Discovery of the Significant Impacts of Swell Propagation on Global Wave Climate Change

This study compared the differences in the wave climate in the South China Sea and North Indian Ocean under these two datasets:ERA-40 wave reanalysis and Mei’s hindcast wave data.In the numerical calculation of regional ocean waves,the wave climate characteristics exhibited significant bias if the influence of external swells(swells from afar)was not fully considered,which may provide an incorrect basis for global climate change analysis.1)The trends of the significant wave height(SWH)obtained from the two datasets showed significant differences,such as those of the Bay of Bengal and the Java Sea in June-July-August.For the past 45 years,SWH from ERA-40(SWH-ERA)exhibited a significant annual increase in low-latitude waters of the North Indian Ocean(0.2-0.6 cm yr^(-1))and South China Sea(0.2-0.8 cm yr^(-1)).2)In the Bay of Bengal,the SWH-ERA in each month was generally 0.5 m higher than the SWH from Mei’s hindcast wave data(SWH-Mei)and can reach 1.0 m higher in some months.3)In the Bay of Bengal,SWH-ERA and SWH-Mei increased significantly at annual rates of 0.13 and 0.27 cm yr^(-1),respectively.This increasing trend was mainly reflected after 1978.SWH-ERA showed a trough in 1975(1.33 m)and a crest in 1992(1.83 m),which were not reflected in SWH-Mei.

A positive trend in the stability of global offshore wind energy

The recognition on the trend of wind energy stability is still extremely rare,although it is closely related to acquisition efficiency,grid connection,equipment lifetime,and costs of wind energy utilization.Using the 40-year(1979–2018)ERA-Interim data from the European Center for Medium-Range Weather Forecasts,this study presented the spatial-temporal distribution and climatic trend of the stability of global offshore wind energy as well as the abrupt phenomenon of wind energy stability in key regions over the past 40 years with the climatic analysis method and Mann-Kendall(M-K)test.The results show the following 5 points.(1)According to the coefficient of variation(C_(v))of the wind power density,there are six permanent stable zones of global offshore wind energy:the southeast and northeast trade wind zones in the Indian,Pacific and Atlantic oceans,the Southern Hemisphere westerly,and a semi-permanent stable zone(North Indian Ocean).(2)There are six lowvalue zones for both seasonal variability index(S_(v))and monthly variability index(M_(v))globally,with a similar spatial distribution as that of the six permanent stable zones.M_(v) and S_(v) in the Arabian Sea are the highest in the world.(3)After C_(v),M_(v) and S_(v) are comprehensively considered,the six permanent stable zones have an obvious advantage in the stability of wind energy over other sea areas,with C_(v) below 0.8,M_(v) within 1.0,and S_(v) within 0.7 all the year round.(4)The global stability of offshore wind energy shows a positive climatic trend for the past four decades.C_(v),M_(v) and S_(v) have not changed significantly or decreased in most of the global ocean during 1979 to2018.That is,wind energy is flat or more stable,while the monthly and seasonal variabilities tend to shrink/smooth,which is beneficial for wind energy utilization.(5)C_(v) in the low-latitude Pacific and M_(v) and S_(v) in both the North Indian Ocean and the low-latitude Pacific have an obvious abrupt phenomenon at the end of the20th century.

Modeling of Naval Vessels Combat System based on Complex Network

Naval Vessels Combat System is a kind of complex system.The modeling of combat system has become hot issues in the past years.This paper proposed a new method to establish models of combat system based on the theory of Complex Network.The method of modeling considered the operational entities as nodes.It considered flow of information,substance and energy as edges in a network.The research also carries on a simulation to prove the applicability.Ultimately,the paper concluded that this method is applicable and accurate.

A Detail Investigation on the Antarctic Wind Energy

The scientific development of wind energy based on local conditions is conducive to the urgent energy demand and environmental protection of Antarctic region.In this study,the ERA5 reanalysis data are used to evaluate the wind energy resources in the Antarctic region.A series of key indicators,such as wind power density,effective wind speed occurrence,energy level occurrence and stability,are comprehensively considered by using climate statistical analysis methods to analyze the temporal and spatial distribution characteristics of Antarctic wind energy resources.The results show that the Antarctic region contains abundant wind energy resources,which benefits the construction of scientific research stations.The superior areas are the Southern Ocean and the coast of the East Antarctica,followed by the Transantarctic Mountains,the coast of the Bellingshausen Sea and Amundsen Sea.These areas have advantages in terms of wind power density(500-2500 W/m2),effective wind speed occurrence(80%-90%),energy level occur-rence(60%-90%)and stability(Cv:0.6-1,Mv:1.2-1.8,Sv:0.8-1.2).The Antarctic’s wind energy resources in wind power density,effective wind speed occurrence and energy level occurrence in autumn and winter are better than those in summer,while the coefficient of variation in summer is worse than that in autumn and winter.

