Nostradamus 2014: Prediction, Modeling and Analysis of by Ivan Zelinka, Ponnuthurai Nagaratnam Suganthan, Guanrong

By Ivan Zelinka, Ponnuthurai Nagaratnam Suganthan, Guanrong Chen, Vaclav Snasel, Ajith Abraham, Otto Rössler

The prediction of habit of complicated platforms, research and modeling of its constitution is a very important challenge in engineering, economic system and usually in technology this day. Examples of such platforms might be visible on this planet round us (including bodies) and naturally in nearly each medical self-discipline together with such “exotic” domain names because the earth’s surroundings, turbulent fluids, economics (exchange expense and inventory markets), inhabitants progress, physics (control of plasma), details movement in social networks and its dynamics, chemistry and intricate networks. to appreciate such complicated dynamics, which regularly show unusual habit, and to exploit it in examine or business functions, it truly is paramount to create its types. For this goal there exists a wealthy spectrum of equipment, from classical comparable to ARMA versions or field Jenkins solution to glossy ones like evolutionary computation, neural networks, fuzzy good judgment, geometry, deterministic chaos among others.

This lawsuits ebook is a set of accredited papers of the Nostradamus convention that has been held in Ostrava, Czech Republic in June 2014. This publication additionally comprises striking keynote lectures via unique visitor audio system: René Lozi (France), Ponnuthurai Nagaratnam Suganthan (Singapore) and Lars Nolle (Germany). the most objective of the convention used to be to create a periodical chance for college kids, teachers and researchers to switch their principles and novel study tools. This convention establishes a discussion board for presentation and dialogue of modern learn traits within the quarter of purposes of assorted predictive tools.

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Kurmis et al. Thus it can be used in real life applications where large number of data is needed to be stored locally, exchanged with other vehicles and vehicular hybrid cloud. Acknowledgments. This work was supported by the Latvia-Lithuania Cross Border Cooperation Programme within the project “JRTC Extension in Area of Development of Distributed Real-Time Signal Processing and Control Systems”, code LLIV-215. Also it was partially supported by the Development of human resources in research and development of latest soft computing methods and their application in practice project, reg.

1 for eq. (3). 5. 4 % and 6%). 0 1 2 3 4 5 6 7 8 Average prediction error E Fig. 2. The error growth rate dE dt versus E for ND1 (the left picture), ND3 (the central picture) and ND5 (the right picture). The thick line represents data from EPS, the thin lines from (3) and the dotdashed lines from (4). The light grey lines represent the data extrapolate from time length τ1, the grey lines represent the data extrapolate from time length τ2 and black lines represent the data in time length τ3. 7 Conclusion This paper studies errors of estimations of time limits and asymptotic value of initial errors growth in low-dimensional atmospheric model L05II introduced by Lorenz [13] with the parameters, that are as close to NWPM as possible.

Thus, it is simple to use one microprocessor to control many DS18B20s distributed over a large area. This part has already become the corner stone of many data logging and temperature control projects. 2 Waviness Measurements At present, the sea and the oceans waviness measurements uses variety of methods, depending on the geographic region, measuring accuracy, and common tasks [5]. The main and most commonly used are: • Ultrasound based sensors: ─ Pros: suitable for measuring waves with a height of over 5 meters ─ Cons: significant measurement errors • Rheostat-type structures: ─ Pros: allows you to get a fairly accurate data ─ Cons: because of its design features cannot be long-lasting 34 G.

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