Target Recognition Method for UAV Multi-Sensor Information Fusion Based on IVIF Multiple Attribute Decision Making

2019 ◽  
Author(s):  
YuehaoYan ◽  
Zhiying Lv ◽  
Feihong Jiang ◽  
Chengda Li
Keyword(s):  
Decision Making ◽  
Information Fusion ◽  
Target Recognition ◽  
Multiple Attribute Decision Making ◽  
Recognition Method ◽  
Multiple Attribute ◽  
Sensor Information

scholarly journals Hesitant Fuzzy Generalised Bonferroni Mean Operators Based on Archimedean Copula for Multiple-Attribute Decision-Making

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Ju Wu ◽  
Fang Liu ◽  
Yuan Rong ◽  
Yi Liu ◽  
Chengxi Liu
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Information Fusion ◽  
Multiple Attribute Decision Making ◽  
Aggregation Operator ◽  
Archimedean Copula ◽  
Fuzzy Information ◽  
Bonferroni Mean ◽  
Operation Rules ◽  
Multiple Attribute

Information fusion is an important part of multiple-attribute decision-making, and aggregation operator is an important tool of decision information fusion. Integration operators in a variety of fuzzy information environments have a slight lack of consideration for the correlation between variables. Archimedean copula provides information fusion patterns that rely on the intrinsic relevance of information. This paper extends the Archimedean copula to the aggregation of hesitant fuzzy information. Firstly, the Archimedean copula is used to generate the operation rules of the hesitant fuzzy elements. Secondly, the hesitant fuzzy copula Bonferroni mean operator and hesitant fuzzy weighted copula Bonferroni mean operator are propounded, and several properties are proved in detail. Furthermore, a decision-making method based on the operators is proposed, and the specific decision steps are given. Finally, an example is presented to illustrate the practical advantages of the method, and the sensitivity analysis of the decision results with the change of parameters is carried out.

An Improved Close Value Method for Multi-Sensor Object Recognition

2014 ◽  
Vol 707 ◽  
pp. 487-490
Author(s):  
Chang Qing Zhang
Keyword(s):  
Decision Making ◽  
Object Recognition ◽  
Information Fusion ◽  
Information Entropy ◽  
Recognition Method ◽  
Multi Attribute Decision Making ◽  
Sensor Information

Multi-sensor information fusion problem contains many characteristic indexes, and thus it can be resolved using a multi-attribute decision making method. Information entropy is used to objectively determine the attributes weights, and thus it can overcome the subjective randomness. The aim of this paper is to develop a new multi-sensor object recognition method based on close value method. The example of part recognition proves that the proposed method is both feasible and effective.

PENERAPAN METODE SIMPLE ADDITIVE WEIGHTING DALAM PENETAPAN TENAGA KEPENDIDIKAN BERPRESTASI

2018 ◽  
Vol 1 (2) ◽  
pp. 45-54
Author(s):  
Helpi Nopriandi
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Multiple Attribute Decision Making ◽  
Multiple Attribute ◽  
Simple Additive Weighting

Tenaga Kependidikan merupakan anggota masyarakat yang mengabdikan diri dan diangkat untuk menunjang penyelenggaraan pendidikan. Decision Support Systems atau lebih dikenal dengan Sistem Pendukung Keputusan adalah bagian dari sebuah sistem informasi yang berbasis komputer termasuk sistem yang berbasis ilmu pengetahuan dan dipakai untuk mendukung pengambil  keputusan dalam suatu organisasi atau perusahaan. untuk memudahkan pimpinan dalam mengambil sebuah keputusan dibuatlah suatu sistem pengambil keputusan dengan menggunakan Fuzzy Multiple Attribute Decision Making  (FMADM) digunakan untuk mencari alternatif optimalkan dari sejumlah alternatif dengan kriteria tertentu, sedangkan metode Simple Additive Weighting (SAW). Metode SAW sering juga dikenal istilah metode penjumlahan terbobot. Konsep dasar metode SAW adalah mencari penjumlahan terbobot dari rating kinerja pada setiap alternatif dari semua atribut.

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