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

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

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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Salami, Ameen M., Dhaideen M. Salih, and Omar N. Jasim. "Fuzzy Logic For Estimating Surgery Risks Based on ASA Classification." Journal of Research in Engineering and Computer Sciences 3, no. 1 (2025): 32–40. https://doi.org/10.63002/jrecs.31.799.

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The huge development of artificial intelligence in health care system dealing with uncertainties in the health decision‐making process. The fuzzy logic provides an effective income for dealing with uncertainties. This research practices fuzzy logic (FL) system to think like an expert clinician and exam the possibility of diagnosing the risk of performing surgical operations requiring general anesthesia. This done through the patient's main tests and analyses the levels of test results according to the American Society of General Anesthesia (ASA). Relying on fuzzy logic rules, the possibility o

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Nasir, Mohammad, Ali Sadollah, Przemyslaw Grzegorzewski, Jin Hee Yoon, and Zong Woo Geem. "Harmony Search Algorithm and Fuzzy Logic Theory: An Extensive Review from Theory to Applications." Mathematics 9, no. 21 (2021): 2665. http://dx.doi.org/10.3390/math9212665.

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In recent years, many researchers have utilized metaheuristic optimization algorithms along with fuzzy logic theory in their studies for various purposes. The harmony search (HS) algorithm is one of the metaheuristic optimization algorithms that is widely employed in different studies along with fuzzy logic (FL) theory. FL theory is a mathematical approach to expressing uncertainty by applying the conceptualization of fuzziness in a system. This review paper presents an extensive review of published papers based on the combination of HS and FL systems. In this regard, the functional characteri

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Ahmed, Omer K., Raid W. Daoud, Shaimaa M. Bawa, and Ahmed H. Ahmed. "Optimization of PV/T Solar Water Collector based on Fuzzy Logic Control." International Journal of Renewable Energy Development 9, no. 2 (2020): 303–10. http://dx.doi.org/10.14710/ijred.9.2.303-310.

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Hybrid solar collector (PV/T) is designed to produce electricity, hot water, or hot air at the same time as they operate solar cells and solar heaters in one system. This system is designed to increase the electrical efficiency of solar cells by absorbing heat from these cells. The fuzzy logic (FL) is a tool usually used to optimize the operation of the systems. In this paper, the FL is to monitor and correct the mainsystem parameters to remain optimization efficiency at a better level. Three affected variables were studied: Effect of reflective mirrors, the effect of the glass cover, and the

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Antigha Ita, Maurice. "Short-Term Electrical Energy Demand Forecasting Using Fuzzy Logic Technique." Arid-zone Journal of Basic and Applied Research 4, no. 1 (2024): 88–102. http://dx.doi.org/10.55639/607.444342.

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Minimization of electrical energy wastage and provision of its regular supply make electrical load forecasting an important aspect of the power infrastructure. An accurate load forecasting is crucial for the reduction of the cost of electrical energy generation and spinning reserve capacity. Therefore, in this study, fuzzy logic (FL) technique was employed for the projection of electrical energy demand on short-term basis. The FL model was trained using the six months hourly load and temperature data respectively obtained from 132/33 kV Ikeja West Transmission Station, Ayobo and Nigerian Meteo

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YALÇINKAYA, Fikret, Ata SEVİNC, Hüseyin AYDİLEK, and Ali ERBAŞ. "Ultrasonic Therapy Device Using Fuzzy-Logic for Clinical Use." Uluslararası Muhendislik Arastirma ve Gelistirme Dergisi 15, no. 2 (2023): 776–85. http://dx.doi.org/10.29137/umagd.1310831.

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In this paper, an ultrasonic therapy device using fuzzy-logic(UTD-FL) has been designed, constructed and tested with phantom materials. Fuzzy-logic rules have been determined using four parameters. In clinical practice, ultrasonic therapy is conducted solely based on subjective evaluation of medical experts, but in UTD-FL, fuzzy-logic rules decide automatically the three critically important characteristic parameters of applicable output power to the patient, namely the power of the signal, the percent of the duty-cycle and the signal frequency. The signal frequency and specifically its amplit

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Hayder, Yousif Abed, Thiab Humod Abdulrahim, and J. Humaidi Amjad. "Type 1 versus type 2 fuzzy logic speed controllers for brushless DC motors." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 1 (2020): 265–74. https://doi.org/10.11591/ijece.v10i1.pp265-274.

