for the development of anti-aircraft missile systems and complexes***** *****Central scientifically-reserch institute of arming and military equipment of the Armed Forces of Ukraine Povitrofloski ave.,
Nowadays, artificial intelligence has entered into all spheres of our life. The system of analysis of the electronic environment is not an exception. However, there are a number of problems in the analysis of the electronic environment, namely the signals. They are analyzed in a complex electronic environment against the background of intentional and natural interference. Also, the input signals do not match the standards due to the influence of different types of interference. Interpretation of signals depends on the experience of the operator, the completeness of additional information on a specific condition of uncertainty. The best solution in this situation is to integrate with the data of the information system analysis of the electronic environment and artificial neural networks. Their advantage is also the ability to work in real time and quick adaptation to specific situations. These circumstances cause uncertainty in the conditions of the task of signal recognition and fuzzy statements in their interpretation, when the additional involved information may be incomplete and the operator makes decisions based on their experience.
That is why, in this article, an improved method for finding solutions for neuro-fuzzy expert systems of analysis of the electronic environment is developed.
Improving the efficiency of information processing (reducing the error) of evaluation is achieved through the use of neuro-fuzzy artificial neural networks that are evolving and learning not only the synaptic weights of the artificial neural network, but also the type and parameters of the membership function. High efficiency of information processing is also achieved through training in the architecture of artificial neural networks by taking into account the type of uncertainty of the information that has to be assessed and work with clear and fuzzy products. This reduces the computational complexity of decision-making and absence of accumulation of an error of training of artificial neural networks as a result of processing of the arriving information on an input of artificial neural networks. The use of the proposed method was tested on the example of assessing the state of the electronic environment. This example showed an increase in the efficiency of assessment at the level of 20–25 % on the efficiency of the processing information
This paper reports an improved method for processing the image of a vehicle's license plate when shooting with a smartphone camera. The method for processing the image of a vehicle's license plate includes the following stages:
– enter the source data;
– split the video streaming into frames;
– preliminary process the image of a vehicle's license plate;
– find the area of a vehicle's license plate;
– refine character recognition using the signature of a vehicle's license plate;
– refine character recognition using the combined results from frames in the streaming video;
– obtain the result of processing.
Experimental studies were conducted on the processing of images of a vehicle's license plate. During the experimental studies, the license plate of a military vehicle (Ukraine) was considered. The original image was the color image of a vehicle. The results of experimental studies are given. A comparison of the quality of character recognition in a license plate has been carried out. It was established that the improved method that uses the combined results from streaming video frames works out efficiently at the end of the sequence. The improved method that employs the combined results from streaming video frames operates with numerical probability vectors.
The assessment of errors of the first and second kind in processing the image of a license plate was carried out. The total accuracy of finding the area of a license plate by known method is 61 % while the improved method's result is 76 %. It has been established that the minimization of errors of the first kind is more important than reducing errors of the second kind. If a license plate is incorrectly identified, these results would certainly be discarded at the character recognition stage.
У статті представлена система протидії негативному інформаційно-психологічному впливу на особовий склад Збройних Сил України та основні заходи, що реалізуються в її підсистемах. Взаємодію складових вказаних підсистем відображає механізм протидії негативному інформаційно-психологічному впливу на особовий склад Збройних Сил України. Запропонований механізм протидії негативному інформаційно-психологічному впливу передбачає виконання низки заходів, пов’язаних як із попередженням, так і з виявленням та усуненням наслідків впливу.
У статті представлений методичний підхід до визначення підрозділів для здійснення протидії негативному інформаційному (психологічному) впливу противника на основі оцінювання їх спроможностей за методикою DOTMLPFI. Проаналізовано причини недостатньої ефективності протидії негативному інформаційному (психологічному) впливу на особовий склад на початку Антитерористичної операції, визначені основні завдання з протидії негативному інформаційному (психологічному) впливу. Запропоновані схема процедур планування протидії негативним інформаційним (психологічним) впливам та варіант типової групи спроможностей “Протидія негативним інформаційним (психологічним) впливам”. Наведені результати оцінювання спроможності “Аналіз та прогнозування інформаційного (психологічного) впливу противника”, що розраховані авторами.