This article is a continuation of a previous one named Fuzzy model use for prediction of the state of emergency of river basin in the case of flash flood (Janál & Starý, 2009), where the potential applications of fuzzy logic in the field of flash flood forecasting were described. Flash flood forecasting needs a specific approach because of the character of torrential rainfall. Storms are very difficult to forecast in space and time. The hydrological models designed for flash flood prediction have to be able to work with very uncertain input data. Moreover, the models have to be capable of evaluating the level of danger in as short a time as possible because of the highly dynamic character of the modeled process. The fuzzy model described in the previous article was modified into a form usable in operational hydrology and a simulation of its operational application was run using this model. The selected time period for the simulation was the summer of 2009, when numerous flash floods occurred in Czech Republic. The topic of this article is the preparation of the model for practical use and the results of the simulation of its operation. and Článek navazuje na předchozí článek s názvem Fuzzy model pro předpověď stupně ohroženosti povodí povodněmi z přívalových dešťů (Janál, Starý, 2009a). V úvodním článku byly popsány možnosti využití fuzzy logiky v problematice operativních předpovědí povodní způsobených přívalovými srážkami. Předpověď tohoto druhu povodní vyžaduje specifický přístup, jelikož výskyt přívalových srážek v prostoru a čase lze, díky jejich charakteru, jen stěží předpovídat. Hydrologické modely, určené pro předpověď povodní jimi způsobenými musí být schopny pracovat s velmi neurčitými vstupy. Díky vysoké dynamice předpovídaného procesu musí být navíc schopny vyhodnotit vstupní data ve velmi krátkém čase. Fuzzy model, popsaný v prvním díle, byl upraven do podoby využitelné v operativní hydrologii a byl otestován pomocí simulace operativního provozu ve zvoleném období z léta 2009, kdy byla ČR zasažena četnými povodněmi z přívalových srážek. Úpravy modelu pro praktické využití a vyhodnocení zpětné simulace jeho provozu jsou předmětem předloženého navazujícího článku.
Intrusion detection systems are increasingly a key part of systems defense. Various approaches to intrusion detection are currently being used, but they are relatively ineffective. Artificial Intelligence plays a driving role in security services. This paper proposes a dynamic model of intelligent intrusion detection system, based on a specific AI approach for intrusion detection. The techniques that are being investigated include fuzzy logic with network profiling, which uses simple data mining techniques to process the network data. The proposed hybrid system combines anomaly and misuse detection. Simple fuzzy rules allow us to construct if-then rules that reflect common ways of describing security attacks. We use DARPA dataset for training and benchmarking.
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., P. Honzík ... [et al.]., and Obsahuje bibliografii a bibliografické odkazy
The paper addresses the problém of efficient and adequate representation of functions using two soft computing techniques: fuzzy logic and neural networks. The principle approach to the construction of approximating formulas is discussed. We suggest a generalized definition of the normál forms in predicate BL and ŁII logic and prove conditional equivalence between a formula and each of its normal forms. Some mutual relations between the normál forms will be also established.
In this paper we preseiit analytic sequent and hypersequent calculi for
Product logic II, an iinportant t-norm based fuzzy logic with conjunction interpreted as multiplication on the real unit interval [0,1], and Cancellative hoop logic CHL, a related logic with product conjunction interpreted on the real unit interval with 0 rernoved.
In this paper we present some results concerning the variety of divisible
MV-algebras. Any free divisible MV-algebra is an algebra of continuous
piecewise linear functions with rational coefficients. Correspondingly, the Rational Łukasiewicz logic is defined and its tautology problem is shown to be co-NP-complete.
The basic fuzzy logic BL is extended by two unary connectives L, U
(lower, upper) whose standard semantics is, given a continuous t-norm, the function assigning to each x € [0,1] the biggest idempotent < x (least idempotent > x). An axiom system is presented and shown complete with respect to the corresponding class of algebras. But the set of tautologies for a fixed continuous t-norm may have an arbitrarily high degree of insolvability.
We investigate some (universal algebraic) properties of residuated lattices—algebras which play the role of structures of truth values of various systems of fuzzy logic.
Digital Watermarking (DW) based on computational intelligence (CI) is currently attracting considerable interest from the research community. This article provides an overview of the research progress in applying CI methods to the problem of DW. The scope of this review will encompass core methods of CI, including rough sets (RS), fuzzy logic (FL), artificial neural networks (ANNs), genetic algorithms (GA), swarm intelligence (SI), and hybrid intelligent systems. The research contributions in each field are systematically summarized and compared to highlight promising new research directions. The findings of this review should provide useful insights into the current DW literature and be a good source for anyone who is interested in the application of CI approaches to DW systems or related fields. In addition, hybrid intelligent systems are a growing research area in CI.
Motivated by the fact that logicians and computer scientists working
in fuzzy logic hardly seem to take notice of the prolific and broad discourse on vagueness in analytic philosophy, we provide an overview of the most irnportant topics and trends in the ‘vagueness debate’. In particnlar we list a range of different phenornena of vagueness that should be addressed by any full-fledged theory of vagueness. Moreover we propose a classiíication of theories of vagueness and suggest various criteria for their evaluation.