标题： 基于拒绝吉布斯悖论后的更高相似性-更高熵关系的多样性评估 显示英文标题

标题： Diversity Assessment Based on a Higher Similarity-Higher Entropy Relation after Rejection of Gibbs Paradox

摘要： 信息源符号的多样性是根据熵作为信息损失的定义计算的，并在拒绝吉布斯悖论陈述后，遵循新的熵-符号相似性关系。 在0到1范围内的多样性，一个类似于香农冗余的指数，随着物种相似性的增加而减少。 已经定义并使用了一种成对的相似性公式，以证明多样性表达式给出了预期的多样性。 更高的熵-更高相似性关系导致更高的信息-更高多样性关系。 显示英文摘要

摘要： The diversity of the symbols of the information source is calculated following the definition that entropy is the information loss and following a new entropy-symbol similarity relation after the rejection of the Gibbs paradox statement. Diversity in a range of 0 to 1, an index similar to Shannon's redundancy, decreases with the increase in the species similarities. A pairwise similarity formula has been defined and used to demonstrated that the diversity expression gives the expected diversity. The higher entropy-higher similarity relation leads to the higher information-higher diversity relation.