(2022) 24(5):2511–2512 https://doi.org/10.1007/s40815-022-01370-4 Editorial Message: Fuzzy Machine Learning Algorithms with Applications Arising in Physical Problems Ali Ahmadian1 • Ahmad Taher Azar2 • Soheil Salahshour3 • Shun-Feng Su4 Published online: 20 July 2022 Ó The ...
machine learning frameworkfuzzy set covering algorithmconcept learningdescription languagesprepositional logicfuzzy logic classificationMany machine learning algorithms for concept learning have been developed using description languages based on prepositional logic. In this paper we show how to extend the so-...
fuzzy-rough-learnis a library of machine learning algorithms involving fuzzy rough sets, as well as data descriptors that can be used for one-class classification / novelty detection. It builds onscikit-learn, but uses a slightly different api, best illustrated with a concrete example: ...
GIS-based landslide susceptibility mapping of the Meghalaya-Shillong Plateau region using machine learning algorithms. Bulletin of Engineering Geology and the Environment, 2023, 82(5): 170. DOI:10.1007/s10064-023-03188-2 83. Rong, G., Li, K., Tong, Z. et al. Population amount risk ...
However, a comparative assessment of MCDM and machine learning has not been carried out for LSM in Slovakia. Therefore, the current study aimed to make a comparative analysis between fuzzy multi-criteria methods and machine learning algorithms. The current study was planned in the following sections...
as in this contribution. Nevertheless, common machine learning algorithms for multiclass text classification may introduce biases in the presence of imbalanced datasets (see, for instance, the discussion in Kaur et al.2019). Moreover, text classifications in this filed are generally based on binary...
Machine learning algorithms for wireless sensor networks: A survey 2019, Information Fusion Citation Excerpt : Detecting DoS attacks in distributed WSNs is an extremely challenging task with traditional approaches. In [185], a combination of game theoretic method and reinforcement learning based fuzzy Q...
Genetic algorithms Fuzzy approximation algorithms Computing with words and Quantum computation (4) Fuzzy Engineering Fuzzy control Fuzzy system engineering Fuzzy knowledge engineering Fuzzy management engineering Fuzzy design Fuzzy industrial engineering
Data mining algorithms can be used for developing CDSS. Data mining encompasses statistical analysis, machine learning techniques to discover useful and previously unknown patterns from voluminous amount of data from databases [5], [6]. The major data mining functionalities are association rule mining,...
Algorithms for (Q)SAR model building 4.2.2. Fuzzy neural networks Fuzzy neural networks are an example of a hybrid approach, which combines the learning ability of a neural network with the noise-handling capability of FL (Buckley and Hayashi, 1995; Nauck and Kruse, 1996). In their simplest...