Relevant bibliographies by topics / Fuzzy logic (FL)

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Fuzzy logic (FL)'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Fuzzy logic (FL)"

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Ab Ghani, Hadhrami, and Suraya Syazwani Mohamad Yusof. "FUZZY LOGIC-EMBEDDED MODEL WITH MACHINE LEARNING FOR TRAFFIC CONGESTION PREDICTION." PROCEEDING AL GHAZALI International Conference 2 (January 21, 2025): 484–95. https://doi.org/10.52802/aicp.v1i1.1358.

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This study explores the application of fuzzy logic-embedded machine learning models for traffic congestion classification and prediction. The main objective is to compare the performance of a Fuzzy Logic-Embedded Long Short-Term Memory (FL LSTM) model, a Fuzzy Logic-Embedded Random Forest (FL RF), and a Fuzzy Logic-Embedded Support Vector Machine (FL SVM) for predicting traffic congestion levels. A simulated dataset, incorporating features such as traffic volume, vehicle speed, and road occupancy, was used to train and test the models. Results indicated that the FL RF model outperformed both F
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Mohamad, Azizah, Azlan Mohd Zain, and Noordin bin Mohd Yusof. "Overview of Fuzzy Logic Technique for Modeling Machining Process." Applied Mechanics and Materials 815 (November 2015): 264–67. http://dx.doi.org/10.4028/www.scientific.net/amm.815.264.

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This paper describes an overview of Fuzzy Logic (FL) application for solving machining problems. The developed fuzzy prediction model is an essential operational guideline for machinist in decision making and adjusting process parameters. This paper also discussed the previous literature that applied the FL in modeling machining process.
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Rathedi, Maemo, Oduetse Matsebe, and Nonofo M. J. Ditshego. "Performance Evaluation of Hydroponics Control Systems for pH, Temperature, and Water Level Control." International Journal of Engineering Research in Africa 65 (August 8, 2023): 105–16. http://dx.doi.org/10.4028/p-rbt3yu.

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This study evaluates different control algorithms used in a hydroponic farming system to improve the quality of farm produce and resource efficiency. It focuses on three key hydroponic control parameters(potential hydrogen (pH), water level, and temperature control). Mathematical models are derived from the literature to represent hydroponic environments. These models are used for simulation purposes in MATLAB software to implement various control algorithms to evaluate their performance against each other and the system requirements utilizing transient performance parameters. Transient perfor
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Moreno-Palacio, Diana P., Carlos A. Gonzalez-Calderon, John Jairo Posada-Henao, Hector Lopez-Ospina, and Jhan Kevin Gil-Marin. "Entropy-Based Transit Tour Synthesis Using Fuzzy Logic." Sustainability 14, no. 21 (2022): 14564. http://dx.doi.org/10.3390/su142114564.

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This paper presents an entropy-based transit tour synthesis (TTS) using fuzzy logic (FL) based on entropy maximization (EM). The objective is to obtain the most probable transit (bus) tour flow distribution in the network based on traffic counts. These models consider fixed parameters and constraints. The costs, traffic counts, and demand for buses vary depending on different aspects (e.g., congestion), which are not captured in detail in the models. Then, as the FL can be included in modeling that variability, it allows obtaining solutions where some or all the constraints do not entirely sat
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Abdalla, M. O., and T. A. Al–Jarrah. "Autogeneration of Fuzzy Logic Rule-Base Controllers." Applied Mechanics and Materials 110-116 (October 2011): 5123–30. http://dx.doi.org/10.4028/www.scientific.net/amm.110-116.5123.

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A novel Fuzzy Logic controller design methodology is presented. The method utilizes a Particle Swarm Optimization (PSO) binary search algorithm to generate the rules for the Fuzzy Logic controller rule-base stage without human experience intervention. The proposed technique is compared with the well established Lyapunov based Fuzzy Logic controller design in generating the rules. Finally, the controller’s effectiveness and performance are tested, verified and validated using an elevator control application. The novel controller’s results are to be compared with traditional Proportional Integra
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Tang, Wei-Ling, Jinn-Tsong Tsai, and Yao-Mei Chen. "Fuzzy logic and Gagné learning hierarchy for assessing mathematics skills." Science Progress 104, no. 2 (2021): 003685042110143. http://dx.doi.org/10.1177/00368504211014346.

