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Machine Learning and the Internet of Things Enable Steam Flood Optimization for Improved Oil Production

Autor: Yan, Mi, MacDonald, Jonathan C., Reaume, Chris T., Cobb, Wesley, Toth, Tamas, Karthigan, Sarah S.

Publikováno v: The 1st International Workshop on Artificial Intelligence of Things at KDD 2019

Recently developed machine learning techniques, in association with the Internet of Things (IoT) allow for the implementation of a method of increasing oil production from heavy-oil wells. Steam flood injection, a widely used enhanced oil recovery te

Externí odkaz: http://arxiv.org/abs/1908.11319

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Towards Evaluating Size Reduction Techniques for Software Model Checking

Autor: Sallai, Gyula, Hajdu, Ákos, Tóth, Tamás, Micskei, Zoltán

Publikováno v: EPTCS 253, 2017, pp. 75-91

Formal verification techniques are widely used for detecting design flaws in software systems. Formal verification can be done by transforming an already implemented source code to a formal model and attempting to prove certain properties of the mode

Externí odkaz: http://arxiv.org/abs/1708.07224

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Exploiting Hierarchy in the Abstraction-Based Verification of Statecharts Using SMT Solvers

Autor: Czipó, Bence, Hajdu, Ákos, Tóth, Tamás, Majzik, István

Publikováno v: EPTCS 245, 2017, pp. 31-45

Statecharts are frequently used as a modeling formalism in the design of state-based systems. Formal verification techniques are also often applied to prove certain properties about the behavior of the system. One of the most efficient techniques for

Externí odkaz: http://arxiv.org/abs/1703.07350

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