous works.Keywords: IT2-FCM, IT2-CFCM, context-based fuzzy clustering, adaptive neuro-fuzzy network, knowledge representation
Procedia PDF Downloads 317912 Liver Lesion Extraction with Fuzzy Thresholding in Contrast Enhanced Ultrasound Images
Authors: Abder-Rahman Ali, Adélaïde Albouy-Kissi, Manuel Grand-Brochier, Viviane Ladan-Marcus, Christine Hoeffl, Claude Marcus, Antoine Vacavant, Jean-Yves Boire
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In this paper, we present a new segmentation approach for focal liver lesions in contrast enhanced ultrasound imaging. This approach, based on a two-cluster Fuzzy C-Means methodology, considers type-II fuzzy sets to handle uncertainty due to the image modality (presence of speckle noise, low contrast, etc.), and to calculate the optimum inter-cluster threshold. Fine boundaries are detected by a local recursive merging of ambiguous pixels. The method has been tested on a representative database. Compared to both Otsu and type-I Fuzzy C-Means techniques, the proposed method significantly reduces the segmentation errors.Keywords: defuzzification, fuzzy clustering, image segmentation, type-II fuzzy sets
Procedia PDF Downloads 478911 Knowledge Representation and Inconsistency Reasoning of Class Diagram Maintenance in Big Data
Authors: Chi-Lun Liu
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Requirements modeling and analysis are important in successful information systems' maintenance. Unified Modeling Language (UML) class diagrams are useful standards for modeling information systems. To our best knowledge, there is a lack of a systems development methodology described by the organism metaphor. The core concept of this metaphor is adaptation. Using the knowledge representation and reasoning approach and ontologies to adopt new requirements are emergent in recent years. This paper proposes an organic methodology which is based on constructivism theory. This methodology is a knowledge representation and reasoning approach to analyze new requirements in the class diagrams maintenance. The process and rules in the proposed methodology automatically analyze inconsistencies in the class diagram. In the big data era, developing an automatic tool based on the proposed methodology to analyze large amounts of class diagram data is an important research topic in the future.Keywords: knowledge representation, reasoning, ontology, class diagram, software engineering
Procedia PDF Downloads 233910 An Algorithm to Find Fractional Edge Domination Number and Upper Fractional Edge Domination Number of an Intuitionistic Fuzzy Graph
Authors: Karunambigai Mevani Govindasamy, Sathishkumar Ayyappan
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In this paper, we formulate the algorithm to find out the dominating function parameters of Intuitionistic Fuzzy Graphs(IFG). The methodology we adopted here is converting any physical problem into an IFG, and that has been transformed into Intuitionistic Fuzzy Matrix. Using Linear Program Solver software (LiPS), we found the defined parameters for the given IFG. We obtained these parameters for a path and cycle IFG. This study can be extended to other varieties of IFG. In particular, we obtain the definition of edge dominating function, minimal edge dominating function, fractional edge domination number (γ_if^') and upper fractional edge domination number (Γ_if^') of an intuitionistic fuzzy graph. Also, we formulated an algorithm which is appropriate to work on LiPS to find fractional edge domination number and upper fractional edge domination number of an IFG.Keywords: fractional edge domination number, intuitionistic fuzzy cycle, intuitionistic fuzzy graph, intuitionistic fuzzy path
Procedia PDF Downloads 166909 Performance Evaluation and Planning for Road Safety Measures Using Data Envelopment Analysis and Fuzzy Decision Making
Authors: Hamid Reza Behnood, Esmaeel Ayati, Tom Brijs, Mohammadali Pirayesh Neghab
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Investment projects in road safety planning can benefit from an effectiveness evaluation regarding their expected safety outcomes. The objective of this study is to develop a decision support system (DSS) to support policymakers in taking the right choice in road safety planning based on the efficiency of previously implemented safety measures in a set of regions in Iran. The measures considered for each region in the study include performance indicators about (1) police operations, (2) treated black spots, (3) freeway and highway facility supplies, (4) speed control cameras, (5) emergency medical services, and (6) road lighting projects. To this end, inefficiency measure is calculated, defined by the proportion of fatality rates in relation to the combined measure of road safety performance indicators (i.e., road safety measures) which should be minimized. The relative inefficiency for each region is modeled by the Data Envelopment Analysis (DEA) technique. In a next step, a fuzzy decision-making system is constructed to convert the information obtained from the DEA analysis into a rule-based system that can be used by policy makers to evaluate the expected outcomes of certain alternative investment strategies in road safety.Keywords: performance indicators, road safety, decision support system, data envelopment analysis, fuzzy reasoning
