Improving the method for increasing the efficiency of decision-making based on bio-inspired algorithms

Abstract

The problem that is solved in the research is to increase the efficiency of assessing the state of the monitoring object while ensuring the given reliability, regardless of the hierarchy of the monitoring object. The object of research is decision support systems. The subject of the research is the process of evaluating the monitoring object using bio-inspired algorithms. The hypothesis of the research is the need to increase the efficiency of the assessment of the state of the monitoring object with the given reliability. In the course of the research, an improved method of increasing the efficiency of decision-making based on bio-inspired algorithms was proposed. General provisions of artificial intelligence theory were used to solve the problem of analyzing the object state in intelligent decision support systems. The essence of improvement is to use the following procedures: − taking into account the type of uncertainty about the state of the monitoring object (full uncertainty, partial uncertainty and full awareness); − taking into account the degree of noise in the data on the state of the monitoring object. Noise refers to the degree of information distortion created by the enemy’s means of electronic and cyber warfare; − using the ant colony optimization algorithm and the genetic algorithm to find the path metric while assessing the state of the monitoring object; − deep learning of synthesized ants using evolving artificial neural networks. An example of using the proposed method in assessing the state of the operational situation of a group of troops (forces) is presented. The specified example showed a 15−22 % increase in the efficiency of data processing using additional improved procedures

Development of the solution search method using the population algorithm of global search optimization

“…Weed agents are placed taking into account the type of uncertainty about the analysis object state. At this stage, the type of uncertainty about the object to be analyzed is taken into account and the basic state model of the object to be analyzed is initialized [2,19,[21][22][23][24][25]. At the same time, the degree of uncertainty can be: full awareness; partial uncertainty and total uncertainty.…”

“…Analysis of the results given in Table 2 allows to conclude that the improved algorithm of invasive weeds increases the efficiency of data processing at the level of 21-27 %. [16] 0.37 0.27 0.18 The canonical cuckoo algorithm [16] 0.96 0.7 0.29 Canonical firefly algorithm [19] 0.62 0.5 0.19 Canonical algorithm of bats [16,22] 0.43 0.96 1 Canonical algorithm of artificial bee colonies 0.81 0.49 0.23 Canonical algorithm for finding a school of fish [22] 0.48 0.38 0.11 Canonical particle swarm algorithm [16,22] 0.21 0.12 0.06 Random search [20] 0.18 0.14 0.07 Canonical algorithm of a pack of gray wolves [16,22] 0 0 0 recommended ship routes marine areas temporarily closed for swimming…”

“…The work [22] indicated that the most popular evolutionary bio-inspired algorithms are the so-called «swarm» procedures (Particle Swarm Optimization -PSO). Among them, there are optimization algorithms based on cat swarms (Cat Swarm Optimization -CSO), which are very promising both from the point of view of speed and ease of implementation.…”

“…An analysis of works [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] showed that the common shortcomings of the above-mentioned researches are:…”

Proceedings of the V International Scientific and Practical Conference

“…Так, загрозу передчасних пологів діагностували у 15 % жінок І групи, у 25 % у жінок ІІ групи, у 30 % жінок ІІІ групи. Тривалість вагітності та пологова діяльність у жінок І групи в основному відбулися вчасно в термін 40 Успішна комунікація між лікарем і пацієнтом забезпечена, якщо з боку медичного персоналу є підтримка, повага, розуміння і співчуття. Без них неможливі хороші стосунки загалом між людьми, а тим більше в терапевтичному процесі.…”