Evaluation of Anti-Tank Guided Missiles: An integrated Fuzzy Entropy and Fuzzy CoCoSo multi criteria methodology using technical and simulation data

Erdal, Hami̇t; DAĞISTANLI, Hakan Ayhan; KURTAY, Kemal Gürol; ALTUNDAŞ, Aygün

doi:10.1016/j.asoc.2023.110145

Cited by 12 publications

(5 citation statements)

References 64 publications

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“…Hence, artifact components can be separated effectively by the entropy criterion. Compared with approximate entropy and sample entropy, fuzzy entropy has the advantages of better anti-noise performance and higher stability ( Erdal et al, 2023 ). Therefore, fuzzy entropy is used as the basis for ECG component discrimination.…”

Section: Methodsmentioning

confidence: 99%

Improved multi-layer wavelet transform and blind source separation based ECG artifacts removal algorithm from the sEMG signal: in the case of upper limbs

Lu,

Gong,

Xue

et al. 2024

Front. Bioeng. Biotechnol.

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Introduction: Surface electromyogram (sEMG) signals have been widely used in human upper limb force estimation and motion intention recognition. However, the electrocardiogram(ECG) artifact generated by the beating of the heart is a major factor that reduces the quality of the EMG signal when recording the sEMG signal from the muscle close to the heart. sEMG signals contaminated by ECG artifacts are difficult to be understood correctly. The objective of this paper is to effectively remove ECG artifacts from sEMG signals by a novel method.Methods: In this paper, sEMG and ECG signals of the biceps brachii, brachialis, and triceps muscle of the human upper limb will be collected respectively. Firstly, an improved multi-layer wavelet transform algorithm is used to preprocess the raw sEMG signal to remove the background noise and power frequency interference in the raw signal. Then, based on the theory of blind source separation analysis, an improved Fast-ICA algorithm was constructed to separate the denoising signals. Finally, an ECG discrimination algorithm was used to find and eliminate ECG signals in sEMG signals. This method consists of the following steps: 1) Acquisition of raw sEMG and ECG signals; 2) Decoupling the raw sEMG signal; 3) Fast-ICA-based signal component separation; 4) ECG artifact recognition and elimination.Results and discussion: The experimental results show that our method has a good effect on removing ECG artifacts from contaminated EMG signals. It can further improve the quality of EMG signals, which is of great significance for improving the accuracy of force estimation and motion intention recognition tasks. Compared with other state-of-the-art methods, our method can also provide the guiding significance for other biological signals.

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Section: Methodsmentioning

confidence: 99%

Improved multi-layer wavelet transform and blind source separation based ECG artifacts removal algorithm from the sEMG signal: in the case of upper limbs

Lu,

Gong,

Xue

et al. 2024

Front. Bioeng. Biotechnol.

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“…Health Services [14] Fuzzy Delphi, DEMATEL, influential-network-relation map (INRM), DANP Selecting the Optimal Resilience Training Programme [15] Fuzzy TOPSIS, Fuzzy AHP The Anti-Tank Guided Missiles (ATGMs) Selection Conundrum [16] Fuzzy Entropy, Fuzzy CoCoSo with Bonferroni Navigating Decision-Making Processes in the Serbian Armed Forces [17] Fuzzy logic Overseeing Military Human Resource Management [18] SAPEVO-M, ELECTRE-MOr Evaluating International High-Performance Aircraft for Defence Applications [19] Fuzzy AHP, Fuzzy TOPSIS Identifying Optimal Locations for Landing Operation Points [20] Fuzzy LMAW, Fuzzy SAW, Fuzzy MABAC, Fuzzy VIKOR, Fuzzy COPRAS, Fuzzy MAIRCA Facilitating Decision-Making within the Engineering Units of the Serbian Army [21] Fuzzy logic A Systematic Approach to Warship Selection [22] AHP Optimal Military Aircraft Selection Strategies [23] Interval Type-2 Fuzzy AHP, Interval Type-2 Fuzzy TOPSIS Strategic Military Camp Selection [24] LBWA, Z-MAIRCA Criteria for Selecting Fighter Aircraft [25] ARAS, FUCOM Unmanned Aerial Vehicle (UAV) Selection Criteria and Challenges [26] AHP, TOPSIS Evaluation of River Crossing Location Strategies [27] Fuzzy logic…”

