ExpSSOA-Deep maxout: Exponential Shuffled shepherd optimization based Deep maxout network for intrusion detection using big data in cloud computing framework

The evolution of the Internet produced a large quantity of information. This makes the internet world more complex and affected by powerful attacks. In modern networks, the Intrusion Detection System (IDS) acts as a significant function for network security. The IDS can be either anomaly or signature-based behavior detection. Recently, several detection approaches have been proposed by researchers to find network intrusions. In this paper, a deep learning approach to intrusion detection using...

Refining Mean-field Approximations by Dynamic State Truncation

Mean-field models are an established method to analyze large stochastic systems with N interacting objects by means of simple deterministic equations that are asymptotically correct when N tends to infinity. For finite N, mean-field equations provide an approximation whose accuracy is model- and parameter-dependent. Recent research has focused on refining the approximation by computing suitable quantities associated with expansions of order $1/N$ and $1/N^2$ to the mean-field equation. In thi...

PID Control of Biochemical Reaction Networks

Exact maximal reduction of stochastic reaction networks by species lumping

Motivation: Stochastic reaction networks are a widespread model to describe biological systems where the presence of noise is relevant, such as in cell regulatory processes. Unfortunately, in all but simplest models the resulting discrete state-space representation hinders analytical tractability and makes numerical simulations expensive. Reduction methods can lower complexity by computing model projections that preserve dynamics of interest to the user. Results: We present an exact lumping m...