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This work presented two fuzzy logic (FL) schemes for speed-controlled brushless DC motors. The first controller is a Type 1 FL controller (T1FLC), whereas the second controller is an interval Type 2 FL controller (IT2FLC). The two proposed controllers were compared in terms of system dynamics and performance. For a fair comparison, the same type and number of membership functions were used for both controllers. The effectiveness of the structures of the two FL controllers was verified through simulation in MATLAB/SIMULINK environment. Simulation result showed that IT2FLC exhibited better perfo

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Lin, Y. J., Y. Lu, T. Lee, and B. Choi. "Modeling and Fuzzy Logic Control of an Active Reaction Compensating Platform System." Shock and Vibration 2, no. 6 (1995): 493–506. http://dx.doi.org/10.1155/1995/829607.

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This article presents the application of the fuzzy logic (FL) concept to the active control of a multiple degree of freedom reaction compensating platform system that is designed and used for isolating vibratory disturbances of space-based devices. The physical model used is a scaled down two-plate platform system. In this work, simulation is performed and presented. According to the desired performance specifications, a full range of investigation regarding the development of an FL stabilization controller for the system is conducted. Specifically, the study includes four stages: comprehensiv

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Tabares, Héctor, and Jesús Hernández. "Forecasting time series. Short-term electrical power using fuzzy logic." Revista Facultad de Ingeniería Universidad de Antioquia, no. 47 (December 4, 2013): 209–17. http://dx.doi.org/10.17533/udea.redin.17784.

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In recent developments of fuzzy logic, the paradigm of universal proximity is very common. The fuzzy systems are estimates of a continuous function in a X group. The objective of this work is to find out a F(x) function with Fuzzy Logic (FL) that will allow to map out daily electrical power curves in a residential sector, in the city of Medellín. The variable input vector is the total electricity required for a 24 hour period (t).

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Aoukach, Basma, and Benyounes Oukarfi. "An improved energy management method based on combination of multi agent system and fuzzy logic." European Physical Journal Applied Physics 92, no. 3 (2020): 30902. http://dx.doi.org/10.1051/epjap/2020200189.

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This paper presents a distributed energy management strategy based on a combination of multi agent system (MAS) and fuzzy logic (FL). Our system is composed of two renewable energy sources which are a photovoltaic panel, wind turbine, storage system and a variable loads. These elements are linked between them through switches. This improved technique allows the control of switches to manage the energy flow between sources and established load priority. MAS consider each element of the system as an agent, one of them is called execution agent that controls switches based on the paradigm of fuzz

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Pan, Bin, Hao Wu, and Jin Wang. "FL-ASB: A Fuzzy Logic Based Adaptive-period Single-hop Broadcast Protocol." International Journal of Distributed Sensor Networks 14, no. 5 (2018): 155014771877848. http://dx.doi.org/10.1177/1550147718778482.

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In vehicular ad hoc networks, vehicle-to-vehicle–based broadcast can fast disseminate safety messages between vehicles within the whole network and hence expand drivers perception vision, which will reduce the accident probability and ensure the transportation reliability. As for fixed-period single-hop broadcast protocol, disseminating safety messages frequently can cause excessive network load. However, increasing period purely does not guarantee the real-time performance. In addition, exiting adaptive-period single-hop broadcast protocols also have limitations without considering synthetica

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AsadUllah, Muhammad, Muhammad Adnan Khan, Sagheer Abbas, Atifa Athar, Syed Saqib Raza, and Gulzar Ahmad. "Blind Channel and Data Estimation Using Fuzzy Logic-Empowered Opposite Learning-Based Mutant Particle Swarm Optimization." Computational Intelligence and Neuroscience 2018 (December 6, 2018): 1–12. http://dx.doi.org/10.1155/2018/6759526.

