Temat: fuzzy database - Prolib Integro

Skocz do pozycji: 1.

Tytuł:: Decision support based methods to facilitate 3D volumetric locking in a new peer to peer based spatial database system
Autorzy:: Vert, G.
Morris, A.
Heaton, J. S.
Tematy:: baza danych
logika rozmyta
peer-to-peer
database
fuzzy logic; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Instytut Badań Systemowych PAN
Powiązania:: https://bibliotekanauki.pl/articles/970482.pdf Link otwiera się w nowym oknie
Opis:: Spatial databases present challenges to data management not found in typical RDBMS. Among these is the desire of users for highly distributed access to data. A new peer to peer database model is being developed that supports high distribution and concurrency of information access. Some aspects of the model are presented in this paper. However the new peer to peer model faces the critical problem of how to lock data as it becomes highly distributed. Conceptual methods borrowed from decision support and data mining are proposed to create a new type of locking model based on 3D volumetrics. The methods and mathematics proposed in this paper can become the basis for the implementation of a new type of peer to peer based spatial database system where spatial information flows to where it is needed on demand.
Dostawca treści:: Biblioteka Nauki

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Tytuł:: A Scheme for Template Security at Feature Fusion Level in Multimodal Biometric System
Autorzy:: Selwal, A.
Gupta, S. K.
Kumar, S.
Tematy:: feature template
biometric data
feature vectors
multimodal biometrics
fuzzy sets
database
feature fusion; Pokaż więcej
Wydawca:: Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Powiązania:: https://bibliotekanauki.pl/articles/102518.pdf Link otwiera się w nowym oknie
Opis:: Biometrics is the science of human recognition by means of their biological, chemical or behavioural traits. These systems are used in many real life applications simply from biometric based attendance system to providing security at a very sophisticated level. A biometric system deals with raw data captured using a sensor and feature template extracted from raw image. One of the challenges being faced by designers of these systems is to secure template data extracted from the biometric modalities of the user and protect the raw images. In order to minimize spoof attacks on biometric systems by unauthorised users one of the solutions is to use multi-biometric systems. Multi-modal biometric system works by using fusion technique to merge feature templates generated from different modalities of the human. In this work, a novel scheme is proposed to secure template during feature fusion level. The scheme is based on union operation of fuzzy relations of templates of modalities during fusion process of multimodal biometric systems. This approach serves dual purpose of feature fusion as well as transformation of templates into a single secured non invertible template. The proposed technique is irreversible, diverse and experimentally tested on a bimodal biometric system comprising of fingerprint and hand geometry. The given scheme results into significant improvement in the performance of the system with lower equal error rate and improvement in genuine acceptance rate.
Dostawca treści:: Biblioteka Nauki

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Tytuł:: Prediction of littoral drift with adaptive neuro-fuzzy inference system
Ocena dryfu morskiego z wykorzystaniem systemu ANFIS [Adaptive Neuro-Fuzzy Inference System]
Autorzy:: Sabet, M S
Naseri, M.A.
Sabet, H.S.
Tematy:: littoral sand drift
coastal zone
adaptive neuro-fuzzy inference system
validation
physical process
database; Pokaż więcej
Wydawca:: Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
Powiązania:: https://bibliotekanauki.pl/articles/81613.pdf Link otwiera się w nowym oknie
Opis:: The amount of sand moving parallel to a coastline forms a prerequisite for many harbor design projects. Such information is currently obtained through various empirical formulae. Despite so many works in the past, an accurate and reliable estimation of the rate of sand drift has still remained a problem. It is a non-linear process and can be described by chaotic time-series. The current study addresses this issue through the use of Adaptive Neuro-Fuzzy Inference System (ANFIS). ANFIS is about taking an initial fuzzy inference system (FIS) and tuning it with a back propagation algorithm based on the collection of input-output data. ANFIS was developed to predict the sand drift from a variety of causative variables. The structure and algorithm of ANFIS for predicting the rate of sand drift is described. The Adaptive Neuro-Fuzzy Inference System was validated by confi rming its consistency with a database of specifi ed physical process.
W artykule przedstawiono adaptację systemu ANFIS do oceny wielkości dryfu fal piaskowych poruszających się wzdłuż wybrzeża morskiego. Pomimo wielu informacji o charakterze ilościowym oraz jakościowym zebranych w badaniach terenowych oraz opracowanych wzorów empirycznych opisujących analizowane zjawisko, autorzy widzą potrzebę stosowania symulacji zjawiska za pomocą metod numerycznych. Takie możliwości daje omówiony w pracy system ANFIS.
Dostawca treści:: Biblioteka Nauki

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