Browsing by Subject "Fuzzy logic"

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Embargo
A comprehensive state-of-the-art survey on the recent modified and hybrid analytic hierarchy process approaches
(Elsevier, 2023-11-16) Ashour, Mojtaba; Mahdiyar, A.
Analytic Hierarchy Process (AHP) is a widely applied technique in multi-criteria decision-making (MCDM) problems. Over time, numerous hybridizations, improvements, and modifications have been proposed to address the shortcomings of traditional AHP. Considering the sheer number of the AHP-based methods, scholars/practitioners are faced with certain challenges when selecting a suitable method due to: (i) lack of adequate knowledge on pros and cons of different AHP approaches, (ii) difficulties and limitations in the application and analysis, and (iii) uncertainties about the suitability of the method. As a result, there is a need for a comprehensive review functioning as a guidance when choosing the best-suited approach considering the specific features of the problem at hand. This paper, therefore, reviews articles published between 2010 and 2023 that have proposed a hybrid, improved, or modified AHP and classifies them based on three main categories of contributions: (A) consistency improvements, (B) reducing the difficulties or limitations, and (C) increasing the accuracy of the results. These categories are further discussed based on the nature of variation (hybridizing with fuzzy sets, metaheuristic algorithms, modification of AHP structure, and hybridization with other approaches). A comprehensive summary table is provided to showcase the strengths and weaknesses of each method, and a roadmap is put forward for scholars and industry experts assisting them in the selection of the appropriate method considering various aspects of problems. Finally, directions for future research are discussed.
Open Access
A framework for applying the principles of depth perception to information visualization
(Association for Computing Machinery, 2013) Zeynep, C. Y.; Bulbul, A.; Capin, T.
During the visualization of 3D content, using the depth cues selectively to support the design goals and enabling a user to perceive the spatial relationships between the objects are important concerns. In this novel solution, we automate this process by proposing a framework that determines important depth cues for the input scene and the rendering methods to provide these cues. While determining the importance of the cues, we consider the user's tasks and the scene's spatial layout. The importance of each depth cue is calculated using a fuzzy logic-based decision system. Then, suitable rendering methods that provide the important cues are selected by performing a cost-profit analysis on the rendering costs of the methods and their contribution to depth perception. Possible cue conflicts are considered and handled in the system. We also provide formal experimental studies designed for several visualization tasks. A statistical analysis of the experiments verifies the success of our framework. © 2013 ACM.
Open Access
A framework for enhancing depth perception in computer graphics
(ACM, 2010-07) Çipiloğlu, Zeynep; Bülbül, Abdullah; Çapin, Tolga
This paper introduces a solution for enhancing depth perception in a given 3D computer-generated scene. For this purpose, we propose a framework that decides on the suitable depth cues for a given scene and the rendering methods which provide these cues. First, the system calculates the importance of each depth cue using a fuzzy logic based algorithm which considers the target tasks in the application and the spatial layout of the scene. Then, a knapsack model is constructed to keep the balance between the rendering costs of the graphical methods that provide these cues and their contibution to depth perception. This cost-profit analysis step selects the proper rendering methods. In this work, we also present several objective and subjective experiments which show that our automated depth enhancement system is statistically (p < 0.05) better than the other method selection techniques that are tested. © 2010 ACM.
Open Access
Fuzzy controller design for parametric controllers
(1996) Akgül, Murat
In this thesis, fuzzy logic controller (FLC) design for tuning some parametric controller is investigated. The objective in designing an FLC is to determine the rule bcise of the system and the data base which includes membership functions, set operations, and inference engine. Two designs have been realized using heuristic rule generation; one for a PID controller and one for a lead-lag type controller. The FTCs in these designs set the parcimeters of the PID and leadlag controller on-line. The rules and the corresponding membership functions are constructed by observing the effect of the changes of the parameters on the overall performance. One other design is performed using the desired inputoutput data pairs. In this design Fuzzy c-Means clustering algorithm is used to e.xtract the rules and the membership functions from the input-output data of the system. Simulation results showed that better controller performance can be cichieved by FLCs in comparison with the classical design methods.