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Multiple-input and multiple-output (MIMO) technology is one of the latest technologies to enhance the capacity of the channel as well as the service quality of the communication system. By using the MIMO technology at the physical layer, the estimation of the data and the channel is performed based on the principle of maximum likelihood. For this purpose, the continuous and discrete fuzzy logic-empowered opposite learning-based mutant particle swarm optimization (FL-OLMPSO) algorithm is used over the Rayleigh fading channel in three levels. The data and the channel populations are prepared dur

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Wan, Jian, Peiwen Ren, and Qiang Guo. "Application of Interactive Multiple Model Adaptive Five-Degree Cubature Kalman Algorithm Based on Fuzzy Logic in Target Tracking." Symmetry 11, no. 6 (2019): 767. http://dx.doi.org/10.3390/sym11060767.

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Aiming at the shortcomings of low precision, hysteresis, and poor robustness of the general interactive multimodel algorithm in the “snake-like” maneuver tracking of anti-ship missiles, an interactive multimodel adaptive five-degree cubature Kalman algorithm based on fuzzy logic (FLIMM5ACKF) is proposed. The algorithm mainly includes adaptive five-degree cubature Kalman algorithm (A5CKF) and fuzzy logic algorithm (FL). A5CKF uses the Sage–Husa noise estimation principle to propose a state error covariance adaptive five-degree cubature Kalman algorithm to improve the performance of state estima

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S.M.A.N.M, Subasinghe. "Leveraging Business-Inspired Computational Intelligence Techniques for Enhanced Data Analytics: Applications of Genetic Algorithms, Fuzzy Logic, and Swarm Intelligence." Leveraging Business-Inspired Computational Intelligence Techniques for Enhanced Data Analytics: Applications of Genetic Algorithms, Fuzzy Logic, and Swarm Intelligence 9, no. 1 (2024): 6. https://doi.org/10.5281/zenodo.10638915.

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Data has become a crucial element for contemporary enterprises; however, deriving practical insights from its immense volume remains an intricate  obstacle. This paper examines the capabilities of three bio- inspired computational intelligence (CI) methods - Genetic  Algorithms (GAs), Fuzzy Logic (FL), and Swarm Intelligence (SI) - in improving data analytics for business optimization and decision-making. The researcher thoroughly examines the fundamental principles of each technique, emphasizing their inherent advantages and appropriateness for addressing practical business challeng

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Ismaeel, Salam, Ayman Al-Khazraji, and Karama Al-delimi. "Fuzzy Information Modeling in a Database System." IAES International Journal of Artificial Intelligence (IJ-AI) 6, no. 1 (2017): 1. http://dx.doi.org/10.11591/ijai.v6.i1.pp1-7.

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A Fuzzy logic (FL) provides a remarkably simple way to draw definite conclusions from vague, ambiguous or imprecise information. In a sense, fuzzy logic resembles human decision making with its ability to work from approximate data and find precise solutions. In this paper a fuzzy information modeling system was developed then used in a database, which contains fuzzy data and real data, to create new information assistance capable of making any decision about this data. The proposed system is implemented on a special database used to evaluation workers or users in any formal organizations.

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Salam, Ismaeel, Al-Khazraji Ayman, and Al-delim Karama. "Fuzzy Information Modeling in a Database System." IAES International Journal of Artificial Intelligence (IJ-AI) 6, no. 1 (2017): 1–7. https://doi.org/10.5281/zenodo.4107767.

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A Fuzzy logic (FL) provides a remarkably simple way to draw definite conclusions from vague, ambiguous or imprecise information. In a sense, fuzzy logic resembles human decision making with its ability to work from approximate data and find precise solutions. In this paper a fuzzy information modeling system was developed then used in a database, which contains fuzzy data and real data, to create new information assistance capable of making any decision about this data. The proposed system is implemented on a special database used to evaluation workers or users in any formal organizations.

