Technical field of invention:
The present invention relates to intelligent deep learning methods for identifying critical factors in responding to a widespread crisis.

Background:
When an organisation experiences a sudden and significant negative event, crisis management is implemented to help deal with the situation. A crisis is the sudden occurrence of an undesirable and legally binding consequence of an unforeseen but previously anticipated risk.
Organizational stability is directly dependent on effective crisis management. An organization's health and resilience in the face of adversity and the unknown call for attention to be focused on more than just its bottom line.

Prior Art:
US10043035B2 Data privacy/anonymity and data value can be increased with the help of specific systems, computer-readable media, and methods that allow for the use of real-world, synthetic, or other data pertaining to a data subject while limiting the risk of re-identification by unauthorised parties and allowing data, including quasiidentifiers, pertaining to the data subject to be disclosed to any authorised party by granting access only to the data relevant to that authorised party's purpose, time period, purpose, place, and data Data protection, dynamic deidentification, anonymity, pseudonymity, granularization, and obscurity policies are all examples of privacy enhancement techniques (PET) that may be incorporated into a policy. These methods, systems, and media can be used with either classical or quantum computers.
US20080033737A1 describes a process for the automated online preparation of a company crisis manual based on data entered by a company representative through a website. The procedure requires the input of data that specifies the nature of the company. The procedure also includes answering bimodal questions to identify any relevant risk factors to the business organisation, entering information to provide details of the business's organisational structure, and preparing and making available the crisis manual, with the manual being automatically prepared by software resident on the Website.
10945115: Systems and methods for handling emergencies are described in detail herein. Methods of crisis management may involve, among other things: registering a group of users for access to a crisis management system; receiving, by crisis management system, an indication of a crisis event at a physical location from at least one user of the group of users, the crisis event caused by an aggressor; determining, by crisis management system, a location of the aggressor; creating, by crisis management system, a secure communication channel between the group of users; denying access to the crisis management system to any user who

Objectives of the invention:
Smart deep learning techniques for identifying critical factors in responding to mass-scale crises is the primary focus of the present invention. The primary purpose of the proposed invention is to develop and implement a strategy for dealing with organisational crises. Effective prediction is achieved through the use of sophisticated deep learning algorithms.

Detailed description of invention:
In the following, we will discuss the most advantageous and most preferred embodiment of the present invention. This description of the invention makes clear that the invention is not limited to the specific embodiments shown, but rather encompasses numerous modifications and embodiments in addition to those shown. In light of this, the present description should be taken as illustrative rather than restrictive. There is no intention to restrict the invention to the disclosed form, but rather, the invention is intended to cover all modifications, alternative constructions, and equivalents falling within the spirit and scope of the invention as defined in the claims.
The present invention relates to intelligent deep learning methods for identifying critical factors in responding to a widespread crisis.
Reference will be made to the appended drawings, which illustrate various embodiments of the invention, in order to provide a more detailed description of the invention and to make clearer the various aspects of some example embodiments thereof. It is understood that the figures herein represent only illustrative embodiments of the invention and are not intended to limit the scope of the invention in any way. The accompanying drawings will be used to provide a more thorough description and explanation of the invention.
Figure illustrates a block diagram representation of smart deep learning techniques for determination of prime factors for handling mass crisis management according to the present invention. This description of the invention is made with reference to the appended drawings, which, however, are not intended to limit the scope of the invention.
Effective crisis management is essential for any organisation. Prior to the occurrence of a crisis, a thorough process known as "crisis management" is put into action. At all points in time leading up to, during, and after a crisis, crisis management procedures are put into action. It's crucial to distinguish between crisis management and risk management.
In the face of a sudden and unexpected event that poses a risk to the organisation or its stakeholders, leaders must implement a plan for dealing with the crisis. Crisis management entails taking action in response to calamitous situations both as they unfold and afterwards. The proposed innovation utilises advanced deep learning methods for improved and precise prediction in the field of crisis management.
At this point, we'll dive deep into the disclosed example implementation. It should be noted, before describing the specific embodiments that are in accordance with this disclosure, that the embodiment resides primarily in the combinations arrangement of the system according to an embodiment herein.
Intelligent deep learning methods for identifying critical factors in responding to large-scale crises are depicted in the figure as a block diagram. A crisis management team is built into the system design. Risk analysis, response procedures, activation protocol, communication strategy, emergency contacts, and post-crisis management are all focal points of smart deep learning crisis management. Organizational crises can be effectively managed with these features in place.
Those with artistic talent will quickly think of other improvements and adaptations. As a result, the scope of the invention should be interpreted broadly, and not narrowly, according to the specific details and embodiments shown and described herein. Accordingly, the invention concept as defined by the appended claims and their equivalents is sufficiently flexible that various modifications may be made without departing from the spirit or scope of the invention.
Smart deep learning techniques for identifying critical factors in responding to mass crises are the next logical step following this invention.
The general purpose of the present invention, which will be described in greater detail below, is to provide a new and improved crisis management system based on smart deep learning unit that has all the advantages of the prior art and none of the disadvantages. This is in view of the aforementioned drawbacks inherent in the known types of crisis management systems now present in the prior art.
The proposed invention also includes a smart deep learning algorithm for monitoring the many facets of crisis management. Risk analysis, communication response procedures, activation procedures, post-crisis assessment, etc. are all parts of crisis management. Smart deep learning algorithms analyse these variables to foretell the effect of crisis management.
The invention is not limited in its application to the details of construction and to the arrangements of the components set forth in the following description or illustrated in the various ways, as will become apparent from the following discussion of at least one embodiment of the invention. The terminology and expressions used herein are for the purpose of description only and are not intended to be limiting.
These and other goals of the invention, as well as the many novel aspects that define it, are described in detail in the disclosure. Reference should be had to the accompanying drawings and descriptive matter, in which are illustrated preferred embodiments of the invention, to better understand the invention, its operating advantages, and the specific objects achieved by its uses.

We Claim:

1. The present invention relates to intelligent deep learning methods for identifying critical factors in responding to a widespread crisis.
2. Claimed in claim 1 are smart deep learning techniques for identifying critical factors in responding to widespread crises.
3. Risk assessment, activation protocol, communication plan, emergency contacts, and crisis resolution are just some of the areas that smart, deep learning-based crisis management focuses on.
4. To effectively manage a crisis, a business needs the intelligent deep learning techniques claimed in claim 1 to determine prime factors for handling mass crisis management.