Procedia PDF Downloads 346908 A Data Envelopment Analysis Model in a Multi-Objective Optimization with Fuzzy Environment
Authors: Michael Gidey Gebru
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Most of Data Envelopment Analysis models operate in a static environment with input and output parameters that are chosen by deterministic data. However, due to ambiguity brought on shifting market conditions, input and output data are not always precisely gathered in real-world scenarios. Fuzzy numbers can be used to address this kind of ambiguity in input and output data. Therefore, this work aims to expand crisp Data Envelopment Analysis into Data Envelopment Analysis with fuzzy environment. In this study, the input and output data are regarded as fuzzy triangular numbers. Then, the Data Envelopment Analysis model with fuzzy environment is solved using a multi-objective method to gauge the Decision Making Units' efficiency. Finally, the developed Data Envelopment Analysis model is illustrated with an application on real data 50 educational institutions.Keywords: efficiency, Data Envelopment Analysis, fuzzy, higher education, input, output
Procedia PDF Downloads 50907 Fuzzy Logic Control for Flexible Joint Manipulator: An Experimental Implementation
Authors: Sophia Fry, Mahir Irtiza, Alexa Hoffman, Yousef Sardahi
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This study presents an intelligent control algorithm for a flexible robotic arm. Fuzzy control is used to control the motion of the arm to maintain the arm tip at the desired position while reducing vibration and increasing the system speed of response. The Fuzzy controller (FC) is based on adding the tip angular position to the arm deflection angle and using their sum as a feedback signal to the control algorithm. This reduces the complexity of the FC in terms of the input variables, number of membership functions, fuzzy rules, and control structure. Also, the design of the fuzzy controller is model-free and uses only our knowledge about the system. To show the efficacy of the FC, the control algorithm is implemented on the flexible joint manipulator (FJM) developed by Quanser. The results show that the proposed control method is effective in terms of response time, overshoot, and vibration amplitude.Keywords: fuzzy logic control, model-free control, flexible joint manipulators, nonlinear control
Procedia PDF Downloads 101906 An Integrated Intuitionistic Fuzzy Elimination Et Choix Traduisant La REalite (IFELECTRE) Model
Authors: Babak Daneshvar Rouyendegh
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The aim of this study is to develop and describe a new methodology for the Multi-Criteria Decision-Making (MCDM) problem using Intuitionistic Fuzzy Elimination Et Choix Traduisant La REalite (IFELECTRE) model. The proposed models enable Decision-Makers (DMs) on the assessment and use Intuitionistic Fuzzy numbers (IFN). A numerical example is provided to demonstrate and clarify the proposed analysis procedure. Also, an empirical experiment is conducted to validation the effectiveness.Keywords: Decision-Makers (DMs), Multi-Criteria Decision-Making (MCDM), Intuitionistic Fuzzy Elimination Et Choix Traduisant La REalite (IFELECTRE), Intuitionistic Fuzzy Numbers (IFN)
Procedia PDF Downloads 674905 Inferential Reasoning for Heterogeneous Multi-Agent Mission
Authors: Sagir M. Yusuf, Chris Baber
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We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.Keywords: distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence
Procedia PDF Downloads 141904 Fuzzy Based Stabilizer Control System for Quad-Rotor
Authors: B. G. Sampath, K. C. R. Perera, W. A. S. I. Wijesuriya, V. P. C. Dassanayake
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In this paper the design, development and testing of a stabilizer control system for a Quad-rotor is presented which is focused on the maneuverability. The mechanical design is performed along with the design of the controlling algorithm which is devised using fuzzy logic controller. The inputs for the system are the angular positions and angular rates of the Quad-Rotor relative to three axes. Then the output data is filtered from an accelerometer and a gyroscope through a Kalman filter. In the development of the stability controlling system Mandani Fuzzy Model is incorporated. The results prove that the fuzzy based stabilizer control system is superior in high dynamic disturbances compared to the traditional systems which use PID integrated stabilizer control systems.Keywords: fuzzy stabilizer, maneuverability, PID, quad-rotor
Procedia PDF Downloads 313903 Optimal Classifying and Extracting Fuzzy Relationship from Query Using Text Mining Techniques
Authors: Faisal Alshuwaier, Ali Areshey
