Panagiotis T. Artikis

Recovery Time of a Complex System in Risk and Crisis Management Operations

It is generally recognised that a random sum of discrete random variables and a maximum of a random number of non-negative random variables are very powerful analytical concepts for formulating effective stochastic models with significant applications in many practical disciplines. The paper combines these concepts in order to formulate a stochastic model. Properties and applications in risk and crisis management operations of the formulated stochastic model are also established.

Discrete random sums in processes of systemics arising in cybernetics and informatics

Abstract Discrete random sums are generally recognized as powerful analytical tools with particularly important applications in many practical fields. The present paper formulates a very wide class of discrete random sums. Applications of the formulated class in systemics, cybernetics and informatics are also established. Moreover, the paper makes quite clear the role of such applications in the description, investigation and control of the performance and evolution of a modern very complex educational organization.

Stochastic discounting for cost effective replacements of systems under competing catastrophic risks

The minimum of a random number of nonnegative random variables constitutes a fundamental concept of extreme value theory with significant practical applications. The present paper is mainly devoted to the formulation, investigation, and interpretation in competing risks management of a stochastic discounting model based on this fundamental concept.

Stochastic models for risk control programs of organizations

Purpose – Risk control programs of modern complex organizations make extensive use of stochastic models. The purpose of this paper is to consider a class of stochastic models in severity and risk duration reduction operations.Design/methodology/approach – A new stochastic model is formulated which is shown to be of some importance in fundamental risk management operations. The investigation of such a model is based on classical methods of characteristic functions theory.Findings – A stochastic model having the form of the product of two non‐negative and independent random variables is formulated. A characterization of the distribution of such a model is established. Moreover, applications of the proposed stochastic model in risk control programs of organizations are provided.Research limitations/implications – The difficulty of evaluating the corresponding distribution function, which extends the practical applicability of the proposed stochastic model still remains.Originality/value – The formulated stoc...

Stochastic Compounding Models for Continuous Uniform Cash Flows Arising in Risk Management

Abstract This paper investigates the conditions under which zero unimodality is introduced into stochastic future value distributions for continuous uniform cash flows, and discusses the associated moments. The distribution of a future value generated from such cash flows is shown to be far more complicated than hitherto thought. In many situations, the statistical evidence suggesting there is potential to generate realistic future value is contradictory. These points are illustrated using a number of important areas of practical application in risk management.

Applications of a Stochastic Model in Supporting Intelligent Multimedia Systems and Educational Processes

It is generally recognized that stochastic models constitute extremely strong analytical tools for a very wide variety of fundamental research areas of modern informatics. The theoretical contribution of the present chapter consists of the formulation and investigation of a stochastic model being an extension of the concept of minimum of a random number of nonnegative random variables. Moreover, the practical contribution of the present chapter consists of the establishment of applications of the formulated stochastic model in the development, assessment, and implementation of operations for supporting intelligent multimedia systems and educational processes.

Consideration of a stochastic multiplicative model in developing fundamental proactive risk management operations

Abstract From a practical and theoretical point of view it is universally recognized that risk severity, risk frequency and risk duration are the most important stochastic components of the complex concept of risk. The formulation of effective stochastic models incorporating these components can substantially contribute to the investigation and implementation of the various operations of the risk management process. The present paper mainly concentrates on the formulation, establishment of theoretical properties and practical applications in risk classification, risk control, risk retention and other fundamental risk management operations of a stochastic multiplicative model which is based on the three most important stochastic components of the concept of risk.

Consideration of Learning Processes Based on Optimal Operations for Recovery of Information Systems

The present paper makes use of the maximum of a random number of nonnegative random variables and a nonnegative random variable for formulating a stochastic multiplicative model. Sufficient conditions for evaluating the distribution function of the model are also established by the paper. Moreover, the paper provides applications of the formulated stochastic model in developing optimal operations for the recovery cost of a damaged information system. It is also shown that the mathematical structure and the practical applicability of the formulated stochastic model constitute structural elements of learning processes related to the evolution of information systems.

Determining a Discrete Geometric Random Sum in Computational Intelligence for Supporting a Complex Human-Computer Interaction System under a Major Risk

A type of geometric random sum of discrete, independent and identically distributed random variables taking values in the set of nonnegative integers is a useful analytical tool of computational intelligence for describing and analyzing the evolution of a complex human-computer interaction system under a major risk. The present paper concentrates on the determination of a particular case of such a geometric random sum and the application of the determined discrete geometric random sum in realizing the most probable and best scenario for the evolution of a complex human-computer interaction system under a major risk.

Performance of Complex Systems in the Environment of a Random Number of Competing Catastrophic Risks

The present paper makes use of the minimum of a random number of nonnegative random variables and a nonnegative random variable for formulating a stochastic multiplicative model. Sufficient conditions for evaluating the distribution function of the model are also established. Moreover, the paper provides applications of the formulated model in investigating the performance of a complex system in the environment of a random number of competing and catastrophic risks.