blog.csdn

TOPSIS综合评价：贴近度排序原理与MATLAB实现

重点剖析MATLAB实现细节，涵盖topsis_eval函数设计、熵权法客观赋权（规避log (0)）、主客观组合权重策略，以及归一化方式差异、同向化遗漏、极端值干扰等四大典型问题排查。 强调权重敏感性分析与结果可视化对结论可信度的关键作用。
blog.csdn

TOPSIS评价模型MATLAB源码实战：从正向化到熵权法避坑指南

本文系统讲解TOPSIS多属性决策模型在MATLAB中的完整实现，涵盖指标正向化（极小型、中间型、区间型）、数据标准化（向量归一化与比例归一化选择）、熵权法自动赋权（含零值对数处理）、贴近度计算与排序。强调EDA预分析、数据清洗、标准化与权重方法的匹配性，并指出五大典型实施陷阱及权重 ...
clinicaltrialvanguard

FDA Clears Combined Use of Restrata Matrix With Solventum V.A.C. Therapy

Ten months after paying $725 million upfront for Acera Surgical, Solventum has its first tangible regulatory return: FDA 510(k) clearance to use Restrata synthetic electrospun fiber matrix and V.A.C.
TechCrunch

People are using AI to make their smart TVs dumb again

The latest use case for AI? Dumbing down your smart TV to get rid of the bloat. A number of developers and vibe coders have recently been sharing solutions for “vibe-coding” your TV to get rid of ...