An R package for handling fuzzy spatial data
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Updated
May 26, 2025 - R
An R package for handling fuzzy spatial data
linguistic fuzzy logic algorithms: mining for linguistic fuzzy association rules, composition of fuzzy relations, performing perception-based logical deduction (PbLD), and forecasting time-series using fuzzy rule-based ensemble (FRBE)
The RMCDA package is a comprehensive toolkit for Multi-Criteria Decision Analysis (MCDA), designed to facilitate the evaluation and ranking of alternatives based on multiple criteria. The package provides methods for implementing various MCDA techniques, including pairwise comparisons, partial-order analysis, and dominance-based decision rules.
Fuzzy Clustering Using Hybrid Fuzzy c-means and Fuzzy Particle Swarm Optimization (A Research Paper Implementation along with Self-organization feature map (SOFM) implementation)
Fuzzy inference system optimized by a genetic algorithm (Case study: Fuzzified hedging rules for a reservoir operation)
R-codes for feature selection method that is based on fuzzy entropy and similarity
Otimizando semáforo com Lógica Fuzzy / Optimizing traffic lights with Fuzzy Logic
Enhancing Boolean networks with continuous logical operators and edge tuning: smoothing simulations
Web app using fuzzy logic to evaluate how much compatibility a person has with the computer science career.
Automated identification of potential avalanche release areas using R. This extended model incorporates snowpack stability, aspect, and altitude to enhance avalanche hazard assessment, building upon the original work by Veitinger et al. Useful for avalanche forecasters and researchers.
This project aimed to develop an expert system using a Fuzzy Neural Network (FNN) to accurately predict insect pest populations in a large avocado farm in Kenya, providing valuable insights for decision-making and timely interventions in integrated pest management (IPM) practices
FuzzyLP CRAN R package providing Fuzzy Linear Programming methods
Data Fusion (open-access research monograph, 2015)
Improving breast cancer prediction through fuzzy rule-based reasoning.
R codes for K-Means Clustering and Fuzzy K-Means Clustering, along with improved versions
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