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Model-Based Dynamic Optimization with OpenModelica and CasADi

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IFAC Proceedings Volumes 2013年第21期46卷 446-451页

作者： Alachew Shitahun Vitalij Ruge Mahder Gebremedhin Bernhard Bachmann Lars Eriksson Joel Andersson Moritz Diehl Peter Fritzson PELAB-Programming Environment Lab Dept. Computer Science Linköping University SE-581 83 Linköping Sweden Dept. Mathematics and Engineering University of Applied Sciences D-33609 Bielefeld Germany Vehicular Systems Dept. Electrical Engineering Linköping University SE-581 83 Linköping Sweden Dept. of Electrical Engineering and Optimization in Engineering Center (OPTEC) K.U. Leuven Belgium

This paper demonstrates model-based dynamic optimization through the coupling of two open source tools: OpenModelica, which is a Modelica-based modeling and simulation platform, and CasADi, a framework for numerical optimization. The coupling uses a standardized XML format for exchange of differential-algebraic equations (DAE) models. OpenModelica supports export of models written in Modelica and the optimization language extension using this XML format, while CasADi supports import of models represented in this format. This allows users to define optimal control problems (OCP) using Modelica and optimization language specification, and solve the underlying model formulation using a range of optimization methods, including direct collocation and direct multiple shooting. The proposed solution has been tested on several industrially relevant optimal control problems, including a diesel-electric power train.

关键词： Modelica OpenModelica model-based optimization dynamic optimization CasADi

Thermodynamics of optical bloch equations

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arXiv 2020年

作者： Elouard, Cyril Herrera-Martí, David Esposito, Massimiliano Auffèves, Alexia Department of Physics and Astronomy University of Rochester RochesterNY14627 United States Atos Centre for Excellence in Performance Programming 1 rue de Provence Echirolles38130 France Complex Systems and Statistical Mechanics Department of Physics and Materials Science University of Luxembourg LuxembourgL-1511 Luxembourg CNRS Université Grenoble Alpes Institut Néel GrenobleF-38042 France

Optical Bloch Equations (OBE) describe the coherent exchange of energy between a quantum bit (qubit) and a quasi-resonant driving field in the presence of a thermal bath. Despite it being an ubiquitous process in quantum technologies, a sound thermodynamic analysis is still missing. We hereby provide such an analysis, by deriving the relevant framework from first principles. We start from a complete microscopic description of the qubit-bath system where definitions of heat, work and entropy production are unambiguous. We trace out the bath and coarse-grain the resulting expressions in time, using a methodology similar to the derivation of the dynamical master equation, to derive closed expressions for the First and Second Law in terms of system properties. Long coarse graining times yield the Floquet Master Equation and its already known thermodynamic description. Short coarse-graining times yield instead to the OBE and a novel thermodynamic framework which explicitly depend on quantum coherences in the qubit’s energy basis which produce quantum signatures in the heat and entropy production flows. This allow us to characterize a genuinely quantum non-equilibrium situation, where the coherences created by the driving field are continuously erased by the bath. Our findings can be readily extended to larger open quantum systems. They carry the seeds for future thermodynamic analyses of quantum gates and the design of quantum engines in the strong coherent driving regime. Copyright © 2020, The Authors. All rights reserved.

关键词： Entropy

Property-Directed verification of recurrent neural networks

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arXiv 2020年

作者： Khmelnitsky, Igor Neider, Daniel Roy, Rajarshi Barbot, Benoît Bollig, Benedikt Finkel, Alain Haddad, Serge Leucker, Martin Ye, Lina LSV CNRS ENS Paris-Saclay Université Paris-Saclay France Inria France Max Planck Institute for Software Systems Kaiserslautern Germany Université Paris-Est Créteil France Institute for Software Engineering and Programming Languages Universität zu Lübeck Germany CentraleSupélec Université Paris-Saclay France Institut Universitaire de France France

This paper presents a property-directed approach to verifying recurrent neural networks (RNNs). To this end, we learn a deterministic finite automaton as a surrogate model from a given RNN using active automata learning. This model may then be analyzed using model checking as verification technique. The term property-directed reflects the idea that our procedure is guided and controlled by the given property rather than performing the two steps separately. We show that this not only allows us to discover small counterexamples fast, but also to generalize them by pumping towards faulty flows hinting at the underlying error in the *** Codes 68Q60, 68T07 Copyright © 2020, The Authors. All rights reserved.