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Thakur, Amey. "Neuro-Fuzzy: Artificial Neural Networks & Fuzzy Logic." International Journal for Research in Applied Science and Engineering Technology 9, no. 9 (2021): 128–35. http://dx.doi.org/10.22214/ijraset.2021.37930.

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Abstract: Neuro Fuzzy is a hybrid system that combines Artificial Neural Networks with Fuzzy Logic. Provides a great deal of freedom when it comes to thinking. This phrase, on the other hand, is frequently used to describe a system that combines both approaches. There are two basic streams of neural network and fuzzy system study. Modelling several elements of the human brain (structure, reasoning, learning, perception, and so on) as well as artificial systems and data: pattern clustering and recognition, function approximation, system parameter estimate, and so on. In general, neural networks

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Alashan, Sadık, Sedat Golgiyaz, Erdinç İkincioğulları, and Eyyüp Ensar Yalçın. "Practical Design of Stepped Spillways Using Machine Learning Methods and Fuzzy Inference System." Harran Üniversitesi Mühendislik Dergisi 10, no. 1 (2025): 36–50. https://doi.org/10.46578/humder.1638527.

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Energy-dissipating pools or flip bucket structures reduce the energy of downstream flow in conventional spillways. Recently, stepped spillways have been widely used to dissipate the flow of energy downstream. Flows on the stepped spillways are complex and advanced techniques such as Fuzzy Logic (FL), Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN), Genetic Programming (GP), Deep Learning, and Tree-Based models are required to calculate energy dissipation ratios. Fuzzy Logic has the advantage of considering physical processes when examining problems using rule bas

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Hamzah, Abdulmughni, Mohammad Shurman, Omar Al-Jarrah, and Eyad Taqieddin. "Energy-Efficient Fuzzy-Logic-Based Clustering Technique for Hierarchical Routing Protocols in Wireless Sensor Networks." Sensors 19, no. 3 (2019): 561. http://dx.doi.org/10.3390/s19030561.

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In wireless sensor networks, the energy source is limited to the capacity of the sensor node’s battery. Clustering in WSN can help with reducing energy consumption because transmission energy is related to the distance between sender and receiver. In this paper, we propose a fuzzy logic model for cluster head election. The proposed model uses five descriptors to determine the opportunity for each node to become a CH. These descriptors are: residual energy, location suitability, density, compacting, and distance from the base station. We use this fuzzy logic model in proposing the Fuzzy Logic-b

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Abed, Hayder Yousif, Abdulrahim Thiab Humod, and Amjad J. Humaidi. "Type 1 versus type 2 fuzzy logic speed controllers for brushless dc motors." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 1 (2020): 265. http://dx.doi.org/10.11591/ijece.v10i1.pp265-274.

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<span lang="EN-US">This work presented two fuzzy logic (FL) schemes for speed-controlled brushless DC motors. The first controller is a Type 1 FL controller (T1FLC), whereas the second controller is an interval Type 2 FL controller (IT2FLC). The two proposed controllers were compared in terms of system dynamics and performance. For a fair comparison, the same type and number of membership functions were used for both controllers. The effectiveness of the structures of the two FL controllers was verified through simulation in MATLAB/SIMULINK environment. Simulation result showed that IT2F

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Wang, Jiyuan, Kaiyue Wang, Xiangfang Yan, and Chanjuan Wang. "A Hybrid Learning Particle Swarm Optimization With Fuzzy Logic for Sentiment Classification Problems." International Journal of Cognitive Informatics and Natural Intelligence 16, no. 1 (2022): 1–23. http://dx.doi.org/10.4018/ijcini.314782.

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Methods based on deep learning have great utility in the current field of sentiment classification. To better optimize the setting of hyper-parameters in deep learning, a hybrid learning particle swarm optimization with fuzzy logic (HLPSO-FL) is proposed in this paper. Hybrid learning strategies are divided into mainstream learning strategies and random learning strategies. The mainstream learning strategy is to define the mainstream particles in the cluster and build a scale-free network through the mainstream particles. The random learning strategy makes full use of historical information an

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Sarojini, Ratnam Kamala, Kaliannan Palanisamy, and Enrico De Tuglie. "A Fuzzy Logic-Based Emulated Inertia Control to a Supercapacitor System to Improve Inertia in a Low Inertia Grid with Renewables." Energies 15, no. 4 (2022): 1333. http://dx.doi.org/10.3390/en15041333.

