fuzzy model
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The mathematics offers the formal models in which variables and parameters can have the different interpretation. The application of formal model is then in the hands of experience and mostly also of knowledge, out of the mathematical way. Hence it followed that in the case, when the function of certain model is ensured by the software of computer, the everybody user to have know of a structure of mathematical models, their sense and possibilities. For example we have any object the role of fuzzy--mathematics in the one medical diagnostic situation. We shall attempt to show that the fundamental concepts of the theory of semantic information can be defined in a very straightforward way on the basis of the theory of fuzzy semantic information that has been recently developed by Zadeh and Shannon.
- MeSH
- diagnóza počítačová * MeSH
- expertní systémy * MeSH
- fuzzy logika * MeSH
- lidé MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- anglický abstrakt MeSH
- časopisecké články MeSH
Expertní znalosti v humanitních oborech jsou charakteristické svou nejistotou a neurčitostí. Údaje, se kterými expert (např. lékař) pracuje, jsou často nepřesné, nejisté a neurčité, ale právě podle takových informací se odborník musí rozhodovat. Zpracováním neurčitých a nejistých dat se zabývá tzv. fuzzy logika, která pracuje s fuzzy množinami. V celé řadě běžných situací a úloh, pro něž nemáme přesné matematické modely, je expert schopný svou znalost a správné řešící postupy formulovat v přirozeném jazyce, a to pomocí tzv. jestllže-pak pravidel. Na nich založené pravidlové fuzzy systémy představují matematický model, který vzniká přímo ze zkušenosti popsané příslušným odborníkem a v jeho přirozeném jazyce. Zároveň tak získáváme i způsob vyjadřování, kterému rozumí počítač a umí s ním pracovat. Fuzzy systémy se mohou uplatnit v celé řadě konkrétních situací z medicínské praxe, příkladem mohou být diagnostické expertní systémy nebo zpětnovazební fuzzy regulační zařízení.
Uncertalnty and indetermlnacy are typlcal of expert knowledge in humanlties. Data processed by an expert (e. g. a medlcal doctor) are often imprecise, uncertaln, and indeterminate. It is, however, these data according to whlch the expert has to make his/her decisions. Processing of indeterminate and uncertain data Is the subject of fuzzy logic, whlch deals with fuzzy sets. In a broad variety of sltuations and tasks for whlch no precise mathematlcal models are avallable, an expert Is able to formulate his/her knowledge and problém solving stratégy In a natural language by meansof so-called"if-then"rules.Rule-based fuzzy systems, which are based on these rules, represent a mathematical model that results dlrectly from the experťs experience descrlbed In a natural language. In addltion to that, fuzzy systems provlde us with a means of communicatlon easlly usable and thus comprehensible by a computer. Fuzzy systems can be applled to a broad spectrum of sítuations in medicíně, such as diagnostic expert systems and feedback fuzzy control devlces.
In this paper we demonstrate that fuzzy logic can provide a better tool for predicting recycling behaviour than the customarily used linear regression. To show this, we take a set of empirical data on recycling behaviour (N=664), which we randomly divide into two halves. The first half is used to estimate a linear regression model of recycling behaviour, and to develop a fuzzy logic model of recycling behaviour. As the first comparison, the fit of both models to the data included in estimation of the models (N=332) is evaluated. As the second comparison, predictive accuracy of both models for "new" cases (hold-out data not included in building the models, N=332) is assessed. In both cases, the fuzzy logic model significantly outperforms the regression model in terms of fit. To conclude, when accurate predictions of recycling and possibly other environmental behaviours are needed, fuzzy logic modelling seems to be a promising technique.
- MeSH
- fuzzy logika * MeSH
- lidé MeSH
- lineární modely * MeSH
- recyklace * statistika a číselné údaje MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
This article focuses on the development of algorithms for a smart neurorehabilitation system, whose core is made up of artificial neural networks. The authors of the article have proposed a completely unique transfer of ACE-R results to the CHC model. This unique approach allows for the saturation of the CHC model domains according to modified ACE-R factor analysis. The outputs of the proposed algorithm thus enable the automatic creation of a personalized and optimized neurorehabilitation plan for individual patients to train their cognitive functions. A set of tasks in 6 levels of difficulty (level 1 to level 6) was designed for each of the nine CHC model domains. For each patient, the results of the ACE-R screening helped deter-mine the specific CHC domains to be rehabilitated, as well as the initial gaming level for rehabilitation in each domain. The proposed artificial neural network algorithm was adapted to real data from 703 patients. Experimental outputs were compared to the outputs of the initially designed fuzzy expert system, which was trained on the same real data, and all outputs from both systems were statistically evaluated against expert conclusions that were available. It is evident from the conducted experimental study that the smart neurorehabilitation system using artificial neural networks achieved significantly better results than the neurorehabilitation system whose core is a fuzzy expert system. Both algorithms are implemented into a comprehensive neurorehabilitation portal (Eddie), which was supported by a research project from the Technology Agency of the Czech Republic.
