Mathematical search technique for detecting moving novel coronavirus disease (COVID-19) based on minimizing the weight function

Abstract

The study of search plans has found considerable interest between searchers due to its interesting applications in our real life like searching for located and moving targets. This paper develops a method for detecting moving targets. We propose a novel strategy based on weight function W(Z), W(Z)=λH(Z)+(1-λ)L(Z), where H(Z), L(Z) are the total probabilities of un-detecting, and total effort respectively, is searching for moving novel coronavirus disease (COVID-19) cells among finite set of different states. The total search effort will be presented in a more flexible way, so it will be presented as a random variable with a given distribution. The objective is searching for COVID-19 which hidden in one of n cells in each fixed number of time intervals m and the detection functions are supposed to be known to the searcher or robot. We look in depth for the optimal distribution of the total effort which minimizes the probability of undetected the target over the set of possible different states. The effectiveness of this model is illustrated by presenting a numerical example.

Keywords

• COVID-19
• Coronavirus
• Optimal search
• Weight function
• Probability of undetected
• Moving target