Fuzzy modelling in population dynamics

By L. C. Barros, R. Bassanezi, P. Tonelli. 2000

275 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/ef35d65f625bb3524ff89466f963ad19ab47a7be

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Citations in the corpus

Intuitionistic fuzzy 2-normed space and some related concepts (2009, background): “population dynamics [4], chaos control [16], computer programming [19], nonlinear dynamical systems [20], medicine [3], etc.”
Coupled coincidence point theorems for contractions without commutative condition in intuitionistic fuzzy normed spaces (2011, background): “Several researchers have applied fuzzy theory to the well-known results in many fields, for example, quantum physics [20], nonlinear dynamical systems [21], population dynamics [22], computer programming [23], fixed point theorem [24-27], fuzzy stability problems [28-30], statistical convergence [31”
First Order Linear Homogeneous Ordinary Differential Equation in Fuzzy Environment Based On Laplace Transform (2013, methodology): “FDE has also used in many models such as HIV model (Hassan et al [7]), decay model (Diniz et al[6]), predator-prey model (Ahmad & Baets[12]), population model (Barros et al[11]), civil engineering (Oberguggenberger & Pittschmann [13] ) and hydraulic (Bencsik et al,[2]) models, Growth model [22], Bac”
Statistical convergence on intuitionistic fuzzy normed spaces (2008, methodology): “The fuzzy logic has been used not only in many engineering applications, such as, in bifurcation of non-linear dynamical systems [17], in the control of chaos [13], in the computer programming [16], in the population dynamics [ 4 ], in the quantum physics [21], but also in various branches of mathem”
First order homogeneous ordinary differential equation with initial value as triangular intuitionistic fuzzy number (2014, methodology): “For example, in population models [54], civil engineering [55], bioinformatics and computational biology [56], quantum optics and gravity [57], modeling hydraulic [58], HIV model [59], decay model [60], predator-prey model [61], population dynamics model [62], Friction model [63], Growth model [64],”
Decision Tree Models for Prediction of Macroinvertebrate Taxa in the River Axios (Northern Greece) (2007, background): “Artificial neural networks (Lek and Guegan 1999), fuzzy logic (Barros et al. 2000), decision trees (Quinlan 1986) and Bayesian belief networks (Adriaenssens et al. 2004) for instance have proven to have a high potential in habitat suitability modelling, as they combine reliable predictions with a…”