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Text mining techniques are generally applied for classifying the text, finding fuzzy relations and structures in data sets. This research provides plenty text mining capabilities. One common application is text classification and event extraction, which encompass deducing specific knowledge concerning incidents referred to in texts. The main contribution of this paper is the clarification of a concept graph generation mechanism, which is based on a text classification and optimal fuzzy relationship extraction. Furthermore, the work presented in this paper explains the application of fuzzy relationship extraction and branch and bound method to simplify the texts.Keywords: extraction, max-prod, fuzzy relations, text mining, memberships, classification, memberships, classification
Procedia PDF Downloads 572902 A Method for Solving a Bi-Objective Transportation Problem under Fuzzy Environment
Authors: Sukhveer Singh, Sandeep Singh
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A bi-objective fuzzy transportation problem with the objectives to minimize the total fuzzy cost and fuzzy time of transportation without according priorities to them is considered. To the best of our knowledge, there is no method in the literature to find efficient solutions of the bi-objective transportation problem under uncertainty. In this paper, a bi-objective transportation problem in an uncertain environment has been formulated. An algorithm has been proposed to find efficient solutions of the bi-objective transportation problem under uncertainty. The proposed algorithm avoids the degeneracy and gives the optimal solution faster than other existing algorithms for the given uncertain transportation problem.Keywords: uncertain transportation problem, efficient solution, ranking function, fuzzy transportation problem
Procedia PDF Downloads 520901 Improving Load Frequency Control of Multi-Area Power System by Considering Uncertainty by Using Optimized Type 2 Fuzzy Pid Controller with the Harmony Search Algorithm
Authors: Mehrdad Mahmudizad, Roya Ahmadi Ahangar
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This paper presents the method of designing the type 2 fuzzy PID controllers in order to solve the problem of Load Frequency Control (LFC). The Harmony Search (HS) algorithm is used to regulate the measurement factors and the effect of uncertainty of membership functions of Interval Type 2 Fuzzy Proportional Integral Differential (IT2FPID) controllers in order to reduce the frequency deviation resulted from the load oscillations. The simulation results implicitly show that the performance of the proposed IT2FPID LFC in terms of error, settling time and resistance against different load oscillations is more appropriate and preferred than PID and Type 1 Fuzzy Proportional Integral Differential (T1FPID) controllers.Keywords: load frequency control, fuzzy-pid controller, type 2 fuzzy system, harmony search algorithm
Procedia PDF Downloads 270900 Influence of Transportation Mode to the Deterioration Rate: Case Study of Food Transport by Ship
Authors: Danijela Tuljak-Suban, Valter Suban
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Food as perishable goods represents a specific and sensitive part in the supply chain theory, since changing of its physical or chemical characteristics considerably influences the approach to stock management. The most delicate phase of this process is transportation, where it becomes difficult to ensure stability conditions that limit the deterioration, since the value of the deterioration rate could be easily influenced by the transportation mode. Fuzzy definition of variables allows taking into account these variations. Furthermore an appropriate choice of the defuzzification method permits to adapt results, as much as possible, to real conditions. In the article will be applied the those methods to the relationship between the deterioration rate of perishable goods and transportation by ship, with the aim: (a) to minimize the total costs function, defined as the sum of the ordering cost, holding cost, disposing cost and transportation costs, and (b) to improve supply chain sustainability by reducing the environmental impact and waste disposal costs.Keywords: perishable goods, fuzzy reasoning, transport by ship, supply chain sustainability
Procedia PDF Downloads 541899 Design of a Fuzzy Luenberger Observer for Fault Nonlinear System
Authors: Mounir Bekaik, Messaoud Ramdani
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We present in this work a new technique of stabilization for fault nonlinear systems. The approach we adopt focus on a fuzzy Luenverger observer. The T-S approximation of the nonlinear observer is based on fuzzy C-Means clustering algorithm to find local linear subsystems. The MOESP identification approach was applied to design an empirical model describing the subsystems state variables. The gain of the observer is given by the minimization of the estimation error through Lyapunov-krasovskii functional and LMI approach. We consider a three tank hydraulic system for an illustrative example.Keywords: nonlinear system, fuzzy, faults, TS, Lyapunov-Krasovskii, observer
Procedia PDF Downloads 322898 Comparative Study between Classical P-Q Method and Modern Fuzzy Controller Method to Improve the Power Quality of an Electrical Network
Authors: A. Morsli, A. Tlemçani, N. Ould Cherchali, M. S. Boucherit