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This study developed a fuzzy logic and Gagné learning hierarchy (FL-GLH) for assessing mathematics skills and identifying learning barrier points. Fuzzy logic was used to model the human reasoning process in linguistic terms. Specifically, fuzzy logic was used to build relationships between skill level concepts as inputs and learning achievement as an output. Gagné learning hierarchy was used to develop a learning hierarchy diagram, which included learning paths and test questions for assessing mathematics skills. First, the Gagné learning hierarchy was used to generate learning path diagrams
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Oladokun, Victor Oluwasina, David G. Proverbs, and Jessica Lamond. "Measuring flood resilience: a fuzzy logic approach." International Journal of Building Pathology and Adaptation 35, no. 5 (2017): 470–87. http://dx.doi.org/10.1108/ijbpa-12-2016-0029.

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Purpose Flood resilience is emerging as a major component of an integrated strategic approach to flood risk management. This approach recognizes that some flooding is inevitable and aligns with the concept of “living with water.” Resilience measurement is a key in making business case for investments in resilient retrofits/adaptations, and could potentially be used to inform the design of new developments in flood prone areas. The literature is, however, sparse on frameworks for measuring flood resilience. The purpose of this paper is to describe the development of a fuzzy logic (FL)-based res
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Nithya, S., K. Maithili, T. Sathish Kumar, et al. "A fuzzy logic and cross-layered optimization for effective congestion control in wireless sensor networks to improve efficiency and performance." MATEC Web of Conferences 392 (2024): 01145. http://dx.doi.org/10.1051/matecconf/202439201145.

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Wireless Sensor Networks (WSNs) are a fundamental component of the Internet of Things (IoT), used in diverse applications to detect environmental conditions and send information to the Internet. WSNs are susceptible to congestion issues, leading to increased packet loss, extended delays, and reduced throughput. This research introduces a Fuzzy Logic-based Cross-Layered Optimization Model (FL-CLOM) for WSNs to tackle the problem. FL-CLOM is developed by including the signal-to-noise ratio of the wireless channels in the Transmission Control Protocol (TCP) approach, bridging the transmission lay
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Chen, J. C., and R. Krisshnasamy. "Development of eDART-based weight prediction system in injection molding via Taguchi design and fuzzy logic." Journal of Physics: Conference Series 2631, no. 1 (2023): 012013. http://dx.doi.org/10.1088/1742-6596/2631/1/012013.

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Abstract This research describes developing a Fuzzy Logic based weight prediction system (FL-eWPS) during the process of injection molding. The main purpose is to apply Fuzzy Logic to predict defects during injection molding operations while processing parameters, such as shot size, barrel temperature, cooling time, and holding pressure. The parameters are varied within a shorter range when using Delrin 511 DP plastic from DuPont Engineering Polymers. eDART data logging system was used for real-time data collection for the different parameters by using the sensors during the injection filling
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Kasmi, B., and A. Hassam. "Comparative Study between Fuzzy Logic and Interval Type-2 Fuzzy Logic Controllers for the Trajectory Planning of a Mobile Robot." Engineering, Technology & Applied Science Research 11, no. 2 (2021): 7011–17. http://dx.doi.org/10.48084/etasr.4031.

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In this study, Fuzzy Logic (FL) and Interval Type-2 FL (IT-2FL) controllers were applied to a mobile robot in order to determine which method facilitates navigation and enables the robot to overcome real-world uncertainties and track an optimal trajectory in a very short time. The robot under consideration is a non-holonomic unicycle mobile robot, represented by a kinematic model, evolving in two different environments. The first environment is barrier-free, and moving the robot from an initial to a target position requires the introduction of a single action module. Subsequently, the same pro
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Dissertations / Theses on the topic "Fuzzy logic (FL)"

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Li, Zhi. "Fuzzy logic based robust control of queue management and optimal treatment of traffic over TCP/IP networks." University of Southern Queensland, Faculty of Sciences, 2005. http://eprints.usq.edu.au/archive/00001461/.

