Search Results - simulation optimization techniques

Groundwater Hydrological Model Simulation

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Advances in Spark-Ignition Engines

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Recent Advances in Mathematical Aspect in Engineering

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Advances in UAV Detection, Classification and Tracking

Subjects: “…optimization techniques…”
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Feature Papers in Materials Simulation and Design

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Computational Modeling and Simulation of Solids and Structures: Recent Advances and Practical Applications

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Beyond Energy Efficiency in Architecture. New Challenges and Research Trajectories for Buildings and the Built Environment

“…The authors also discuss the use of advanced modeling techniques to simulate the performance of different building systems, including vertical greenery systems and the solar cadaster.…”
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Recovery and Treatment of Solid Waste

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Numerical and Evolutionary Optimization 2021

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Control, Optimization, and Mathematical Modeling of Complex Systems

“…Undertaking a comprehensive study of such systems is a challenging problem, one which is impossible to solve without the use of contemporary mathematical modeling techniques. Mathematical models form the basis for the optimal design and control of complex systems. …”
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Testing of Materials and Elements in Civil Engineering (2nd Edition)

Subjects: “…DIC technique…”
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Testing of Materials and Elements in Civil Engineering (2nd Edition)

Subjects: “…DIC technique…”
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Advanced X-by-Wire Technologies in Design, Control and Measurement for Vehicular Electrified Chassis

Subjects: “…energy consumption optimization…”
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Recent Advances in Underwater Signal Processing

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Physical Metallurgy of Metals and Alloys

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Computational Methods and Applications for Numerical Analysis

Subjects: “…topology optimization…”
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Modeling and Simulation in Engineering, 2nd Edition

Subjects: “…optimization techniques…”
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Identification, Knowledge Engineering and Digital Modeling for Adaptive and Intelligent Control

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Advanced Thermoplastic Polymers and Composites

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Advances in Machine Learning and Mathematical Modeling for Optimization Problems

“…Recently, deep learning and deep reinforcement learning have begun to develop end-to-end training to solve more complex operation research and combinatorial optimization problems, such as covering problems, vehicle routing problems, traveling salesman problems, scheduling problems, and other complex problems requiring general simulations. …”
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