COMBAT SIMULATION - TWO SIDES.xls

The data are the outputs of the simulation of a closed-loop, two-sides (Blue vs Red) combat model saved in an Excel spreadsheet. The 1st tab has the input data while the other two tabs have the outputs for the Blue and for the Red. Each column in the Input tab is a design point randomly selected (250 in total). The first two rows represent the number of tanks and recce of the Blue, while rows 3 and 4 represent the respective Red. The 5th row represents the probability of shock that has been applied the same to both sides. Rows 6, 7 and 8 represent the percentage Unit participation of Tanks, Machine Guns and Anti-tanks respectively. These last three variables also apply equally to both Blue and Red.The model used (SIMBAT) is stochastic and therefore each design point was run 40 times, taking care to use the same random numbers for each point (Common Random Numbers) Therefore each of the 250 columns in the two output tabs has 40 rows.The data have been used in%3AP. Boutselis, Trevor J. RingroseGAMLSS and neural networks in combat simulation metamodelling%3A A case study. Expert Syst. Appl. 40(15)%3A 6087-6093 (2013), doi%3A10.1016/j.eswa.2013.05.023to produce two different metamodels%3A a statistical model (GAMLSS) and a neural network (ANN), while recently the same data have been used to produce a Bayesian Network.

本数据集为存储于Excel电子表格中的闭环双边（蓝军对阵红军）作战模型仿真输出结果。首个工作表包含输入数据，其余两个工作表分别对应蓝军与红军的仿真输出。输入工作表的每一列均为一组随机选取的设计点，总计250组。前两行分别记录蓝军的坦克与侦察车（recce）数量，第三、四行则对应红军的同类装备数量。第五行代表双方统一设定的冲击概率。第六、七、八行分别代表坦克、机枪与反坦克武器的单位参与占比，上述三项参数同样适用于红蓝双方。本次采用的仿真模型（SIMBAT）为随机模型，因此每组设计点均需执行40次运算，且采用公共随机数法（Common Random Numbers）确保每组设计点使用完全一致的随机数序列。因此两个输出工作表的250列数据中，每一列均包含40行结果。本数据集曾被应用于P. 布特塞利斯（P. Boutselis）与特雷弗·J. 林罗斯（Trevor J. Ringrose）的研究论文《作战仿真元建模中的GAMLSS与神经网络：一则案例研究》，该论文发表于《专家系统与应用》（Expert Systems with Applications）40(15): 6087-6093 (2013)，DOI: 10.1016/j.eswa.2013.05.023。该项研究构建了两类不同的元模型：统计模型（GAMLSS）与人工神经网络（ANN, Artificial Neural Network）。近期该数据集还被用于构建贝叶斯网络（Bayesian Network）。