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The Combination Operator of Information Sources by a New Expressive Matrix

机译:新型表达矩阵的信息源组合算子

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The multi-sensors fusion refers to the synergistic combination of sensory data from multiple sensors to provide more accurate and reliable information. The potential benefits of the Fusion are multi-sensors’ redundancy and extra information acquired. The fusion of redundant information can reduce the overall uncertainty and thus helps to provide information specified more precisely. Several sensors providing redundant information can also be used to increase reliability in the case of error, omission or failure of sensors. The combination operators are exponential and are more complex in terms of calculation; the Dempster-Shafer operator is exponential for more than three (3) information sources?[1] [2]. Our work focuses on the definition of another formulation of this operation, and puts it in a matrix form to illuminate the computational complexity, more precision guaranty and a minimal execution time. We propose to use each information source in a form of a matrix, which contains 0 value in lines that do not contain the masses (m(Ai) = 0) or once m(Ai) is not null (m(Ai) ≠ 0). The use of this expressed matrix attempts to ameliorate Dempster-Shafer operator via initialing either a criterion or criteria sources’ solution, increasing the efficiency of the Dempster-Shafer operator and facilitates the combination among the sources. We evaluate our approach by conducting a case study for showing the effectiveness of this matrix.
机译:多传感器融合是指来自多个传感器的传感数据的协同组合,以提供更准确和可靠的信息。 Fusion的潜在好处是多传感器的冗余和获得的额外信息。冗余信息的融合可以减少总体不确定性,从而有助于提供更精确指定的信息。在传感器出现错误,遗漏或故障的情况下,也可以使用提供冗余信息的多个传感器来提高可靠性。组合运算符是指数的,并且在计算方面更复杂; Dempster-Shafer运算符对于三(3)个以上的信息源是指数的?[1] [2]。我们的工作集中于此操作的另一种表示形式的定义,并将其以矩阵形式显示以阐明计算复杂性,更精确的保证和最少的执行时间。我们建议使用矩阵形式的每个信息源,该矩阵在不包含质量的行中包含0值(m(Ai)= 0)或一旦m(Ai)不为空(m(Ai)≠0 )。使用此表示的矩阵试图通过初始化一个或多个标准源的解决方案来改善Dempster-Shafer算子,从而提高Dempster-Shafer算子的效率并促进这些源之间的组合。我们通过进行案例研究以评估此矩阵的有效性来评估我们的方法。

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