concept

fuzzy logic

Also known as: fuzzy logic, fuzzy logic systems, FL, Fuzzy logic, fuzzy logic method, Fuzzy Logic

Facts (23)

Sources

A comprehensive overview on demand side energy management ... link.springer.com Springer Mar 13, 2023 7 facts

referenceHasaranga W, Hemarathne R, Mahawithana M, Sandanuwan M, Hettiarachchi H, and Hemapala K (2017) presented a fuzzy logic-based battery state-of-charge (SOC) control strategy for smart microgrids.

referenceKeshtkar A, Arzanpour S, Keshtkar F, and Ahmadi P (2015) proposed a method for smart residential load reduction utilizing fuzzy logic, wireless sensors, and smart grid incentives, published in Energy and Buildings.

claimPanwar et al. (2017) presented a fuzzy logic-based energy management system (EMS) designed to reduce fluctuations and peak power in grid-tied microgrids.

claimIn the context of energy management optimization, FL stands for Fuzzy logic.

referenceHasaranga W, Hemarathne R, Mahawithana M, Sandanuwan M, Hettiarachchi H, and Hemapala K (2017) presented 'A fuzzy logic based battery SOC level control strategy for smart micro grid' at the 2017 Third International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-informatics (AEEICB), which proposes a fuzzy logic control strategy for battery state-of-charge (SOC) in smart microgrids.

referenceKeshtkar A, Arzanpour S, Keshtkar F, and Ahmadi P (2015) proposed a method for smart residential load reduction utilizing fuzzy logic, wireless sensors, and smart grid incentives.

referencePanwar et al. (2017) presented a fuzzy logic-based energy management system (EMS) designed to lower fluctuations and peak powers in a grid-tied microgrid.

Comprehensive framework for smart residential demand side ... nature.com Nature Mar 22, 2025 6 facts

referenceRavibabu et al. (2009) proposed a demand-side management technique for domestic load management using fuzzy logic.

claimFuzzy logic (FL) and artificial neural networks (ANN) are used individually or in hybrid ways for Residential Demand Side Management (RDSM) problems, though they depend on system parameter values and adequate training, making them difficult to formulate for complex issues.

claimFuzzy logic (FL) and artificial neural networks (ANN) are used in Residential Demand Side Management (RDSM) problems, either individually or in hybrid configurations, though they depend on system parameter values and adequate training, making them difficult to formulate for complex issues.

claimRecent research suggests that prominent methods for demand-side management include linear programming, nonlinear programming, dynamic programming, stochastic programming, robust optimization, fuzzy logic, metaheuristic or evolutionary optimization, artificial neural networks, and game theory.

claimProminent methods suggested in recent research for demand-side management include linear programming, nonlinear programming, dynamic programming, stochastic programming, robust optimization, fuzzy logic, metaheuristic or evolutionary optimization, artificial neural networks, and game theory.

A Comprehensive Review of Neuro-symbolic AI for Robustness ... link.springer.com Springer Dec 9, 2025 6 facts

referenceNeuro-fuzzy systems leverage fuzzy logic in neuro-symbolic AI by embedding fuzzy rule bases into neural network architectures to make logical components differentiable.

claimFuzzy rule-based systems have been historically used in medical diagnosis to handle symptomatic uncertainty.

claimUncertainty Quantification is embedded in neuro-symbolic models through methods such as probabilistic symbolic reasoning, Bayesian neural modules, or fuzzy logic systems.

claimNeuro-symbolic systems quantify uncertainty by propagating neural prediction uncertainties through logic rules, often utilizing fuzzy logic or probabilistic logic in the background.

referenceFuzzy logic handles uncertainty by allowing truth values to be degrees of belief between 0 and 1, utilizing membership functions that map real inputs to a truth degree in a fuzzy set.

referenceChen, X., Hu, Z., and Sun, Y. utilized fuzzy logic to perform logical query answering on knowledge graphs, as detailed in the 2022 Proceedings of the AAAI Conference on Artificial Intelligence.

A critical review on techno-economic analysis of hybrid renewable ... link.springer.com Springer Dec 6, 2023 3 facts

procedureSingh et al. (2015) performed a technical and economic feasibility assessment of a solar power-hydrogen fuel cell hybrid Combined Flow Power System (CFPS) for an academic research building in India using HOMER software and the Fuzzy Logic (FL) program to calculate capital and replacement costs.

claimBelmili et al. developed a fuzzy logic-based control and sizing method for photovoltaic-to-air current power conversion systems.

claimArtificial Intelligence technologies, including deep learning networks, fuzzy logic, and evolutionary algorithms, can be used to build more efficient decentralized power control systems to address the issue of complex communication protocols.

A Comprehensive Review on Residential Demand Side Management ideas.repec.org MDPI 1 fact

referenceSébastien Bissey, Sébastien Jacques, and Jean-Charles Le Bunetel published 'The Fuzzy Logic Method to Efficiently Optimize Electricity Consumption in Individual Housing' in the journal Energies in October 2017.