Search results for "Inference"

Inverse Kinematics for a 7 DOF Robotic Arm Using the Redundancy Circle and ANFIS Models

2014

In this paper we have presented a method to solve the inverse kinematics problem of a redundant robotic arm with seven degrees of freedom and a human like workspace based on mathematical equations, ANFIS implementation and Simulink models. For better visualization of the kinematics simulation a CAD model that mimics the real robotic arm was created into SolidWorks® and then the CAD parts were converted into SimMechanics model.

What do we mean by diversity? : the path towards quantification

2018

The concept of biological diversity has evolved from a simple count of species to more sophisticated measures that are sensitive to relative abundances and even to evolutionary divergence times between species. In the course of this evolution, diversity measures have often been borrowed from other disciplines. Biological reasoning about diversity often implicitly assumed that measures of diversity had certain mathematical properties, but most of biologys traditional diversity measures did not actually possess these properties, a situation which often led to mathematically and biologically invalid inferences. Biologists now usually transform the traditional measures to the «effective number …

New insights in Bayesian Survival Analysis in Ecology

2020

La fauna silvestre está asediada. Y ésta no es solo una frase impactante con la que empezar una tesis, tristemente, es una realidad. En el último siglo, muchas especies han disminuido drásticamente, mientras que otras afrontan su extinción debido, principalmente, a los rápidos cambios (y a gran escala) ocurridos tanto en hábitats como en ecosistemas. El cambio climático, las especies invasoras, la caza ilegal y la sobrepesca son sólo algunas de las principales amenazas que afectan a las poblaciones de animales silvestres en la actualidad. Para abordar este problema, se requiere de un compromiso a todos los niveles, desde las comunidades locales hasta los gobiernos, pasando por los expertos,…

Importance of proper conduct of clinical trials

2021

Predictive distributions that mimic frequencies over a restricted subdomain

2020

A predictive distribution over a sequence of $$N+1$$ events is said to be “frequency mimicking” whenever the probability for the final event conditioned on the outcome of the first N events equals the relative frequency of successes among them. Exchangeable distributions that exhibit this feature universally are known to have several annoying concomitant properties. We motivate frequency mimicking assertions over a limited subdomain in practical problems of finite inference, and we identify their computable coherent implications. We provide some examples using reference distributions, and we introduce computational software to generate any complete specification desired. Theorems on reducti…

Machine learning of microbial interactions using abductive ILP and hypothesis frequency/compression estimation

2021

Interaction between species in microbial communities plays an important role in the functioning of all ecosystems, from cropland soils to human gut microbiota. Many statistical approaches have been proposed to infer these interactions from microbial abundance information. However, these statistical approaches have no general mechanisms for incorporating existing ecological knowledge in the inference process. We propose an Abductive/Inductive Logic Programming (A/ILP) framework to infer microbial interactions from microbial abundance data, by including logical descriptions of different types of interaction as background knowledge in the learning. This framework also includes a new mechanism …

Predicting the Short-Term Exchange Rate Between United State Dollar and Czech Koruna Using Hilbert-Huang Transform and Fuzzy Logic

2017

In this paper, the combination of the Hilbert-Huang Transform, fuzzy logic and an embedding theorem is described to predict the short-term exchange rate from United States dollar to Czech Koruna. By Using the Hilbert-Huang Transform as an adaptive filter, the proposed method decreases the embedding dimension space from five (original samples) to four (de-noising samples). This dimension space provides the number of inputs to the fuzzy rule base system, which causes the number of rules, the time for training and the inference process to decrease. Experimental results indicated that this method achieves higher accuracy prediction than the direct use of original data.

Fuzzy control of pH using NAL

1991

Abstract A fuzzy controller for a neutralization process is described. The controller was set up for a laboratory pilot plant. The approach is shown to be effective and can be extended to highly nonlinear and nonstationary processes. The “operator” knowledge encoded in the rules was obtained by several experimental runs of the system using manual control. Rules are composed using the max-min compositional rule of inference. The use of metarules, which depends on controller performance and on active disturbances, makes the controller behave like an adaptive controller. The control program is encoded in NAL, a new experimental logic programming language that was first used in this work in a r…

Fuzzy modeling and control for a class of inverted pendulum system

2014

Published version of an article in the journal: Abstract and Applied Analysis. Also available from the publisher at: http://dx.doi.org/10.1155/2014/936868 Open Access Focusing on the issue of nonlinear stability control system about the single-stage inverted pendulum, the T-S fuzzy model is employed. Firstly, linear approximation method would be applied into fuzzy model for the single-stage inverted pendulum. At the same time, for some nonlinear terms which could not be dealt with via linear approximation method, this paper will adopt fan range method into fuzzy model. After the T-S fuzzy model, the PDC technology is utilized to design the fuzzy controller secondly. Numerical simulation res…

Prediction of stock index futures prices based on fuzzy sets and multivariate fuzzy time series

2015

Abstract This paper makes a prediction of Chinese stock index (CSI) future prices using fuzzy sets and multivariate fuzzy time series method. We select Chinese CSI 300 index futures as the research object. The fuzzy time series model combines the fuzzy theory and the time series theory, thus this model can solve the fuzzy data in stock index futures prices. This paper establishes a multivariate model and improves the accuracy of computation. By combing traditional fuzzy time series models and rough set method, we use fuzzy c-mean algorithm to make the data into discrete. Further more, we deal with the rules in mature modules of the rough set and then refine the rules using data mining algor…