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The contribution of power generation from converter-dominated renewable energy sources (RES) has increased enormously. Consequently, the system inertia is decreasing, and it impacts the frequency of the system. With large-scale integration of power electronic inverter-based power generation from RES, inertia from energy storage devices would be unavoidable in future power grids. In this paper, the inertia emulator is formed with a supercapacitor (IE–SC) to improve inertia in a low inertia grid. To emulate the inertia in a low inertia grid, this paper proposes a fuzzy logic controller-based emu

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Zhang, Gui Chen. "Design and Simulation of the Self-Tune Fuzzy Logic PID Controller for VAV Air Condition System." Applied Mechanics and Materials 397-400 (September 2013): 1286–90. http://dx.doi.org/10.4028/www.scientific.net/amm.397-400.1286.

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Base on the Fuzzy Logic(FL) control theorem, the Self-tune FL PID controller is designed in which the base rules of operator experience were combined. In MATLAB simulation, when system uses the same parameters, the Self-tune FL PID controller’s over-adjust decreases by 17% compared to the conventional PID controller. That applying Self-tune FL PID controller to control the damper’s position in VAV system is able to achieve the steady and less energy consumption system.

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John Rose, A., G. Anandha Kumar, A. Ragavendiran, and A. Kalaimurugan. "Model Predictive Controlled Four-Bus System Employing Hybrid Power Flow Controller." Journal of Sensors 2023 (March 3, 2023): 1–10. http://dx.doi.org/10.1155/2023/4621537.

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A fuzzy logic- (FL-) based control technique for unified power flow controller (UPFC) to resolve the power quality issues in transmission network is presented in this paper. MATLAB/Simulink is used to design the FL-based controllers for shunt and series converters of UPFC, which is validated on 4-bus system. In addition, the performance of the suggested FL-based UPFC is compared with PI (proportional integral), HC (hysteresis controller), MPC (model predictive controller), and FLC (fuzzy logic controller), and the outcomes are compared in terms of settling time and steady-state error. The cons

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Haghighat, Ezzatollah, Saeed Shaikhzadeh Najar, and Seyed Mohammad Etrati. "The Prediction of Needle Penetration Force in Woven Denim Fabrics Using Soft Computing Models." Journal of Engineered Fibers and Fabrics 9, no. 4 (2014): 155892501400900. http://dx.doi.org/10.1177/155892501400900406.

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The aim of this paper was to predict the needle penetration force in denim fabrics based on sewing parameters by using the fuzzy logic (FL) model. Moreover, the performance of fuzzy logic model is compared with that of the artificial neural network (ANN) model. The needle penetration force was measured on the Instron tensile tester. In order to plan the fuzzy logic model, the sewing needle size, number of fabric layers and fabric weight were taken into account as input parameters. The output parameter is needle penetration force. In addition, the same parameters and data are used in artificial

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Baalousha, Husam Musa, Bassam Tawabini, and Thomas D. Seers. "Fuzzy or Non-Fuzzy? A Comparison between Fuzzy Logic-Based Vulnerability Mapping and DRASTIC Approach Using a Numerical Model. A Case Study from Qatar." Water 13, no. 9 (2021): 1288. http://dx.doi.org/10.3390/w13091288.

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Vulnerability maps are useful for groundwater protection, water resources development, and land use management. The literature contains various approaches for intrinsic vulnerability assessment, and they mainly depend on hydrogeological settings and anthropogenic impacts. Most methods assign certain ratings and weights to each contributing factor to groundwater vulnerability. Fuzzy logic (FL) is an alternative artificial intelligence tool for overlay analysis, where spatial properties are fuzzified. Unlike the specific rating used in the weighted overlay-based vulnerability mapping methods, FL

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Wang, Jianping, Qigao Feng, Jianwei Ma, and Yikun Feng. "FL-SDUAN: A Fuzzy Logic-Based Routing Scheme for Software-Defined Underwater Acoustic Networks." Applied Sciences 13, no. 2 (2023): 944. http://dx.doi.org/10.3390/app13020944.