Performance Evaluation of Three Parameterizations on Internal Tidal Mixing in the Northern Pacific

The accurate assessment of the energy dissipation of internal tides(ITs)is of great importance because ITs contribute significantly to abyssal mixing.Thus,in this study,the IT-driven dissipation and diapycnal diffusion in the northern Pacific are esti-mated using parameterizations proposed by St.Laurent et al.(2002),Koch-Larrouy et al.(2007),and de Lavergne et al.(2020)(hereaf-ter referred to as LSJ02,KL07,and dL20,respectively).The performances of the three parameterizations are evaluated by comparing the calculated results with fine structure observations.In particular,the dissipation estimated by LSJ02 parameterization shows a bottom-intensified characteristic,with the patterns showing good agreement with the observations near seamounts.Moreover,43%of the results calculated using the LSJ02 parameterization have errors lower than one order of magnitude in the generation sites of ITs.Meanwhile,the strongest dissipation estimated by the KL07 parameterization shifts to the thermocline,with the results showing the highest level of consistency with observations in the generation sites.The proportion of results with errors lower than one order of magnitude is 80.7%.Furthermore,the results calculated by dL20 parameterization agree well with the observations in the upper and middle layers,with the parameterization showing an accurate estimation of the remote dissipation.The percentages of the errors lower than one order of magnitude between the dL20 parameterization and observations account for 77.1%and 88.7%in the genera-tion sites and far-field regions,respectively.

Multi-attribute decision making method for air target threat evaluation based on intuitionistic fuzzy sets

The function of the air target threat evaluation （TE） is the foundation for weapons allocation and senor resources management within the surface air defense. The multi-attribute evaluation methodology is utilized to address the issue of the TE in which the tactic features of the detected target are treated as evaluation attributes. Meanwhile, the intuitionistic fuzzy set （IFS） is employed to deal with information uncertainty in the TE process. Furthermore, on the basis of the entropy weight and inclusion-comparison probability, a hybrid TE method is developed. In order to accommodate the demands of naturalistic decision making, the proposed method allows air defense commanders to express their intuitive opinions besides incorporating into the threat features of the detected target. An illustrative example is provided to indicate the feasibility and advantage of the proposed method.

Immune multi-agent model using vaccine for cooperative air-defense system of systems for surface warship formation based on danger theory

Aiming at the problem on cooperative air-defense of surface warship formation, this paper maps the cooperative airdefense system of systems （SoS） for surface warship formation （CASoSSWF） to the biological immune system （BIS） according to the similarity of the defense mechanism and characteristics between the CASoSSWF and the BIS, and then designs the models of components and the architecture for a monitoring agent, a regulating agent, a killer agent, a pre-warning agent and a communicating agent by making use of the theories and methods of the artificial immune system, the multi-agent system （MAS）, the vaccine and the danger theory （DT）. Moreover a new immune multi-agent model using vaccine based on DT （IMMUVBDT） for the cooperative air-defense SoS is advanced. The immune response and immune mechanism of the CASoSSWF are analyzed. The model has a capability of memory, evolution, commendable dynamic environment adaptability and self-learning, and embodies adequately the cooperative air-defense mechanism for the CASoSSWF. Therefore it shows a novel idea for the CASoSSWF which can provide conception models for a surface warship formation operation simulation system.

Infrared image segmentation method based on 2D histogram shape modification and optimal objective function

In the methods of image thresholding segmentation, such methods based on two-dimensional （2D） histogram and optimal objective functions are important. However, when they are used for infrared image segmentation, they are weak in suppressing background noises and worse in segmenting targets with non-uniform gray level. The concept of 2D histogram shape modification is proposed, which is realized by target information prior restraint after enhancing target information using plateau histogram equalization. The formula of 2D minimum Renyi entropy is deduced for image segmentation, then the shape-modified 2D histogram is combined wfth four optimal objective functions （i.e., maximum between-class variance, maximum entropy, maximum correlation and minimum Renyi entropy） respectively for the appli- cation of infrared image segmentation. Simultaneously, F-measure is introduced to evaluate the segmentation effects objectively. The experimental results show that F-measure is an effective evaluation index for image segmentation since its value is fully consistent with the subjective evaluation, and after 2D histogram shape modification, the methods of optimal objective functions can overcome their original forms＇ deficiency and their segmentation effects are more or less improvements, where the best one is the maximum entropy method based on 2D histogram shape modification.

