Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  present a new tool SReach, which solves probabilistic bounded reachability problems for two classes of mod- els of stochastic hybrid systems. The first one is (nonlinear) hybrid automata with parametric uncertainty. The second one is probabilistic hybrid automata with additional randomness for both transition prob- abilities and variable resets. Standard approaches to reachability prob- lems for linear hybrid systems require numerical solutions for large opti- mization problems, and become infeasible for systems involving both nonlinear dynamics over the reals and stochasticity. SReach encodes stochastic information by using a set of introduced random variables, and combines δ-complete decision procedures and statistical tests to solve δ-reachability problems in a sound manner. Compared to stan- dard simulation-based methods, it supports non-deterministic branching, increases the coverage of simulation, and avoids the zero-crossing prob- lem.  demonstrate SReach's applicability by discussing three represen- tative biological models and additional benchmarks for nonlinear hybrid systems with multiple probabilistic system parameters.
['Qinsi Wang', 'Paolo Zuliani', 'Soonho Kong', 'Sicun Gao', 'Edmund M. Clarke']
I am writing a research paper on a idea SReach: A Probabilistic Bounded Delta-Reachability Analyzer for Stochastic Hybrid Systems
[{"from": "human", "value": "I am writing a research paper on a idea SReach: A Probabilistic Bounded Delta-Reachability Analyzer for Stochastic Hybrid Systems"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  present a new tool SReach, which solves probabilistic bounded reachability problems for two classes of mod- els of stochastic hybrid systems. The first one is (nonlinear) hybrid automata with parametric uncertainty. The second one is probabilistic hybrid automata with additional randomness for both transition prob- abilities and variable resets. Standard approaches to reachability prob- lems for linear hybrid systems require numerical solutions for large opti- mization problems, and become infeasible for systems involving both nonlinear dynamics over the reals and stochasticity. SReach encodes stochastic information by using a set of introduced random variables, and combines \u03b4-complete decision procedures and statistical tests to solve \u03b4-reachability problems in a sound manner. Compared to stan- dard simulation-based methods, it supports non-deterministic branching, increases the coverage of simulation, and avoids the zero-crossing prob- lem.  demonstrate SReach's applicability by discussing three represen- tative biological models and additional benchmarks for nonlinear hybrid systems with multiple probabilistic system parameters."}]