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Assessment model of armament battlefield damage based on Bayesian network
Abstract
The battlefield damage of the components in an artillery was researched using computer simulation in order to solve the assessing problem of battlefield damage without complete information. The correlation of component damage was analyzed, lots of data were obtained through simulation, and the correlation of each component was built using a statistical method. The correlation was expressed quantitatively using Bayesian network, and the Bayesian network was built in order to assist an assessment person to assess the battlefield damage. The properties of the network were analyzed based on battlefield hypothesis, and the assessment process was demonstrated using Bayesian network.
In order to integrate equipment battlefield damage models of many levels into one large model, and describe equipment battlefield damage characteristics from resolving power of microcosmic, moderate, and macroscopical angles, composable modeling and simulating technology is studied. The hiberarchy of equipment battlefield damage models is researched from the sides of physical alteration level, function degradation level, and equipment cluster battle effectiveness degradation level. The relations among those different level models are analyzed. The mapping relation between physical alteration battlefield damage model and function degradation battlefield damage model is researched, the function description method based on equipment characteristic is presented, as well as the aggregation/disaggregation method for physical alteration battlefield damage model and function degradation battlefield damage model. The mapping relation between function degradation battlefield damage model and equipment cluster battle effectiveness degradation battlefield damage model is researched, the aggregation/disaggregation method for function degradation battlefield damage model and equipment cluster battle effectiveness degradation battlefield damage model is presented. At last a case of equipment battlefield damage composable modeling is researched. The research result shows that equipment battlefield damage composable modeling and simulating technology can realize high resolving power output for macroscopical model, and it helps to research equipment battlefield damage roundly.
Aiming at the complexity of modern battlefield, diversity, uncertainty and illegibility of battle damage assessment (BDA) data sources, the BDA fuzzy Bayesian networks is constructed by integrate the fuzzy set theory into Bayesian networks. The continuous node of this network is converted to corresponding membership degree, and then the membership degree is converted to probability knowledge which can be used to Bayesian networks inference by possibility transformation theory. The effect on BDA of weather, electronic jamming, optical jamming and weapon-target matching degree are considered in this model. The combat decision-maker can use the model to simulate on the target damage under the varied kinds of attack conditions, and make quick and correct assessment on target damage grade. It can get true target damage information by syncretizing the reconnaissance intelligence collected after the attack, and it also can make use of assessment accuracy to modify the assessment model. Finally, it will provide decision-making evidence for second strike and properly making fire-power configuration scheme.
In order to improve damage diagnosis ability of maintenance personnel, constructing method of Bayesian network applied to weapon battlefield damage diagnosis is researched. Battlefield damage correlations among damaged parts of weapon are analyzed if one weapon is attacked by bombshells, and is the basis of damage diagnosis with the use of Bayesian network. Bayesian network for damage diagnosis is constructed based on K2 arithmetic. Variables sequence is the key factor of Bayesian network constructing, a statistical method of ascertaining variables sequence is presented with the use of weapon battlefield simulation technology.
A new compound, named trollioside, together with nine known compounds, proglobeflowery acid, isoswertisin, isoswertiajaponin, cirsimaritin, veratric acid, vitexin, orientin, beta-sitosterol and daucosterol, were isolated from the ethanol extract of the dried flowers of Trollius chinensis Bunge. The isolation and structural determination of these compounds are discussed.