With respect to multiple criteria group decision making problems with conflicting and non-commensurable criteria, it is generally difficult to find an alternative that meets all the criteria simultaneously. By extending the fuzzy VIKOR method, this study provides a rational and systematic process for developing the best alternative and compromise solution under the interval-valued intuitionistic fuzzy environment. Furthermore, a fuzzy cross-entropy approach is proposed to state the discrimination measure between optional and optimal interval-valued intuitionistic fuzzy numbers. Finally, to expatiate on the practical value of the method proposed, an illustrative example is presented to demonstrate its practicality and effectiveness over existing TOPSIS method.

The harsh scientific research environment of Antarctic stations demands a reliable energy supply; however, traditional methods not only pose a challenge in supply but also harm the environment. Antarctic energy supply has become a new choice for energy development in Antarctica due to its abundant wind energy resources. Using ERA5 10 m wind field reanalysis data, we compared and analyzed the correlation (r) and Root Mean Square Error (RMSE) between some observation stations and reanalysis data, with correlations above 0.67 and root mean square error below 2.3. This indicates that the accuracy of the ERA5 data is suitable for resource assessment at stations in Antarctica. We assessed the wind energy potential of the Great Wall, Zhongshan, Kunlun and Taishan Stations. The results show that the annual distribution and long-term trend of wind energy at Taishan Station are the best, followed by the Great Wall, Zhongshan and Kunlun Stations. Taishan Station has stable wind direction and abundant wind energy, the average wind power density is 800 W/m², with an annual growth trend of 2.02 W/m²·yr⁻¹. The effective wind speed occurrence and energy level occurrence are generally above 90% and the coefficient of variation is generally below 0.8. The dominant direction of wind energy is northeast and the wind direction is stable, which is conducive to the development and utilization of wind energy.

Changes in the information age have induced the necessity for a more efficient and effective self-decision-making requirement. A method of extracting and constructing naval operations decision-making rules based on scenario analysis is proposed. The template specifications of Event Condition Action (ECA) rules are defined, and a consistency detection method of ECA rules based on SWRL is proposed. The logical relationships and state transitions of the naval operational process is analyzed in detail, and the association of objects, events, and behaviors is realized. Finally, the operation of the proposed methods is illustrated through an example process, showing the method can effectively solve the problems of self-decision-making rule extraction and construction among naval battlefield decision environment, and avoid relying on artificial intelligence, which may have brought some uncertain factors.