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This article presents two methods for the compensation of harmonics generated by a nonlinear load. The first is the classic method P-Q. The second is the controller by modern method of artificial intelligence specifically fuzzy logic. Both methods are applied to an Active Power Filter shunt (APFs) based on a three-phase voltage converter at five levels NPC topology. In calculating the harmonic currents of reference, we use the algorithm P-Q and pulse generation, we use the intersective PWM. For flexibility and dynamics, we use fuzzy logic. The results give us clear that the rate of Harmonic Distortion issued by fuzzy logic is better than P-Q.Keywords: fuzzy logic controller, P-Q method, pulse width modulation (PWM), shunt active power filter (sAPF), total harmonic distortion (THD)
Procedia PDF Downloads 543897 Design and Simulation of Unified Power Quality Conditioner based on Adaptive Fuzzy PI Controller
Authors: Brahim Ferdi, Samira Dib
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The unified power quality conditioner (UPQC), a combination of shunt and series active power filter, is one of the best solutions towards the mitigation of voltage and current harmonics problems in distribution power system. PI controller is very common in the control of UPQC. However, one disadvantage of this conventional controller is the difficulty in tuning its gains (Kp and Ki). To overcome this problem, an adaptive fuzzy logic PI controller is proposed. The controller is composed of fuzzy controller and PI controller. According to the error and error rate of the control system and fuzzy control rules, the fuzzy controller can online adjust the two gains of the PI controller to get better performance of UPQC. Simulations using MATLAB/SIMULINK are carried out to verify the performance of the proposed controller. The results show that the proposed controller has fast dynamic response and high accuracy of tracking the current and voltage references.Keywords: adaptive fuzzy PI controller, current harmonics, PI controller, voltage harmonics, UPQC
Procedia PDF Downloads 547896 Lambda-Levelwise Statistical Convergence of a Sequence of Fuzzy Numbers
Authors: F. Berna Benli, Özgür Keskin
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Lately, many mathematicians have been studied the statistical convergence of a sequence of fuzzy numbers. We know that Lambda-statistically convergence is a kind of convergence between ordinary convergence and statistical convergence. In this paper, we will introduce the new kind of convergence such as λ-levelwise statistical convergence. Then, we will define the concept of the λ-levelwise statistical cluster and limit points of a sequence of fuzzy numbers. Also, we will discuss the relations between the sets of λ-levelwise statistical cluster points and λ-levelwise statistical limit points of sequences of fuzzy numbers. This work has been extended in this paper, where some relations have been considered such that when lambda-statistical limit inferior and lambda-statistical limit superior for lambda-statistically convergent sequences of fuzzy numbers are equal. Furthermore, lambda-statistical boundedness condition for different sequences of fuzzy numbers has been studied.Keywords: fuzzy number, λ-levelwise statistical cluster points, λ-levelwise statistical convergence, λ-levelwise statistical limit points, λ-statistical cluster points, λ-statistical convergence, λ-statistical limit points
Procedia PDF Downloads 471895 Determining a Suitable Maintenance Measure for Gentelligent Components Using Case-Based Reasoning
Authors: Maximilian Winkens, Peter Nyhuis
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Components with sensory properties such as gentelligent components developed at the Collaborative Research Center 653 offer a new angle on the full utilization of the remaining service life in case of a preventive maintenance. The developed methodology of component status driven maintenance analyses the stress data obtained during the component's useful life and on the basis of this knowledge assesses the type of maintenance called for in this case. The procedure is derived from the case-based reasoning method and will be elucidated in detail. The method's functionality is demonstrated with real-life data obtained during test runs of a racing car prototype.Keywords: gentelligent component, preventive maintenance, case-based reasoning, sensory
Procedia PDF Downloads 359894 Case-Based Reasoning for Build Order in Real-Time Strategy Games
Authors: Ben G. Weber, Michael Mateas
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We present a case-based reasoning technique for selecting build orders in a real-time strategy game. The case retrieval process generalizes features of the game state and selects cases using domain-specific recall methods, which perform exact matching on a subset of the case features. We demonstrate the performance of the technique by implementing it as a component of the integrated agent framework of McCoy and Mateas. Our results demonstrate that the technique outperforms nearest-neighbor retrieval when imperfect information is enforced in a real-time strategy game.Keywords: case based reasoning, real time strategy systems, requirements elicitation, requirement analyst, artificial intelligence