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Improving network performance in terms of efficiency, fairness in the bandwidth, and system stability has been a research issue for decades. Current Internet traffic control maintains sophistication in end TCPs but simplicity in routers. In each router, incoming packets queue up in a buffer for transmission until the buffer is full, and then the packets are dropped. This router queue management strategy is referred to as Drop Tail. End TCPs eventually detect packet losses and slow down their sending rates to ease congestion in the network. This way, the aggregate sending rate converges to the
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Windridge, David, Michael Felsberg, and Affan Shaukat. "A Framework for Hierarchical Perception–Action Learning Utilizing Fuzzy Reasoning." Linköpings universitet, Datorseende, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-85688.

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Perception-action (P-A) learning is an approach to cognitive system building that seeks to reduce the complexity associated with conventional environment-representation/action-planning approaches. Instead, actions are directly mapped onto the perceptual transitions that they bring about, eliminating the need for intermediate representation and significantly reducing training requirements. We here set out a very general learning framework for cognitive systems in which online learning of the P-A mapping may be conducted within a symbolic processing context, so that complex contextual reasoning
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Branco, Hermes Manoel Galvão Castelo. "Uma estratégia para a detecção e classificação de transitórios em transformadores de potência pela utilização da transformada Wavelet e da lógica Fuzzy." Universidade de São Paulo, 2009. http://www.teses.usp.br/teses/disponiveis/18/18154/tde-09092009-083518/.

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Nesta pesquisa, apresentam-se os principais eventos relacionados com a proteção de transformadores e sua correlação com os distúrbios de qualidade da energia elétrica (QEE). Neste sentido, foi desenvolvido um algoritmo que utiliza a transformada Wavelet (TW) e a lógica Fuzzy (LF) para classificar os eventos transitórios associados à proteção de transformadores. Estes eventos foram observados em um sistema elétrico de potência (SEP) simulado com a utilização do software Alternative Transients Program (ATP). Importa ressaltar que o sistema modelado apresenta transformadores ligados em paralelo,
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(12971010), Masoud Mohammadian. "Integrating neural networks, fuzzy logic and genetic algorithms for intelligent control." Thesis, 1993. https://figshare.com/articles/thesis/Integrating_neural_networks_fuzzy_logic_and_genetic_algorithms_for_intelligent_control/20174402.

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<p>In this thesis, the integration of Neural Networks (NNs), Fuzzy Logic (FL) and Genetic Algorithms (GAs) for intelligent control is proposed and applied to the classical problem of docking a truck.</p> <p>A backpropagation neural network architecture using a "step" update weight modification is used to obtain quickly and efficiently trajectory data from given initial states. A new algorithm to define fuzzy logic rules is used on the trajectory data to build a fuzzy logic knowledge base. This fuzzy logic knowledge base is then optimised using a genetic algorithm to obtain a fuzzy logic contro
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Books on the topic "Fuzzy logic (FL)"

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Belohlavek, Radim, Joseph W. Dauben, and George J. Klir. Fuzzy Logic and Mathematics. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190200015.001.0001.

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The term “fuzzy logic” (FL) is a generic one, which stands for a broad variety of logical systems. Their common ground is the rejection of the most fundamental principle of classical logic—the principle of bivalence—according to which each declarative sentence has exactly two possible truth values—true and false. Each logical system subsumed under FL allows for additional, intermediary truth values, which are interpreted as degrees of truth. These systems are distinguished from one another by the set of truth degrees employed, its algebraic structure, truth functions chosen for logical connect
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Book chapters on the topic "Fuzzy logic (FL)"

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Heister, Hanns-Werner. "Einleitung. Vier Prinzipien und fünf Erscheinungsformen der FL im Musikprozess." In Musik und Fuzzy Logic. Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-662-63006-8_1.

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Zadeh, Lotfi A. "Some reflections on the relationship between AI and fuzzy logic (FL) —A heretical view." In Fuzzy Logic in Artificial Intelligence. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/bfb0095067.

