Sentence examples for simulation-based testing from inspiring English sources

We achieve this via adaptive, simulation-based testing of the autonomous system where each sample represents a simulated scenario.

With the goal to develop a tool-chain for certifiable software for medical devices, I will walk through (a) formal modeling of the heart and pacemaker in timed automata, (b) verification of the closed-loop system, (c) automatic model translation from UPPAAL to Stateflow for simulation-based testing, and (d) automatic code generation for platform-level testing of the heart and real pacemakers.

The developers are also taking advantage of Google's powerful cloud-based data and computing environment to do extensive simulation-based testing.

Arnoud described Waymo's simulation-based testing capability as the equivalent of 25,000 virtual cars driving 2.5 billion real and modified miles in 2017.

The verified model must then be translated to a more detailed model for simulation-based testing and finally translated into executable code in a physical implementation.

Back in April, Rigetti was able to turn early results from its simulation-based testing into $2.5 million in seed funding from AME Cloud Ventures, Morado Ventures, Susa Ventures, and Tim Draper, among others.

The approach is based on a model-based paradigm for integrating dynamic simulators and has been used to construct a simulation-based testbed to evaluate plant-specific control algorithms together with networks and network attack models.

The results are of practical and theoretical relevance for designing simulation-based learning environments and simulation-based tests for measuring intelligence and problem-solving ability.

This paper introduces an architectural design of control software and a simulation-based test-bed for testing various control rules of the control software.

The simulation-based test shows that compared with the no controlled situation, IRLRC can reduce the total travel time up to 24%, which outperforms the direct reinforcement learning (DRL) method with a reduction of 18% after the same number of iterations.

Factors contributing to the high false positive rate include use of short amplicons (∼300 bp), use of a permissive P-value (0.1) for rejection of the null or neutral hypothesis [31], no correction for multiple tests, and an inadequate model of the domestication process in the coalescence simulation-based tests.