Procedia PDF Downloads 438893 Fuzzy Decision Support System for Human-Realistic Overtaking in Railway Traffic Simulations
Authors: Tomáš Vyčítal
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In a simulation model of a railway system it is important, besides other crucial algorithms, to have correct behaviour of train overtaking in stochastic conditions. This problem is being addressed in many simulation tools focused on railway traffic, however these are not very human-realistic. The goal of this paper is to create a more human-realistic overtaking decision support system for the use in railway traffic simulations. A fuzzy system has been chosen for this task as fuzzy systems are well-suited for human-like decision making. The fuzzy system designed takes into account timetables, train positions, delays and buffer times as inputs and provides an instruction to overtake or not overtake.Keywords: decision-making support, fuzzy systems, simulation, railway, transport
Procedia PDF Downloads 134892 Fuzzy Logic Driven PID Controller for PWM Based Buck Converter
Authors: Bandreddy Anand Babu, Mandadi Srinivasa Rao, Chintala Pradeep Reddy
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The main theme of this paper is to design fuzzy logic Proportional Integral Derivative controller for controlling of Pulse Width Modulator (PWM) based DCDC buck converter in continuous conduction mode of operation and comparing the results of FPID and ANFIS. Simulation is done to fuzzy the given input variables and membership functions of input values, creating the interference rules linking the input and output variables and after then defuzzfies the output variables. Fuzzy logic is simple for nonlinear models like buck converter. Fuzzy logic based PID controller technique is to control, nonlinear plants like buck converters in switching variables of power electronics. The characteristics of FPID are in terms of rise time, settling time, rise time, steady state errors for different inputs and load disturbances.Keywords: fuzzy logic, PID controller, DC-DC buck converter, pulse width modulation
Procedia PDF Downloads 1004891 Transformation of Periodic Fuzzy Membership Function to Discrete Polygon on Circular Polar Coordinates
Authors: Takashi Mitsuishi
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Fuzzy logic has gained acceptance in the recent years in the fields of social sciences and humanities such as psychology and linguistics because it can manage the fuzziness of words and human subjectivity in a logical manner. However, the major field of application of the fuzzy logic is control engineering as it is a part of the set theory and mathematical logic. Mamdani method, which is the most popular technique for approximate reasoning in the field of fuzzy control, is one of the ways to numerically represent the control afforded by human language and sensitivity and has been applied in various practical control plants. Fuzzy logic has been gradually developing as an artificial intelligence in different applications such as neural networks, expert systems, and operations research. The objects of inference vary for different application fields. Some of these include time, angle, color, symptom and medical condition whose fuzzy membership function is a periodic function. In the defuzzification stage, the domain of the membership function should be unique to obtain uniqueness its defuzzified value. However, if the domain of the periodic membership function is determined as unique, an unintuitive defuzzified value may be obtained as the inference result using the center of gravity method. Therefore, the authors propose a method of circular-polar-coordinates transformation and defuzzification of the periodic membership functions in this study. The transformation to circular polar coordinates simplifies the domain of the periodic membership function. Defuzzified value in circular polar coordinates is an argument. Furthermore, it is required that the argument is calculated from a closed plane figure which is a periodic membership function on the circular polar coordinates. If the closed plane figure is continuous with the continuity of the membership function, a significant amount of computation is required. Therefore, to simplify the practice example and significantly reduce the computational complexity, we have discretized the continuous interval and the membership function in this study. In this study, the following three methods are proposed to decide the argument from the discrete polygon which the continuous plane figure is transformed into. The first method provides an argument of a straight line passing through the origin and through the coordinate of the arithmetic mean of each coordinate of the polygon (physical center of gravity). The second one provides an argument of a straight line passing through the origin and the coordinate of the geometric center of gravity of the polygon. The third one provides an argument of a straight line passing through the origin bisecting the perimeter of the polygon (or the closed continuous plane figure).Keywords: defuzzification, fuzzy membership function, periodic function, polar coordinates transformation
Procedia PDF Downloads 358