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In underwater acoustic networks, the accurate estimation of routing weights is NP-hard due to the time-varying environment. Fuzzy logic is a powerful tool for dealing with vague problems. Software-defined networking (SDN) is a promising technology that enables flexible management by decoupling the data plane from the control plane. Inspired by this, we proposed a fuzzy logic-based software-defined routing scheme for underwater acoustic networks (FL-SDUAN). Specifically, we designed a software-defined underwater acoustic network architecture. Based on fuzzy path optimization (FPO-MST) and fuzzy

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Lehal, Manpreet Singh. "Fuzzy in the Real World." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 7, no. 1 (2013): 473–77. http://dx.doi.org/10.24297/ijct.v7i1.3476.

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The Fuzzy Logic tool was introduced in 1965, by LotfiZadeh, and is a mathematical tool for dealing with uncertainty. It offers to a soft computing partnership the important concept of computing with words. It provides a technique to deal with imprecision and information granularity. Fuzzy Logic (FL) is a multi valued logic that allows intermediate values to be defined between conventional evaluations like true/false, yes/no, high/low, etc. Notions like rather tall or very fast can be formulated mathematically and processed by computers, in order to apply a more human like way of thinking in th

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Goswami, Ayush, and Mahesh Ram Patel. "A Review on Enhancing the properties of Stone Mastic Asphalt Using Bagasse and Coir Fiber as Additives." International Journal for Research in Applied Science and Engineering Technology 11, no. 3 (2023): 466–70. http://dx.doi.org/10.22214/ijraset.2023.49461.

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Abstract: Stone mastic asphalt is recognized for its remarkable durability, making it a crucial component for constructing pavements on aerital roads, which must withstand heavy traffic. When road authorities choose asphalt for main roads under these conditions, they often prefer stone mastic asphalt. The most crucial aspect of this type of asphalt is ensuring that SMA is implemented correctly, as it has excellent performance characteristics. However, improper implementation can lead to changes in performance. European countries favor SMA for its outstanding performance. There have been recent

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Goswami, Ayush, and Mahesh Ram Patel. "Enhancing the Properties of Stone Mastic Asphalt Using Bagasse and Coir Fiber as Additives." International Journal for Research in Applied Science and Engineering Technology 11, no. 3 (2023): 452–65. http://dx.doi.org/10.22214/ijraset.2023.49460.

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Abstract: Stone mastic asphalt is recognized for its remarkable durability, making it a crucial component for constructing pavements on aerital roads, which must withstand heavy traffic. When road authorities choose asphalt for main roads under these conditions, they often prefer stone mastic asphalt. The most crucial aspect of this type of asphalt is ensuring that SMA is implemented correctly, as it has excellent performance characteristics. However, improper implementation can lead to changes in performance. European countries favor SMA for its outstanding performance. There have been recent

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Surekha, B., Pandu R. Vundavilli, and M. B. Parappagoudar. "Reverse Modeling of Green Sand Mould System Using Fuzzy Logic-Based Approaches." Journal for Manufacturing Science & Production 12, no. 1 (2012): 1–16. http://dx.doi.org/10.1515/jmsp-2011-0012.

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AbstractIn the present study, reverse mapping problems of green sand mould system have been solved using Fuzzy Logic (FL)-based approaches. It is a complicated process, in which the quality of the castings is influenced by the mould properties (that is, green compression strength, permeability, hardness and others). In forward modeling, the outputs are expressed as the functions of input variables, whereas in reverse modeling, the later are represented as the functions of the former. The main advantage of reverse modeling lies in the fact that it helps in effective real-time control of the pro

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Hussein, Shalau Farhad, Zena Ez Dallalbashi, and Ahmed Burhan Mohammed. "Anomaly detection in internet of medical things with artificial intillegence." Eastern-European Journal of Enterprise Technologies 1, no. 4 (121) (2023): 56–62. http://dx.doi.org/10.15587/1729-4061.2023.274575.

