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Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas

econometrics and other areas. Processing uncertainty is essential, considering that computers - which help us understand real-life processes and make;

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Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas

econometrics and other areas. Processing uncertainty is essential, considering that computers - which help us understand real-life processes and make;

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Statistical Methods for Fuzzy Data

characterizing function of fuzzy measurement results. Furthermore, statistical methods are then generalized to the analysis of fuzzy data and fuzzy a;

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Robustness in Econometrics

mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for;

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Fuzzy Image Processing and Applications with MATLAB

approaches and those suggested by different authors, offering data and insights that will be useful to teachers, scientists, and engineers, among;

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Information Processing and Management of Uncertainty in Knowledge-Based Systems

learning II; XAI; image processing; temporal data processing; text analysis and processing; fuzzy interval analysis; theoretical and applied;

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Information Processing and Management of Uncertainty in Knowledge-Based Systems

learning II; XAI; image processing; temporal data processing; text analysis and processing; fuzzy interval analysis; theoretical and applied;

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Information Processing and Management of Uncertainty in Knowledge-Based Systems

learning II; XAI; image processing; temporal data processing; text analysis and processing; fuzzy interval analysis; theoretical and applied;

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How Interval and Fuzzy Techniques Can Improve Teaching

a large number of statistical studies of different teaching techniques, the authors combined statistical and fuzzy approaches to process the;

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Fuzzy Recurrence Plots and Networks with Applications in Biomedicine

, and fuzzy logic. After basic concepts of these three approaches are introduced, this book presents recently developed methods known as;

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Fuzzy Recurrence Plots and Networks with Applications in Biomedicine

, and fuzzy logic. After basic concepts of these three approaches are introduced, this book presents recently developed methods known as;

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Fuzzy Approach to Reasoning and Decision-Making

contributions from other areas, like fuzzy classifications and the use of fuzzy approaches in quantum physics. The volume contains papers presented at;

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10th International Conference on Theory and Application of Soft Computing, Computing with Words and Perceptions - ICSCCW-2019

computing with words, such as uncertain computation, decision-making under imperfect information, neuro-fuzzy approaches, deep learning, natural;

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Predictive Econometrics and Big Data

techniques - which directly aim at predicting economic phenomena; and big data techniques - which enable us to handle the enormous amounts of data;

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Fuzzy Transforms for Image Processing and Data Analysis

traditional methods. Emphasis is placed on applications of fuzzy transforms to innovative problems, such as massive data mining, and image and video;

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Fuzzy Transforms for Image Processing and Data Analysis

traditional methods. Emphasis is placed on applications of fuzzy transforms to innovative problems, such as massive data mining, and image and video;

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Developing Econometrics

that benefit econometric practice. It deals with exploratory data analysis, a prerequisite to statistical modelling and part of data mining. It;

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Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations

; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications;

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Computational Learning Approaches to Data Analytics in Biomedical Applications

Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis;

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The Signed Distance Measure in Fuzzy Statistical Analysis

levels; the other is an extension of the multi-ways analysis of variance to the space of fuzzy sets. To illustrate these approaches, the book;

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Modeling Fuzzy Spatiotemporal Data with XML

This book offers in-depth insights into the rapidly growing topic of technologies and approaches to modeling fuzzy spatiotemporal data with;

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Modeling Fuzzy Spatiotemporal Data with XML

This book offers in-depth insights into the rapidly growing topic of technologies and approaches to modeling fuzzy spatiotemporal data with;

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Constrained Statistical Inference

inference under inequality constraints and to apply the theory to problems in a variety of areas. Constrained Statistical Inference: Order;

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Fuzzy Set Theory

in the Social Sciences provides a systematic, yet practical guide for researchers wishing to combine fuzzy set theory with standard statistical;

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Intelligent Signal Processing

is extracted from incoming signal and noise data, making few assumptions about the statistical structure of signals and their environment. Intelligent;

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Computational Intelligence in Sensor Networks

ranging from small-scale data processing to big data processing realized through sensor nodes with the help of computational approaches. Advances;

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Fuzzy C-means Clustering using Pattern Recognition

recognize the pattern and the structure in data. The fuzzy approach that i have chosen to process the data completely depends on the type of data;

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