Section: Research Subject and Referencementioning

confidence: 99%

Optimising Assault Boat Selection for Military Operations: An Application of the DIBR II-BM-CoCoSo MCDM Model

Tešić,

Božanić,

Radovanović

et al. 2023

JIMD

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In the pivotal task of selecting an assault boat conducive for military operations, especially amidst the challenges posed by water obstacles, the utilisation of Multi-Criteria Decision-Making (MCDM) methods surfaces as vital. In this investigation, a meticulous application of the DIBR II (Defining Interrelationships Between Ranked criteria II) -BM (Bonfferoni Mean) -CoCoSo (COmbined COmpromise SOlution) multi-criteria decision-making model is performed. Initially, the weight coefficients of the criteria were determined via the DIBR II method, with expert opinions being cohesively aggregated using BM operators. Subsequently, the CoCoSo method was employed to discern the optimal alternative among various assault boats. A comprehensive analysis, entailing the examination of the sensitivity of the output results to alterations in the weight coefficients of the criteria, was conducted post-final ranking of alternatives. Noteworthy is the finding that negligible deviations in defining the weight coefficients by experts do not impose a significant impact on the ultimate selection of the optimal alternative. Furthermore, a comparative analysis alongside other MCDM methods corroborated not only the efficacy but also the superiority of the implemented model. The insights derived underscore the practical applicability, stability, and accuracy of the proposed model in choosing assault boats for military operations. This exploration fortifies the decision-making process in military contexts related to overcoming water obstacles and portends potential applicability in domains necessitating intricate multi-criteria decision-making.

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“…(17) Indica que una distribución amplia representa más incertidumbre que la de una distribución con picos pronunciados. (18) Cuanto mayor diversidad haya en las evaluaciones (valores) de las alternativas, mayor importancia deberá tener dicho criterio en la decisión final, ya que posee mayor poder de discriminación entre las alternativas. El método mide la diversidad de un criterio, a través de la entropía.…”

Section: Método Entropíaunclassified

Evaluation and Prioritization of Training Programs for the Management of Marfan Syndrome

Ezcurdia Barzaga,

Troya Altamirano,

Betancourt Rubio

2023

Data and Metadata

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Introduction: Marfan Syndrome has been a connective tissue disease affecting multiple systems of the body, requiring an interdisciplinary diagnostic and therapeutic approach. The variability in presentation and potential complications underscored the need for precise and specialized medical training. Therefore, the general objective of this research is to evaluate specific training programs to improve the diagnosis and management of Marfan Syndrome by identifying critical gaps in current medical practice.Method: Multicriteria decision-making methodologies were used, including the AHP Saaty method to quantify the incidence of diagnostic gaps and the MOORA method to prioritize medical training programs based on the improvement of the diagnosis and treatment of Marfan Syndrome.Results: The analysis revealed that insufficient knowledge and incomplete clinical evaluations are the main gaps. Priority training programs included the advanced course in clinical genetics and the training program in echocardiography, noted for their direct capacity to improve clinical outcomes.Conclusions: Medical education in genetics and echocardiography must be prioritized to effectively address Marfan Syndrome. The implementation of these programs constitutes the support to close the identified gaps. Thus, they significantly improve early diagnosis and management of complications, promoting interdisciplinary collaboration in patient care.

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Evaluation of Anti-Tank Guided Missiles: An integrated Fuzzy Entropy and Fuzzy CoCoSo multi criteria methodology using technical and simulation data

Cited by 12 publications

References 64 publications

Improved multi-layer wavelet transform and blind source separation based ECG artifacts removal algorithm from the sEMG signal: in the case of upper limbs

Improved multi-layer wavelet transform and blind source separation based ECG artifacts removal algorithm from the sEMG signal: in the case of upper limbs

Optimising Assault Boat Selection for Military Operations: An Application of the DIBR II-BM-CoCoSo MCDM Model

Evaluation and Prioritization of Training Programs for the Management of Marfan Syndrome

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