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Khanna, Daksh, Tanupriya Choudhury, A. Sai Sabitha, and Nguyen Gia Nhu. "Microarray Gene Expression Analysis Using Fuzzy Logic (MGA-FL)." In Advances in Intelligent Systems and Computing. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1951-8_16.

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Wu, Yining. "Transforming Fuzzy Description Logic $\mathcal{ALC}_\mathcal{FL}$ into Classical Description Logic $\mathcal{ALCH}$." In Uncertainty Reasoning for the Semantic Web II. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35975-0_10.

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Mandal, Sujit, and Subrata Mondal. "Knowledge-Driven Statistical Approach for Landslide Susceptibility Assessment Using GIS and Fuzzy Logic (FL) Approach." In Statistical Approaches for Landslide Susceptibility Assessment and Prediction. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93897-4_7.

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Fathima Shemim, K. S., and Ulf Witkowski. "Enhanced Energy-Efficient Fuzzy Logic Clustering and Network Coding Strategy for Wireless Sensor Networks (EEE-FL-NC)." In Advanced Computing and Intelligent Technologies. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2164-2_5.

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Zindani, Divya, Apurba Kumar Roy, Kaushik Kumar, and J. Paulo Davim. "Fuzzy Logic for Machining Applications." In Advanced Fuzzy Logic Approaches in Engineering Science. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-5709-8.ch016.

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There have been umpteen research reports on the usage of artificial intelligence (AI) strategies for modelling various machining processes. One of the well-known AI strategies is that of fuzzy logic (FL) techniques that has been used for prediction of machining performance variables for both the categories of machining processes and controls the machining process. Given the increasing trend of FL in machining, the chapter reviews the application of fuzzy logic in modelling and controlling the machining processes. The work begins with introduction section and then proceeds to discuss the import
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Martínez-Barrera, Gonzalo, Osman Gencel, Ahmet Beycioglu, Serkan Subaşı, and Nelly González-Rivas. "Artificial Intelligence Methods and Their Applications in Civil Engineering." In Fuzzy Systems. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-1908-9.ch059.

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Simulation of material properties generally involves the development of a mathematical model derived from experimental data. In structural mechanics and construction materials contexts, recent experiments have reported that fuzzy logic (FL), artificial neural networks (ANNs), genetic algorithm (GA), and fuzzy genetic (FG) may offer a promising alternative. They are known as artificial intelligence (AI). In civil engineering, AI methods have been extensively used in the fields of civil engineering applications such as construction management, building materials, hydraulic, optimization, geotech
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Kolomvatsos, Kostas, and Stathes Hadjiefthymiades. "On the Use of Fuzzy Logic in Electronic Marketplaces." In Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-61350-429-1.ch030.

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Today, there is a large number of product providers in the Web. Electronic Marketplaces (EMs) enable entities to negotiate and trade products. Usually, intelligent agents assume the responsibility of representing buyers or sellers in EMs. However, uncertainty about the characteristics and intentions of the negotiating entities is present in these scenarios. Fuzzy Logic (FL) theory presents a lot of advantages when used in environments where entities have limited or no knowledge about their peers. Hence, entities can rely on a FL knowledge base that determines the appropriate action on every po
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Banimelhem, Omar, Eyad Taqieddin, Moad Y. Mowafi, Fahed Awad, and Feda' Al-Ma'aqbeh. "Fuzzy Logic-Based Cluster Heads Percentage Calculation for Improving the Performance of the LEACH Protocol." In Fuzzy Systems. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-1908-9.ch027.

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In wireless sensor networks, cluster-based routing was proven to be the most energy-efficient strategy to deal with the scaling problem. In addition, selecting the proper number of clusters is a critical decision that can impose a significant impact on the energy consumption and the network lifetime. This paper presents FL-LEACH, a variant of the well-known LEACH clustering protocol, which attempts to relax the stringent strategy of determining the number of clusters used by LEACH via fuzzy logic decision-making scheme. This relates the number of clusters to a number of network characteristics
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Conference papers on the topic "Fuzzy logic (FL)"

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Attaullah, Hasina, Sanaullah Sanaullah, and Thorsten Jungeblut. "FL-DL: Fuzzy Logic with Deep Learning, Hybrid Anomaly Detection and Activity Prediction in Smart Homes Data-Sets." In 2024 IEEE 24th International Symposium on Computational Intelligence and Informatics (CINTI). IEEE, 2024. https://doi.org/10.1109/cinti63048.2024.10830825.

