Titlebook: Artificial Intelligence and Soft Computing; 18th International C Leszek Rutkowski,Rafał Scherer,Jacek M. Zurada Conference proceedings 2019

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Sensitivity Analysis of the Neural Networks Randomized Learningmeters that are learned are the output weights. Parameters of hidden neurons are generated randomly once and need not to be adjusted. The key issue in randomized learning algorithms is to generate parameters in a right way to ensure good approximation and generalization properties of the network. Re

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Smart Well Data Generation via Boundary-Seeking Deep Convolutional Generative Adversarial Networksion. Alas, this comes with a great increase in computational time, encumbering the optimization process. With the growing adoption rate for smart wells in oil field development projects, these optimizations are indispensable as to justify the investment on the technology and maximize financial retur

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Study of Learning Ability in Profit Sharing Using Convolutional Neural Networkents have been conducted using Atari 2600’s Asterix in the Profit Sharing using Convolutional Neural Networks, and it is known that a better score can be obtained than Deep Q-Network. However, experiments have not been conducted on games other than Asterix, and sufficient consideration has not been

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Sequential Data Mining of Network Traffic in URL Logsanalysis algorithms, there are new possibilities of using registered actions of many users in logs. In this paper, we present a way to detect anomalies in URL logs using sequential pattern mining algorithms. We analyse the registered URL request sequences of the public institution website in order t

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