ROK Navy intends to secure the Korean-type aircraft carrier in order to effectively prepare for various future security threats. In general, the Korean national competency is considered to be at the level of having an aircraft carrier, but it is unclear what scale aircraft carrier would be appropriate. In this study, the efficiency was evaluated through the relative comparison between national competency(national power, economic power) and the scale of aircraft carriers, and the optimal scale of the Korean-type aircraft carrier that could be acquired was presented. A DEA(Data Envelopment Analysis) model was applied to aircraft carriers(19 aircraft carriers in 11 countries) currently in operation and scheduled to be possessed in the world. As input variables, CINC(Composite Index of National Capability) and GDP(Gross Domestic Product), which are the most widely used as indicators of national and economic power, and as output variables, the full-load displacement, length, and width of aircraft carriers were selected. ARIMA(short-term within 5 years) and simple regression(long-term over 5 years) were used to estimate the future national competency of each country at the time of aircraft carriers acquisition. The relative efficiency score of the Korean-type aircraft carrier currently being evaluated is 1.062, and it was evaluated as small-scale aircraft carrier compared to the national competency. Based on Korean national competency, the optimal scale of the Korean-type aircraft carrier calculated by aggregating benchmark groups, is 58,308.1 tons of full-load displacement, 279.4m in length, and 68.3m in width.
Artificial intelligence is driving the Fourth Industrial Revolution and is in the spotlight as a general-purpose technology. As the data collection from the battlefield increases rapidly, the need to us artificial intelligence is increasing in the military, but it is still in its early stages. In order to identify maritime targets, Republic of Korea navy acquires images by ISAR(Inverse Synthetic Aperture Radar) of maritime patrol aircraft, and humans make out them. The radar image is displayed by synthesizing signals reflected from the target after radiating radar waves. In addition, day/night and all-weather observations are possible. In this study, an artificial intelligence is used to identify maritime targets based on radar images. Data of radar images of 24 maritime targets in Republic of Korea and North Korea acquired by ISAR were pre-processed, and an artificial intelligence algorithm( ResNet-50) was applied. The accuracy of maritime targets identification showed about 99%. Out of the 81 warship types, 75 types took less than 5 seconds, and 6 types took 15 to 163 seconds.
Strong naval power is needed to protect the sea, the lifeline of the national economy and people's lives. The navy has been operating with the increase of forces and the selection of officers to achieve its mission, and long-term service officers are selected every year. In this study, problems were identified through the analysis of relative influence of the long-term service selection system for naval officers by evaluation factors. As a result of relative influence on the selection data for long-term service of 203 officers over the past 3 years(2018∼2020) showed education results(25.05%) > english ability(23.33%) > work evaluation(11.23%) > prize(10.91%). In order to equal the relative influence and the rate of allocation by evaluation factors, higher the score of work evaluation, command recommendation, and physical strength, lower the score of education results, english ability, and prize were required. Sensitivity analysis was conducted after suggesting the alternatives that adjusted the scoring by ±2∼5, ±2∼10 points. As a result of calculating the relative influence on the alternatives, rankings of the score and the relative influence gradually became similar.
Modern combat has been extended to the concept of real-time response to a variety of threats simultaneously occurring in vast areas. In order to quick command determination and accurate engagement in these threats, the combat system has emerged in frigate. Frigates conduct anti-surface, anti-submarine, and anti-aircraft as the core forces of the fleet. In this study, the combat effectiveness measures naval frigates using AHP (analytic hierarchy process) method. A hierarchical structure for measuring the combat effectiveness was developed, and weights of criteria were calculated by expert surveys and pair-wise comparisons. In addition, the combat effectiveness of frigates was synthesized and compared. The weights for each attribute were calculated, and the weights for the three main attributes were in the order of act (0.594), evaluate (0.277), and see (0.129). As a result of calculating the weight, anti surface warfare (0.203) was the highest. The combat effectiveness of FFG Batch-III, which has advanced hardware and software and improved combat system capabilities, see (1.73 to 2.56 times), evaluate (1.68 to 2.08 times), and act (1.31 to 3.80 times) better than the comparative frigate. In summarizing the combat effects of the frigate, FFG Batch-III was 1.41~2.95 times superior to the comparative frigate. In particular, a group of experts evaluated the act importantly, resulting in better combat effectiveness.