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Internet of things (IoT) becomes the most popular term in the recent advances in Healthcare devices. The healthcare data in the IoT process and structure is very sensitive and critical in terms of healthy and technical considerations. Outlier detection approaches are considered as principal tool or stage of any IoT system and are mainly categorized in statistical and probabilistic, clustering and classification-based outlier detection. Recently, fuzzy logic (FL) system is used in ensemble and cascade systems with other ML-based tools to enhance outlier detection performance but its limitation

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Shalau, Farhad Hussein, Ez. Dallalbashi Zena, and Burhan Mohammed Ahmed. "Anomaly detection in internet of medical things with artificial intillegence." Eastern-European Journal of Enterprise Technologies 1, no. 4 (121) (2023): 56–62. https://doi.org/10.15587/1729-4061.2023.274575.

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Internet of things (IoT) becomes the most popular term in the recent advances in Healthcare devices. The healthcare data in the IoT process and structure is very sensitive and critical in terms of healthy and technical considerations. Outlier detection approaches are considered as principal tool or stage of any IoT system and are mainly categorized in statistical and probabilistic, clustering and classification-based outlier detection. Recently, fuzzy logic (FL) system is used in ensemble and cascade systems with other ML-based tools to enhance outlier detection performance but its limitation

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Nasser, Khalid W., Salam J. Yaqoob, and Zainab A. Hassoun. "Improved dynamic performance of photovoltaic panel using fuzzy logic-MPPT algorithm." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 2 (2021): 617–24. https://doi.org/10.11591/ijeecs.v21.i2.pp617-624.

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The nonlinear characteristics and intense credence dependence of photovoltaic (PV) panel on the solar irradiance and ambient temperature demonstrate important challenges for researchers in the PV panel topic. To overcome these problems, the maximum power point tracking (MPPT) controller is needed which can improve the PV panel efficiency. In other words, for maximum efficiency, the MPPT controller can help to extract the optimal and overall available output power from the PV panel at different output load conditions. Fuzzy logic (FL) is one of the strongest techniques in the extracting of MPP

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Redi, Mekonnen, Mihret Dananto, and Natesan Thillaigovindan. "A Bi-level Neuro-Fuzzy System Soft Computing for Reservoir Operation." International Journal of Advances in Soft Computing and its Applications 13, no. 3 (2021): 224–47. http://dx.doi.org/10.15849/ijasca.211128.15.

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Reservoir operation studies purely based on the storage level, inflow, and release decisions during dry periods only fail to serve the optimal reservoir operation policy design because of the fact that the release decision during this period is highly dependent on wet season water conservation and flood risk management operations. Imperatively, the operation logic in the two seasons are quite different. If the two operations are not sufficiently coordinated, they may produce poor responses to the system dynamics. There are high levels of uncertainties on the model parameters, values and how th

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Nagham, Hikmat Aziz, and Abdulrhman Al-Flaiyeh Maha. "Critical clearing time estimation of multi-machine power system transient stability using fuzzy logic." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 1 (2023): 125–33. https://doi.org/10.11591/ijece.v13i1.pp125-133.

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Studying network stability requires determining the best critical clearing time (CCT) for the network after the fault has occurred. CCT is an essential issue for transient stability assessment (TSA) in the operation, security, and maintenance of an electrical power system. This paper proposes an algorithm to obtain CCT based on fuzzy logic (FL) under fault conditions, for a multi-machine power system. CCT was estimated using a two-step fuzzy logic algorithm: the first step is to calculate Δt, which represents the output of the FL, while maximum angle deviation (δmax) represents the

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Ali, Sumon, Ismail Hossain, Mohammad Abdul Jalil, and Joy Sarkar. "Fuzzy Logic Model to Predict the Color Properties of Pineapple Leaf Fiber Fabric." Journal of Engineering Science 15, no. 2 (2025): 13–27. https://doi.org/10.3329/jes.v15i2.82158.

