Show threadKees AntiFa van MalssenDec 31
@TCatInReality @kstrlworks reminds me of #FuzzyLogic we investigated 40 years ago when studying chemistry at the University. At least it had the right name.
Atilio FRANCOISOct 9, 2025
Modéliser l’incertitude et les transitions progressives dans QGIS : FuzzyAttributes V2
Développé pour QGIS, FuzzyAttributes V1 offrait déjà la possibilité de convertir des attributs numériques en valeurs floues, et de les combiner via des fonctions d’agrégation personnalisées.
La version 2 marque une étape importante : FuzzyAttributes intègre la transformation floue des rasters 🔗 https://shorturl.at/NURrC
#QGIS #FuzzyLogic #SIG #SpatialAnalysis #Geospatial #GIS #DecisionSupport t #Environnement
JdeBPSep 20, 2025

@ianb

BUG REPORT: The Economist is trying to introduce fuzzy logic. With quantum mechanical sub-heads.

https://economist.com/science-and-technology/2025/09/19/are-touchscreens-in-cars-dangerous

#QuestionHeadlines #FuzzyLogic #TheEconomist #QuantumMechanics

Are touchscreens in cars dangerous?

Probably—and safety organisations are beginning to take note

The Economist
Kianoosh ShakeriAug 28, 2025
Today I learned that fuzzy logic came to be thanks to an Iranian scientist, Lotfi A. Zadeh. Fuzzy mathematics play an important role in so many appliances and new tech, including your rice cooker and the AI you use daily.
Fuzzy logic allows computers to work with a degrees of truth rather than 1/0 or true/false. Fuzzy mathematics added a little humanity to our machines.
Think about it! We say the weather is warm, really hot, kind of cool, extremely cold, ETC. There's no just hot/cold. Machines can understand this using the fuzzy logic.
In simpler words, fuzzy logic is designed to mimic human reasoning by handling imprecise information.
I am proud of my country and my people, but I should emphasize that my current government is definitely not my people.
#Iran #FuzzyLogic #LotfiZadeh #Mathematics #AI #Tech #Computing
Saül Gordillo 🤖 📡 🚀Jul 27, 2025

🧠 NEW! Transparent Algorithm #96

“AI models reason, but do not think”

Meet Enric Trillas — pioneer of fuzzy logic and a key figure in Spain’s AI history. An essential read for anyone who wants to understand how it all began.

📖 https://open.substack.com/pub/transparentalgorithm/p/exclusive-interview-with-enric-trillas?r=f2io0&utm_medium=ios

#AI #FuzzyLogic #Trillas #AlgoritmoTransparente

🤖 Exclusive Interview with Enric Trillas 🎯 “AI models reason, but they don't think”

🧠 “I’m recognized as the pioneer in Spain of the fuzzy logic system, methods for dealing with language imprecision”

Transparent Algorithm
Sólo YoJul 9, 2025

Gestión de un sistema fotovoltaico por medio de algoritmos basados en lógica difusa bajo diversas condiciones ambientales

https://dialnet.unirioja.es/descarga/articulo/10097423.pdf

#physics #engineering #solarpower #solarsystem #fuzzylogic

Minoru SabaApr 29, 2025

In the times before "AI" hype there were washing machines with "fuzzy logic" and "neuro" whatever.

Found reddit comment:
"Fuzzy logic was an overhyped 90s phenomenon that was largely based on the belief that one could design a control system without an understanding of control theory and somehow it would magically turn out better. That reality never materialized."
https://www.reddit.com/r/engineering/comments/pwht4f/comment/heha0c2/

...leading to Bob Pease articles[1][2]:
1. https://www.electronicdesign.com/technologies/embedded/digital-ics/article/21757343/whats-all-this-fuzzy-logic-stuff-anyhow
2. https://www.electronicdesign.com/technologies/embedded/article/21757031/whats-all-this-ball-on-beam-balancing-stuff-anyhow
#FuzzyLogic

Knowledge ZoneApr 23, 2025

Embracing #Uncertainty: The Power of #FuzzyLogic in #Decision-Making : Medium

#Physicists Think They’ve Finally Seen #Evidence of #StringTheory : Pop Mech

We’ve #Misunderstood #Uranus all these years — period ($) : Nature

Check our latest #KnowledgeLinks

https://knowledgezone.co.in/resources/bookmarks

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PhilApr 12, 2025
@jaruzel add #fuzzylogic and I match some not none.
💧🌏 Greg CocksFeb 26, 2025
A Methodology For The Multitemporal Analysis Of Land Cover Changes And Urban Expansion Using Synthetic Aperture Radar (SAR) Imagery - A Case Study Of The Aburrá Valley In Colombia
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https://doi.org/10.3390/rs17030554 <-- shared paper
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#GIS #spatial #mapping #SyntheticApertureRadar #SAR #remotesensing #multitemporalanalysis #landcover #landcoverchange #clustering #kurtosis #fuzzylogic #kernelbasedmethod #machinelearning #spatialanalysis #spatiotemporal #geostatistics #model #modeling #AburráValley #Columbia #urban #urbanexpansion #population #growth #topography #monitoring #satellite #sentinel #valley #landuse #distribution #infrastructure #building #roads #naturalresources #environmental #conservation #monitoring #multitemporal
A Methodology for the Multitemporal Analysis of Land Cover Changes and Urban Expansion Using Synthetic Aperture Radar (SAR) Imagery: A Case Study of the Aburrá Valley in Colombia

The Aburrá Valley, located in the northwestern region of Colombia, has undergone significant land cover changes and urban expansion in recent decades, driven by rapid population growth and infrastructure development. This region, known for its steep topography and dense urbanization, faces considerable environmental challenges. Monitoring these transformations is essential for informed territorial planning and sustainable development. This study leverages Synthetic Aperture Radar (SAR) imagery from the Sentinel-1 mission, covering 2017–2024, to propose a methodology for the multitemporal analysis of land cover dynamics and urban expansion in the valley. The novel proposed methodology comprises several steps: first, monthly SAR images were acquired for every year under study from 2017 to 2024, ensuring the capture of surface changes. These images were properly calibrated, rescaled, and co-registered. Then, various multitemporal fusions using statistics operations were proposed to detect and find different phenomena related to land cover and urban expansion. The methodology also involved statistical fusion techniques—median, mean, and standard deviation—to capture urbanization dynamics. The kurtosis calculations highlighted areas where infrequent but significant changes occurred, such as large-scale construction projects or sudden shifts in land use, providing a statistical measure of surface variability throughout the study period. An advanced clustering technique segmented images into distinctive classes, utilizing fuzzy logic and a kernel-based method, enhancing the analysis of changes. Additionally, Pearson correlation coefficients were calculated to explore the relationships between identified land cover change classes and their spatial distribution across nine distinct geographic zones in the Aburrá Valley. The results highlight a marked increase in urbanization, particularly along the valley’s periphery, where previously vegetated areas have been replaced by built environments. Additionally, the visual inspection analysis revealed areas of high variability near river courses and industrial zones, indicating ongoing infrastructure and construction projects. These findings emphasize the rapid and often unplanned nature of urban growth in the region, posing challenges to both natural resource management and environmental conservation efforts. The study underscores the need for the continuous monitoring of land cover changes using advanced remote sensing techniques like SAR, which can overcome the limitations posed by cloud cover and rugged terrain. The conclusions drawn suggest that SAR-based multitemporal analysis is a robust tool for detecting and understanding urbanization’s spatial and temporal dynamics in regions like the Aburrá Valley, providing vital data for policymakers and planners to promote sustainable urban development and mitigate environmental degradation.

MDPI