关键词： Recurrent neural networks

Energy Efficiency Improvement System for AC Circuits

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Energy Efficiency Improvement System for AC Circuits

IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW)

作者： Vladimir Kulagin Kirill Selivanov Andrey Vlasov Dmitrii Aminev Lyudmila Bunina Sergey Bikovsky Moscow technical university of communications and informatics Moscow Russian Federation Department of Design and Technology of Electronic Devices Bauman Moscow State Technical University BMSTU Moscow Russian Federation Department of Development of software solutions and system programming Russian Technological University – MIREA Moscow Russian Federation Department of Electrical Engineering Systems Russian Technological University – MIREA Moscow Russian Federation

The problem of the rational use of energy resources remains constantly relevant and requires the search for new approaches. One of them is power control. In AC circuits, the authors see the most promising method of phase AC power control. Based on it, a power control module was developed. The structural and circuit diagrams of the developed device are presented to implement the proposed solution. The authors produced its experimental prototype and conducted experimental testing at various levels of regulated power. Savings when using the proposed power control module were calculated using the example of energy consumption in various sectors of energy-intensive systems. According to the data obtained, the module allows saving energy consumption without significant discomfort to the energy user. The calculated results allow concluding that the proposed AC power control module is fully operational, and its widespread use will significantly reduce the need for electricity.

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Lecture Notes in Computer Science (including subseries Lectu...

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Preface

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2000年 1782卷 VII页

作者： Smolka, Gert University of Saarland Programming Systems Lab Building 45 P. O. Box 15 11 50 Saarbrücken Germany

Sensing metric-based hybrid underlay/overlay transmission framework for CR-IoT networks for smart city applications

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Sensing metric-based hybrid underlay/overlay transmission fr...

7th IET Smart Cities Symposium (SCS 2023)

作者： Indu Bala Maad M. Mijwil Mostafa Abotaleb El-Sayed M. El-kenawy Abdelhameed Ibrahim School of Electrical and Electronics Engineering Lovely Professional University Punjab India Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

With the increasing number of IoT devices, there is a growing need for bandwidth to support their communication. Unfortunately, there is a shortage of available bandwidth due to preallocated bands for various services. To address this issue, Cognitive Internet of Things (CR-IoT) enables devices to optimize their efficiency and enhance their communication capabilities by intelligently accessing available bandwidth. This is achieved through the use of soft sensing metrics, where devices continuously monitor the RF environment and transmit data opportunistically in overlay mode if a free channel is detected, or in underlay mode if not. In this paper, a soft sensing metric based hybrid transmission framework is proposed for CR-IoT devices to meet the data rate requirement for the smart city applications. The efficacy of this approach is demonstrated through simulation results.

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Classification of Buildings' Potential for Seismic Damage by Means of Artificial Intelligence Techniques

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arXiv 2022年

作者： Kostinakis, Konstantinos Morfidis, Konstantinos Demertzis, Konstantinos Iliadis, Lazaros Department of Civil Engineering Aristotle University Thessaloniki Aristotle University Campus Thessaloniki54124 Greece Terma Dasylliou Thessaloniki55535 Greece Laboratory of Complex Systems Department of Physics Faculty of Sciences International Hellenic University Kavala Campus St. Loukas 65404 Greece School of Engineering Department of Civil Engineering Faculty of Mathematics Programming and General Courses Democritus University of Thrace Xanthi Kimmeria Greece

