THE CURRENT STATE OF THE VIRTUAL DOCUMENT CIRCULATION SYSTEM

Abstract

Virtual document circulation is truly a convenient and secure way to share and store files. The primary data function is to securely upload and download multiple files, which may include business letters, documents, or charts. The design and style of virtual document circulation should facilitate the secure transfer and storage of records. It offers a user-friendly interface. The use of virtual document circulation is intended for sharing and storing confidential documents. Board members, often spread across the globe, need to view important documents or review highly classified information. It helps to securely access and keep your files private. Using an online data space allows us to securely discuss business-critical files, while avoiding legal issues that could arise from document leaks.

Summary Recently, intrusion detection systems (IDS) have been implemented effectively secure networks. Using neural networks and machine learning in detection and classification inputs are powerful alternative solutions. Both Gradients in this research paper momentum -based backscattering (BP) and gradient descent momentum and adaptive gain (GDM/AG) are used neural networks work like IDS. Offer done of both efficiency check learning circuits, neuron to the network offer based IDS done learning from the algorithm used without built - rhythms . The efficiency of both algorithms is checked in terms of convergence speed . achieve system learning and elapsed learning time using different neural network settings parameters. The result showed that the BP learning algorithm based on GDM/AG GDM-based BP is superior to the learning algorithm.