- MeSH
- algoritmy MeSH
- expertní systémy * MeSH
- fuzzy logika MeSH
- lidé MeSH
- neuronové sítě MeSH
- neurorehabilitace * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
This research proposes an assessment and decision support model to use when a driver should be examined about their propensity for traffic accidents, based on an estimation of the driver's psychological traits. The proposed model was tested on a sample of 305 drivers. Each participant completed four psychological tests: the Barratt Impulsiveness Scale (BIS-11), the Aggressive Driving Behaviour Questionnaire (ADBQ), the Manchester Driver Attitude Questionnaire (DAQ) and the Questionnaire for Self-assessment of Driving Ability. In addition, participants completed an extensive demographic and driving survey. Various fuzzy inference systems were tested and each was defined using the well-known Wang-Mendel method for rule-base definition based on empirical data. For this purpose, a programming code was designed and utilized. Based on the obtained results, it was determined which combination of the considered psychological tests provides the best prediction of a driver's propensity for traffic accidents. The best of the considered fuzzy inference systems might be used as a decision support tool in various situations, such as in recruitment procedures for professional drivers. The validity of the proposed fuzzy approach was confirmed as its implementation provided better results than from statistics, in this case multiple regression analysis.
- MeSH
- agrese MeSH
- bezpečnost MeSH
- dopravní nehody * MeSH
- dospělí MeSH
- fuzzy logika MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- postoj MeSH
- průzkumy a dotazníky MeSH
- psychologické modely * MeSH
- regresní analýza MeSH
- řízení motorových vozidel psychologie MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
A fuzzy model has been developed for the optimization of high-shear wet granulation wetting on a plant scale depending on the characteristics of pharmaceutical active substance particles. The model optimized on the basis of experimental data involves a set of rules obtained from expert knowledge and full-scale process data. The skewness coefficient of particle size distribution and the tapped density of the granulated mixture were chosen as the model input variables. The output of the fuzzy ruled system is the optimal quantity of wetting liquid. In comparison to manufacturing practice, a very strong sensitivity of the optimal quantity of the added wetting liquid to the size and shape of the active substance particles has been identified by fuzzy modeling.
Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.
The aim of this study was a comparison of risk stratification for death in patients after myocardial infarction (MI) and of risk stratification for malignant arrhythmias in patients with implantable cardioverter-defibrillator (ICD). The individual risk factors and more complex approaches were used, which take into account that a borderline between a risky and non-risky value of each predictor is not clear-cut (fuzzification of a critical value) and that individual risk factors have different weight (area under receiver operating curve – AUC or Sommers´ D – Dxy). The risk factors were baroreflex sensitivity, ejection fraction and the number of ventricular premature complexes/hour on Holter monitoring. Those factors were evaluated separately and they were involved into logit model and fuzzy models (Fuzzy, Fuzzy- AUC, and Fuzzy-Dxy). Two groups of patients were examined: a) 308 patients 7-21 days after MI (23 patients died within period of 24 month); b) 53 patients with left ventricular dysfunction examined before implantation of ICD (7 patients with malignant arrhythmia and electric discharge within 11 month after implantation). Our results obtained in MI patients demonstrated that the application of logit and fuzzy models was superior over the risk stratification based on algorithm where the decision making is dependent on one parameter. In patients with implanted defibrillator only logit method yielded statistically significant result, but its reliability was doubtful because all other tests were statistically insignificant. We recommend evaluating the data not only by tests based on logit model but also by tests based on fuzzy models.
- MeSH
- algoritmy MeSH
- baroreflex MeSH
- časové faktory MeSH
- defibrilátory implantabilní MeSH
- elektrická defibrilace přístrojové vybavení MeSH
- elektrokardiografie ambulantní MeSH
- financování organizované MeSH
- fuzzy logika MeSH
- hodnocení rizik MeSH
- infarkt myokardu mortalita patofyziologie MeSH
- komorové extrasystoly patofyziologie MeSH
- lidé středního věku MeSH
- lidé MeSH
- logistické modely MeSH
- prognóza MeSH
- reprodukovatelnost výsledků MeSH
- rizikové faktory MeSH
- ROC křivka MeSH
- senioři MeSH
- srdeční arytmie patofyziologie prevence a kontrola MeSH
- tepový objem MeSH
- ukazatele zdravotního stavu MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- senioři MeSH
- Publikační typ
- srovnávací studie MeSH