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This study aimed to fabricate a Fuzzy Logic (FL) model based on dye, salt, and alkali concentrations to predict the color properties of pineapple leaf fiber (PALF) fabric dyed with reactive dyes. The nonlinear and interactive nature of these factors makes it challenging to make an exact model using mathematical or statistical methods. Additionally, artificial neural networks and neuro-fuzzy models require extensive trial data for parameter optimization, which is often difficult to obtain from dyeing industries. In this context, FL is an effective modeling tool, capable of handling nonlinear co

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Hwang, Wen-Shyang, Teng-Yu Cheng, Yan-Jing Wu, and Ming-Hua Cheng. "Adaptive Handover Decision Using Fuzzy Logic for 5G Ultra-Dense Networks." Electronics 11, no. 20 (2022): 3278. http://dx.doi.org/10.3390/electronics11203278.

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With the explosive increase in traffic volume in fifth-generation (5G) mobile wireless networks, an ultra-dense network (UDN) architecture, composed of highly concentrated millimeter-wave base stations within the fourth-generation (4G) system, has been developed. User equipment (UE) may encounter more frequent handover opportunities when moving in a UDN. Conventional handover schemes are too simple to adapt to the diverse handover scenarios encountered in 5G UDNs because they consider only UE signal strength. Unnecessary handovers aggravate the ping-pong effect and degrade the quality of servi

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Kuk, Kristijan, Aleksandar Stanojević, Petar Čisar, et al. "Applications of Fuzzy Logic and Probabilistic Neural Networks in E-Service for Malware Detection." Axioms 13, no. 9 (2024): 624. http://dx.doi.org/10.3390/axioms13090624.

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The key point in the process of agent-based management in e-service for malware detection (according to accuracy criteria) is a decision-making process. To determine the optimal e-service for malware detection, two concepts were investigated: Fuzzy Logic (FL) and Probabilistic Neural Networks (PNN). In this study, three evolutionary variants of fuzzy partitioning, including regular, hierarchical fuzzy partitioning, and k-means, were used to automatically process the design of the fuzzy partition. Also, this study demonstrates the application of a feature selection method to reduce the dimensio

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W. Nasser, Khalid, Salam J. Yaqoob, and Zainab A. Hassoun. "Improved dynamic performance of photovoltaic panel using fuzzy Logic-MPPT algorithm." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 2 (2021): 617. http://dx.doi.org/10.11591/ijeecs.v21.i2.pp617-624.

Full text

Abstract:

The nonlinear characteristics and intense credence dependence of photovoltaic (PV) panel on the solar irradiance and ambient temperature demonstrate important challenges for researchers in the PV panel topic. To overcome these problems, the maximum power point tracking (MPPT) controller is needed which can improve the PV panel efficiency. In other words, for maximum efficiency, the MPPT controller can help to extract the optimal and overall available output power from the PV panel at different output load conditions. Fuzzy logic (FL) is one of the strongest techniques in the extracting of MPP

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Bonilla Huerta, Edmundo, Eduardo Martínez Juárez, Roberto Morales Caporal, and Eduardo Vázquez Urbina. "Fuzzy Logic and Machine Learning Algorithms for Detection and Classification of Falls and Activities of Daily Living." International Journal of Combinatorial Optimization Problems and Informatics 15, no. 4 (2024): 42–60. http://dx.doi.org/10.61467/2007.1558.2024.v15i4.497.

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This article analyses the movements of young and elderly people using data collected from an accelerometer and a gyroscope. This study proposes Type I fuzzy logic (FL) and several machine learning (ML) algorithms for the detection and classification of daily life movements and falls. The results obtained demonstrate that a fuzzy logic system can efficiently integrate data from an accelerometer and a gyroscope to classify falls and movements in daily life with 97.4% accuracy. When ML classifiers are used, the performance across several algorithms is also very high.

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