F
Florentin Smarandache
Researcher at University of New Mexico
Publications - 1964
Citations - 31054
Florentin Smarandache is an academic researcher from University of New Mexico. The author has contributed to research in topics: Fuzzy logic & Fuzzy set. The author has an hindex of 69, co-authored 1897 publications receiving 27563 citations. Previous affiliations of Florentin Smarandache include International Islamic University, Islamabad & Mohammed V University.
Papers
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Proceedings ArticleDOI
Target Type Tracking with PCR5 and Dempster's rules: A Comparative Analysis
TL;DR: In this paper, the authors consider and analyze the behavior of two combinational rules for temporal/sequential attribute data fusion for target type estimation for real-time Generalized Data Association - Multi Target Tracking systems (GDA-MTT).
Posted Content
The use of the pivot pairwise relative criteria importance assessment method for determining the weights of criteria
Florentin Smarandache,Dragisa Stanujkic,Edmundas Kazimieras Zavadskas,Darjan Karabasevic,Zenonas Turskis +4 more
TL;DR: In this article, two extensions of the SWARA method that can be used in cases when it is not easy, or even is impossible to reach a consensus on the expected importance of the evaluation criteria are proposed.
Book ChapterDOI
Solving the supply chain problem using the best-worst method based on a novel Plithogenic model
Mohamed Abdel-Basset,Rehab Mohamed,Abd El-Nasser H. Zaied,Abduallah Gamal,Florentin Smarandache +4 more
TL;DR: This paper proposes a plithogenic model based on the best-worst method, and presents two real-world supply chain problems as case studies to test the proposed model; these problems are warehouse location and plant evaluation.
Journal ArticleDOI
Neutrosophic Parametrized Soft Set Theory and Its Decision Making
TL;DR: In this article, the authors presented definition of neutrosophic parameterized (NP) soft set and its operations and defined NP-aggregation operator to form NP-soft decision making method which allows constructing more efficient decision processes.
Journal ArticleDOI
Evidence supporting measure of similarity for reducing the complexity in information fusion
TL;DR: In this paper, the authors presented a new method for reducing the number of sources of evidence to combine in order to reduce the complexity of the fusion processing, which is often required in many applications where the real-time constraint and limited computing resources are of prime importance.