Developing a rapid, but also reliable and efficient, method for classifying the seismic damage potential of buildings constructed in countries with regions of high seismicity is always at the forefront of modern scientific research. Such a technique would be essential for estimating the pre-seismic vulnerability of the buildings, so that the authorities will be able to develop earthquake safety plans for seismic rehabilitation of the highly earthquake-susceptible structures. In the last decades, several researchers have proposed such procedures, some of which were adopted by seismic code guidelines. These procedures usually utilize methods based either on simple calculations or on the application of statistics theory. Recently, the increase of the computers' power has led to the development of modern statistical methods based on the adoption of Machine Learning algorithms. These methods have been shown to be useful for predicting seismic performance and classifying structural damage level by means of extracting patterns from data collected via various sources. The present paper attempts to compare and evaluate the capability of various Machine Learning methods to adequately classify the seismic damage potential of R/C buildings. A large training dataset is used for the implementation of the classification algorithms. To this end, 90 3D R/C buildings with three different masonry infills' distributions are analysed utilizing Nonlinear Time History Analysis method for 65 real seismic records. The level of the seismic damage is expressed in terms of the Maximum Interstory Drift Ratio. A large number of Machine Learning algorithms is utilized in order to estimate the buildings' damage response. The most significant conclusion which is extracted is that the Machine Learning methods that are mathematically well-established and their operations that are clearly interpretable step by step can be used to solve some of the most sophisticated real-world problems in consideratio

关键词： Classification (of information)

Sentiment Analysis Technology of English Newspapers Quotes Based on Neural Network as Public Opinion Influences Identification Tool

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Sentiment Analysis Technology of English Newspapers Quotes B...

International Computer Sciences and Information Technologies (CSIT)

作者： Serhii Voloshyn Victoria Vysotska Oksana Markiv Ivan Dyyak Ihor Budz Vadim Schuchmann Information Systems and Networks Department Lviv Polytechnic National University Lviv Ukraine Lviv Polytechnic National University Lviv Ukraine Osnabrück University Osnabrück Germany Applied Mathematics Department Ivan Franko National University of Lviv Lviv Ukraine Computational Mathematics and Programming Department Lviv Polytechnic National University Lviv Ukraine Software Engineering Department West Ukrainian National University Ternopil Ukraine

ISBN: (纸本)9798350334326

This article dwells upon research concerning human language processing techniques, namely emotion analysis, conducted to identify emotions of author quotations in English newspaper articles. The publication describes general information about human language processing, brief description of analogues based on machine learning and neural network to analyse emotions in text. The main goal is to develop intelligent system for sentiment analysis of English language quotations and keywords identification that influences public opinion. The article describes sequence of program actions and tools that have been used. Then, statistics of tasks performed by neural networks with various functions of activators have been described. In the publication, product demo version has been described, and primary usage scenario has been depicted. In the end, research results have been summarised.

关键词： Training Sentiment analysis Vocabulary Dictionaries Mood Neural networks Text categorization

A compact QUBO encoding of computational logic formulae demonstrated on cryptography constructions

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arXiv 2024年

作者： Morse, Gregory Kozsik, Tamás Mencer, Oskar Rakyta, Péter Department of Programming Languages and Compilers Eötvös Loránd University Budapest1117 Hungary Groq Inc. 400 Castro St Mountain ViewCA94041 United States Department of Physics of Complex Systems Eötvös Loránd University Budapest1117 Hungary Wigner Research Center for Physics P.O. Box 49 Budapest1525 Hungary

We aim to advance the state-of-the-art in Quadratic Unconstrained Binary Optimization formulation with a focus on cryptography algorithms. As the minimal QUBO encoding of the linear constraints of optimization problems emerges as the solution of integer linear programming (ILP) problems, by solving special boolean logic formulas (like ANF and DNF) for their integer coefficients it is straightforward to handle any normal form, or any substitution for multi-input AND, OR or XOR operations in a QUBO form. To showcase the efficiency of the proposed approach we considered the most widespread cryptography algorithms including AES-128/192/256, MD5, SHA1 and SHA256. For each of these, we achieved QUBO instances reduced by thousands of logical variables compared to previously published results, while keeping the QUBO matrix sparse and the magnitude of the coefficients low. In the particular case of AES-256 cryptography function we obtained more than 8× reduction in variable count compared to previous results. The demonstrated reduction in QUBO sizes notably increases the vulnerability of cryptography algorithms against future quantum annealers, capable of embedding around 30 thousands of logical variables. © 2024, CC BY.

关键词： Integer linear programming