Dynamic WTA optimization model of air defense operation of warships' formation

WTA （weapon-target allocation） of air defense operation is a very complicated problem and current models focus on static and restricted WTA problem mostly. Based on the dynamic characteristics of air defense operational command and decision of warships＇ formation, a dynamic WTA model is established. Simulation results show that switch fire and repetition fire of anti-air weapon system affect the result of the air defense operation remarkably and the dynamic model is more satisfying than static ones. Related results are gained based on the analysis of the simulation results and the results are accordant with the intuitionistic tactical judgment. The model is some reference for the research of air defense C^3I system of warships＇ formation.

Method for Underwater Target Tracking Based on an Interacting Multiple Model

According to the requirements of real-time performance and reliability in underwater maneuvering target tracking as well as clarifying motion features of the underwater target, an interacting multiple model algorithm based on fuzzy logic inference （FIMM） is proposed. Maneuvering patterns of the target are represented by model sets, including the constant velocity model （CA）, the Singer mode~, and the nearly constant speed horizontal-turn model （HT） in FIMM technology. The simulation results show that compared to conventional IMM, the reliability and real-time performance of underwater target tracking can be improved by FIMM algorithm.

The seasonal variations in the significant wave height and sea surface wind speed of the China's seas

Long-term variations in a sea surface wind speed （WS） and a significant wave height （SWH） are associated with the global climate change, the prevention and mitigation of natural disasters, and an ocean resource exploitation, and other activities. The seasonal characteristics of the long-term trends in China＇s seas WS and SWH are determined based on 24 a （1988-2011） cross-calibrated, multi-platform （CCMP） wind data and 24 a hindcast wave data obtained with the WAVEWATCH-III （WW3） wave model forced by CCMP wind data. The results show the following. （1） For the past 24 a, the China＇s WS and SWH exhibit a significant increasing trend as a whole, of 3.38 cm/（s.a） in the WS, 1.3 cm/a in the SWH. （2） As a whole, the increasing trend of the China＇s seas WS and SWH is strongest in March-April-May （MAM） and December-January-February （DJF）, followed by June-July-August （JJA）, and smallest in September-October-November （SON）. （3） The areal extent of significant increases in the WS was largest in MAM, while the area decreased in JJA and DJF; the smallest area was apparent in SON. In contrast to the WS, almost all of China＇s seas exhibited a significant increase in SWH in MAM and DJF; the range was slightly smaller in JJA and SON. The WS and SWH in the Bohai Sea, the Yellow Sea, East China Sea, the Tsushima Strait, the Taiwan Strait, the northern South China Sea, the Beibu Gull and the Gulf of Thailand exhibited a significant increase in all seasons. （4） The variations in China＇s seas SWH and WS depended on the season. The areas with a strong increase usually appeared in DJF.

Generalized ordered weighted averaging operators based methods for MADM in intuitionistic fuzzy set setting

Multiattribute decision making（MADM） problems, in which the weights and ratings of alternatives are expressed with intuitionistic fuzzy（IF） sets, are investigated.Firstly, the relative degrees of membership and the relative degrees of non-membership are formulated as IF sets, the weights and values of alternatives on both qualitative and quantitative attributes may be expressed as IF sets in a unified way.Then a MADM method based on generalized ordered weighted averaging operators is proposed.The proposed method is illustrated with a numerical example.

Mission-Oriented Configuration Model of Aircraft Carrying Spares and Dynamic Optimization Policy

Spare parts are critical to scheduled maintenance and fault repair, and can directly affect the readiness and combat capability of equipment. Equipmentrs capacity of carrying spares is influenced by its storage space and scales, so it is necessary to consider economic factors, e.g. spares cost, as well as non-economic ones, such as spares volume, mass and scale, when optimizing spares configuration. Aiming at this problem, the optimization model based on multi-constraints for carrying spares is built by METRIC theory and system analysis. Through the introduction of Lagrange factors, the spares cost is transformed to shadow price, and the optimization method for carrying spares and the dynamic adjustment policy of Lagrange factors are proposed. The result of a given example is analyzed, and demonstrates that the proposed model can be optimized with all constraints, and the research can provide a new way for carrying spares optimization.

