Titlebook: Engineering Applications of Neural Networks; 14th International C Lazaros Iliadis,Harris Papadopoulos,Chrisina Jayne Conference proceedings

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Joan Marques,Satinder Dhiman,Jerry Biberman super-Turing machines that implement them. Using these results, in this paper, at mathematical level of rigor, the phenomena of life and thinking are defined and perspectives of their artificial reproduction are considered. It is demonstrated that machines built of inorganic raw materials can never

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https://doi.org/10.1007/978-3-319-22732-0udied section into blocks arranged in layers, with determination of electrical conductivity in the center of each block. This inverse problem can be solved separately for each block, or simultaneously for a group of blocks. In this study, the dependence of solution error on the number of blocks for

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Don Passey,Angela Siew-Hoong Lee exchange rates. The end product of our work is an efficient Artificial Neural Network (ANN) based prediction model that forecasts the foreign currency exchange rates, making use of the trends in historical data. These trends in the historical currency data serve as significant prognostic factor to

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https://doi.org/10.1007/978-3-030-47821-6and other emergency response activities before, during, and after events. Probability analyses require multiple simulations which, generally, cannot be performed with the physics-based models under the time constraints during emergency conditions. To obtain highly accurate results with a fast turnar

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https://doi.org/10.1057/9780230507906d shape provides essential information to localization and navigation. It can also be used to identify reference points in the scenario. Crossroads are usual road shapes in urban environments. The detection of these structures is the main focus of this paper. Whereas cameras are sensible to illumina

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Dilemmas of Teaching Mathematical Reasoningng a mobile GSM network terminal inside a building..The localization data includes the information about the average GSM and WiFi signals in each of the given (x,y,floor) coordinates from more than two thousand points inside a five story building..We show that the PSO algorithm could be with success

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Laura Birklein,Anna Susanne Steinwegated spatiotemporal data could potentially lead to the development of reliable models, towards forecasting of the annual burned area. This paper takes advantage of the regression capabilities of modern Soft Computing approaches. More specifically numerous Artificial Neural Networks’ and e-Regression

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