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Method of measurement for the quantification of subjective ideas multidimensional and devices for implementing this process, consisting of an electronic computer

机译:多维主观思维量化的测量方法和实现此过程的设备,包括电子计算机

摘要

1,176,801. Computer programming. J. F. CANGUILHEM. 30 Dec., 1966 [5 Jan., 1966], No. 58447/66. Heading G4A. A computer is programmed to perform "dimensional synthesis" on a plurality of sets of values representing points or vectors in a multi-dimensional space, the synthesis proceeding according to one or more of six subprogrammes which calculate quantities (specified in the claim) concerned with respectively: (1) co-ordinate-scaling using standard deviation, a diagonal value also being calculated, (2) co-ordinate-scaling using range of variation, a diagonal value also being calculated, (3) value of a target quantity in absolute form, for a single entity, (4) as (3) but not in absolute form, (5) value of a target quantity in absolute form, for a group of entities, using vector addition in effect, (6) use of second-order moments for obtaining the value of a target quantity for a group of entities. Entities (e.g. firms) are each plotted as a point in a multidimensional space according to the values they have for certain factors (e.g. manpower, turnover, &c.), each factor corresponding to a respective dimension. The value of a target quantity (e.g. prosperity) for each entity is then given by the (magnitude of the) position vector of the point or the distance of the point from a point representing the optimum. This arises because each dimension is scaled in accordance with the relative importance of the factor towards the target quantity, by taking the magnitude of the unit vector for that dimension proportional to the difference of the largest and smallest values of the corresponding factor (over all entities) divided by the product of hierarchy coefficient representing the importance and a common scale factor. The difference mentioned may be replaced by the standard deviation of the values of the factor. The value of the target quantity may be expressed in absolute form viz. as a percentage of the largest diagonal of the parallelopiped whose sides are the ranges of variation of the respective factors (as found among the entities actually plotted, i.e. not possible variations). The sides of the parallelopiped may alternatively be the standard deviations of the respective factors. The value of the target quantity for the group of entities as a whole (or for a subset of them) may, depending on the nature of the target quantity, be obtained by vector addition of the position vectors of the points representing the entities, or by the principle of moments. In the second case, the target quantity for the group is that of an imaginary entity the importance of which is equal to the sum of the importances of the separate entities, and the second order moment of the importance of which (about the optimum point previously mentioned) is equal to the sum of such moments for the separate entities (the importance of an entity being considered to reside at the point representing the entity). Just as the target quantity can be calculated for a group of entities from its values for the entities as above, so its value for a set of groups can in the same way be calculated from its values for the groups, and so on. Entities can be ordered for desirability according to their distance in the space from the optimum point, or grouped for similarity according to their closeness to each other in the space. Optimization problems can be solved by minimizing the lengths of the trajectories traced out by points in the space as conditions vary. Sub-programmes (procedures) for mathematical calculations required above, and example programmes utilizing them for particular problems, are given in french ALGOL.
机译:1,176,801。电脑编程。 J.F.坎古莱姆1966年12月30日[1966年1月5日],第58447/66号。标题G4A。对计算机进行编程以对表示多维空间中的点或向量的多组值执行“维综合”,该综合根据六个子程序中的一个或多个进行,这些子程序计算与之相关的数量(在权利要求中指定) (1)使用标准偏差进行坐标缩放,还计算对角线值;(2)使用变化范围进行坐标缩放,还计算对角线值;(3)目标量的值绝对形式,对于单个实体,(4)为(3),但不是绝对形式,(5)对于一组实体,实际上使用矢量加法,(5)使用绝对形式的目标数量的值用于获得一组实体的目标数量值的二阶矩。根据实体对某些因素(例如,人力,营业额等)所具有的值,每个实体(例如,企业)都在多维空间中被绘制为一个点,每个因素对应于相应的维度。然后,通过该点的位置矢量(的幅值)或该点与代表最优点的距离来给出每个实体的目标数量(例如,繁荣)的值。之所以会出现这种情况,是因为每个维度都是根据因子对目标数量的相对重要性来缩放的,方法是将该维度的单位向量的大小与相应因子的最大值和最小值之差(在所有实体上)成比例)除以代表重要性的层次系数乘积和共同的比例因子。所提到的差异可以用因子值的标准偏差代替。目标量的值可以以绝对形式表示。表示平行边的最大对角线的百分比,平行边的最大对角线的边是各个因子的变化范围(在实际绘制的实体中发现,即不可能的变化)。平行六面体的侧面可以替代地是各个因素的标准偏差。可以根据目标数量的性质,通过对代表实体的各点的位置矢量进行矢量求和来获得整个实体组(或实体子集)的目标数量值。根据瞬间原则。在第二种情况下,该组的目标数量是一个虚拟实体的数量,该虚拟实体的重要性等于各个实体的重要性之和,以及该重要性的二阶矩(大约是先前的最佳点)提到的)等于这些时间对于各个实体的总和(一个实体的重要性被认为位于代表该实体的点上)。正如可以从上述实体的值为一组实体计算目标数量一样,可以以相同的方式从其组的值计算出一组组的目标数量,依此类推。可以根据实体在空间中距最佳点的距离来对实体进行合乎需要的排序,也可以根据实体在空间中彼此之间的接近程度对实体进行分组以进行相似性分类。通过最小化空间中点随条件变化而绘制的轨迹的长度,可以解决优化问题。上面要求的数学计算子程序(过程),以及使用它们解决特定问题的示例程序,以法语ALGOL给出。

著录项

  • 公开/公告号DE1303305B

    专利类型

  • 公开/公告日1972-06-29

    原文格式PDF

  • 申请/专利权人 CANGUILHEM J;

    申请/专利号DED1303305

  • 发明设计人

    申请日1967-01-03

  • 分类号G06F15/34;

  • 国家 DE

  • 入库时间 2022-08-23 08:35:19

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