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Modeling of Fuzzy Data
Fuzzy data are imprecise data obtained from measurements, perception or by interviewing people. Typically, those data are expressed in linguistic...
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Set-valued Data
Since fuzzy sets are generalizations of ordinary sets, we present in this Chapter the essentials of random set theory for statistics. This material...
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Tests of Hypothesis: Means
In many expositions of fuzzy methods, fuzzy techniques are described as an alternative to a more traditional statistical approach. In this chapter,...
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Fuzzy Time Series Analysis and Forecasting
The problem of system modeling and identification has attracted considerable attention during the past decades mostly because of a large number of...
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Fuzzy Statistical Analysis and Estimation
In social science research, many decisions, evaluations, or purposes of evaluations are done by surveys or questionnaires to seek for people’s...
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Aspects of Statistical Inference
With the background in previous chapters, problems of statistical inference with fuzzy data should be somewhat straightforward in principle! By that...
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Convergence of Random Fuzzy Sets
As in Chapter 5, we view random fuzzy sets as generalizations of random closed sets on R d , or more generally on...
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Random Fuzzy Sets
Statistical models for observations which are numbers or vectors are random variables and random vectors, respectively. Similarly, if the...
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Introduction
First like fuzzy logics are logics with fuzzy concepts, by fuzzy statistics we mean statistics with fuzzy data. Data are fuzzy when they are...
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Toward fair graph neural networks via real counterfactual samples
Graph neural networks (GNNs) have become pivotal in various critical decision-making scenarios due to their exceptional performance. However,...
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Assessment of spray patterns and efficiency of an unmanned sprayer used in planar growing systems
Automated technologies in precision agriculture enable unmanned systems to precisely target areas with chemicals through controlled nozzle movements....
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Predicting the rock cutting performance indices using gene expression modeling
In this study, a machine learning approach was employed to optimize the rock cutting process for construction practices and geotechnical engineering...
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Performance evaluation of nursing homes using finite mixtures of logistic models and M-quantile regression for binary data
Evaluating the performance of health care institutions is of paramount interest and it is often conducted using generalized linear mixed models. In...
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Aspect-based drug review classification through a hybrid model with ant colony optimization using deep learning
The task of aspect-level sentiment analysis is intricately designed to determine the sentiment polarity directed towards a specific target within a...
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Enhanced streamflow forecasting using attention-based neural network models: a comparative study in MOPEX basins
To mitigate the adverse effects of floods, hydrologists are increasingly turning to artificial intelligence methodologies to enhance streamflow...