An Algorithm of the Adaptive Grid and Fuzzy Interacting Multiple Model

This paper studies the algorithm of the adaptive grid and fuzzy interacting multiple model （AGFIMM） for maneuvering target tracking, while focusing on the problems of the fixed structure multiple model （FSMM） algorithm＇s cost-efficiency ratio being not high and the Markov transition probability of the interacting multiple model （IMM） algorithm being difficult to determine exactly. This algorithm realizes the adaptive model set by adaptive grid adjustment, and obtains each model matching degree in the model set by fuzzy logic inference. The simulation results show that the AGFIMM algorithm can effectively improve the accuracy and cost-efficiency ratio of the multiple model algorithm, and as a result is suitable for enineering apolications.

Impact of observational MJO forcing on ENSO predictability in the Zebiak-Cane model: PartⅠ.Effect on the maximum prediction error

With the observational wind data and the Zebiak-Cane model, the impact of Madden-Iulian Oscillation （MJO） as external forcing on El Nino-Southern Oscillation （ENSO） predictability is studied. The observational data are analyzed with Continuous Wavelet Transform （CWT） and then used to extract MJO signals, which are added into the model to get a new model. After the Conditional Nonlinear Optimal Perturbation （CNOP） method has been used, the initial errors which can evolve into maximum prediction error, model errors and their join errors are gained and then the Nifio 3 indices and spatial structures of three kinds of errors are investigated. The results mainly show that the observational MJO has little impact on the maximum prediction error of ENSO events and the initial error affects much greater than model error caused by MJO forcing. These demonstrate that the initial error might be the main error source that produces uncertainty in ENSO prediction, which could provide a theoretical foundation for the adaptive data assimilation of the ENSO forecast and contribute to the ENSO target observation.

An evaporation duct prediction model coupled with the MM5

Evaporation duct is an abnormal refractive phenomenon in the marine atmosphere boundary layer. It has been generally accepted that the evaporation duct prominently affects the performance of the electronic equipment over the sea because of its wide distribution and frequent occurrence. It has become a research focus of the navies all over the world. At present, the diagnostic models of the evaporation duct are all based on the Monin-Obukhov similarity theory, with only differences in the flux and character scale calculations in the surface layer. These models are applicable to the stationary and uniform open sea areas without considering the alongshore effect. This paper introduces the nonlinear factor a and the gust wind item wg into the Babin model, and thus extends the evaporation duct diagnostic model to the offshore area under extremely low wind speed. In addition, an evaporation duct prediction model is designed and coupled with the fifth generation mesoscale model （MMS）. The tower observational data and radar data at the Pingtan island of Fujian Province on May 25-26, 2002 were used to validate the forecast results. The outputs of the prediction model agree with the observations from 0 to 48 h. The relative error of the predicted evaporation duct height is 19.3% and the prediction results are consistent with the radar detection.

Magnetic Detection Method for Seabed Cable in Marine Engineering Surveying

The detection and identification of the seabed cable is becoming an important task in the marine engineering. The features of the magnetic anomaly can be used to detect the existence of the seabed cable. The magnetic field model is presented, and the consistency of the magnetic anomaly distribution between the simulation of the model and the observed data is verified. The comparison shows that the seabed cable can be effectively detected and identified with reasonable method.

Electronic image stabilization algorithm based on fixed-lag smooth filtering

An algorithm using fixed-lag smooth filtering to improve the precision of EIS algorithm is presented in this paper. Ftrstly, gray projection algorithm （GPA） is used to calculate the interframe global motion vectors. Secondly, the fixed-lag smooth filter is used to smoothen the motion track of the original video sequence, according to different motion models. At last, the original sequence is compensated by using the compensation vectors calculated from filtering. This algorithm has been proved superior in filtering precision by experiments of video sequences in different motion scenes. This algorithm also satisfies the real-time request.

Fuzzy distances based FMAGDM compromise ratio method and application

An extended compromise ratio method（CRM） based on fuzzy distances is developed to solve fuzzy multi-attribute group decision making problems in which weights of attributes and ratings of alternatives on attributes are expressed with values of linguistic variables parameterized using triangular fuzzy numbers.A compromise solution is determined by introducing the ranking index based on the concept that the chosen alternative should be as close as possible to the positive ideal solution and as far away from the negative ideal solution as possible simultaneously.This proposed method is compared with other existing methods to show its feasibility and effectiveness and illustrated with an example of the military route selection problem as one of the possible applications.