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Tayal, Shikha, Taskeen Zaidi, and Preeti Gera. "Utilization of Support Vector Machines (SVM), Fuzzy Logic (FL) & Adaptive Neuro-Fuzzy Inference System (ANFIS) for Carrying Out Proficient Energy Routing in 5G Wireless Networks." In 2024 1st International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI (ICSCAI). IEEE, 2024. https://doi.org/10.1109/icscai61790.2024.10866528.

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Gannamneni, Nanda Kishore, Archit Joshi, Priyank Mohan, Ramya Ramachandran, Krishan Kumar, and Shakeb Khan. "QPSO-FL-EECP: Quantum Particle Swarm Optimization and Fuzzy Logic-Based Protocol for Energy-Efficient Clustering Protocol in Wireless Sensor Networks." In 2024 13th International Conference on System Modeling & Advancement in Research Trends (SMART). IEEE, 2024. https://doi.org/10.1109/smart63812.2024.10882515.

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Zadeh, Lotfi A. "Fuzzy logic: principles, applications, and perspectives." In Orlando '91, Orlando, FL, edited by Mohan M. Trivedi. SPIE, 1991. http://dx.doi.org/10.1117/12.45456.

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Priebe, Russell, and Richard A. Jones. "Fuzzy logic approach to multitarget tracking in clutter." In Orlando '91, Orlando, FL, edited by Michael K. Masten and Larry A. Stockum. SPIE, 1991. http://dx.doi.org/10.1117/12.45703.

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Crawford, Anthony L., and Dean B. Edwards. "Implementing Fuzzy Logic in the Control of a Biologically Inspired Robotic Cat Leg." In ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-49785.

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This research discusses the implementation of a fuzzy logic control system to drive the movement of a simplified cat leg model. The system’s movement in this paper addresses a planar motion where the model experiences a fixed horizontal velocity and a harmonic vertical displacement. The fuzzy logic (FL) controller applies membership functions to fuzzify the position and velocity errors and applies height defuzzification to generate the time dependant forcing function for the system’s horizontal and vertical governing equations. A PID controller is also applied as a benchmark for this research.
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Bello, Opeyemi, Francisco Serdio Fernández, Catalin Teodoriu, Joachim Oppelt, Javier Holzmann, and Susanne Saminger-Platz. "Novel Application of Fuzzy Logic (FL) Method for Drilling Rig Selection." In Abu Dhabi International Petroleum Exhibition and Conference. Society of Petroleum Engineers, 2015. http://dx.doi.org/10.2118/177653-ms.

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Basehore, Paul, and Joseph T. Yestrebsky. "Innovative architectural and theoretical considerations yield efficient fuzzy logic controller VLSI design." In Orlando '91, Orlando, FL, edited by Vibeke Libby. SPIE, 1991. http://dx.doi.org/10.1117/12.44850.

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Karr, Charles L. "Design of a cart-pole balancing fuzzy logic controller using a genetic algorithm." In Orlando '91, Orlando, FL, edited by Mohan M. Trivedi. SPIE, 1991. http://dx.doi.org/10.1117/12.45446.

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Laribi, M. A., L. Romdhane, A. Mlika, and S. Zeghloul. "A Combined Genetic Algorithm-Fuzzy Logic Method (GA-FL) to Design a 6 Bars Planar Mechanism." In ASME 7th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2004. http://dx.doi.org/10.1115/esda2004-58193.

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This work deals with solution methods of optimal synthesis of planar mechanisms. A searching procedure presents a combined genetic algorithm–fuzzy logic method to solve the problem of path generation in mechanism synthesis. Previous works, dealing with the same problem and using the genetic algorithm method, suffered from the lack of precision, especially for large domain problems. The proposed method is made of a classical genetic algorithm coupled with a fuzzy logic controller (GA-FL). This controller monitors the variation of the design variables during the first run of the genetic algorith
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