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doi:10.19062/2247-3173.2023.24

Cited by 2 publications

(1 citation statement)

References 5 publications

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“…These rules are formed based on an exemplary investment evaluation system and determine the recommendation for the type of investment, depending on the financial statistics provided. This kind of data can be obtained from specialized databases or web sites such as [15]. The system of rules is depicted fig.…”

Section: Methodsmentioning

confidence: 99%

Fuzzy Inference System for Investment Value Assessment Based on Historical Data

Slavyanov

2024

ETR

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The analysis of financial parameters is of fundamental importance when planning one or another investment in shares of a given company. It is important for such an analysis to consider some basic numerical parameters such as: annual revenue growth for the last few years, gross, operating, and net profit margins, price/earnings ratio, current price, average annual price, and other historical data for analysis. In this research, an investment decision-making approach based on fuzzy logic is proposed, which evaluates various aspects of a given company's activity. Mamdani method and the fuzzy logic toolset in MATLAB were used. A set of fuzzy rules forms the basis of the investment evaluation system and determines the investment type recommendation, depending on the financial data provided. Simulation experiments with different inputs prove the correct approach and the adequate solutions that can be obtained. The precise set of input variables and well-thought-out logical rules can achieve a reduction in risks for specific investment intentions.

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Section: Methodsmentioning

confidence: 99%

Fuzzy Inference System for Investment Value Assessment Based on Historical Data

Slavyanov

2024

ETR

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Applications of design and reverse engineering for the development of digital and smart tools for composite additive manufacturing

ANDREI,

STROE,

BERBENTE

et al. 2023

INCAS BULLETIN

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This paper presents a study dedicated to the development of Digital and Smart Tools, based on solved applications of design engineering and reverse engineering. This approach is justified by the fact as well as the need for preparations prior to Composite Additive Manufacturing. Future integration of Digital Smart Tools with Composite Additive Manufacturing will significantly contribute to the efficient and effective support of the green economy, the active, responsible, safe and resilient protection of environment, life and climate. The research involved in this paper contributes to develop Digital and Smart Tools Applications, intended for integrated digital design, development, manufacturing and further predictive maintenance and services, based on robotic systems, extended automatic control, Artificial Intelligence and Machine Learning, including Mathematical Modeling and Numerical Simulations for Performance Prediction at Design Regime and Off-Design Regimes for jet engines, with the best capabilities to generate and integrate improvements, optimizations and potential innovative solutions. This paper presents significant applications of design, concept engineering development and reverse engineering design, as: 1/ the design of a transonic axial compressor rotor blade, 2/ the design of a swept axial compressor rotor, 3/ concept design engineering developments in case of a swept fan rotor blade, 4/ concept design developments and reverse engineering in case of a HP axial compressor rotor blade, part of Spey 512-14 DW turbofan engine, 5/ reverse engineering design of a Cessna 182 Skylane N223IF light aircraft wheel cover. In line with Europe´s vision for sustainable aviation, this research study and INCAS´ TGA Project "Technological Development Platform for "Green" Technologies in Aviation and Ecological Manufacturing with Superior Added Value; TGA - Technologies for Green Aviation" will significantly contribute to the Green Deal, as a production center using "Green" Technologies in aviation and ecological manufacturing, as well as collaborative developer of Digital and Smart Tools for Composite Additive Manufacturing.

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Cited by 2 publications

References 5 publications

Fuzzy Inference System for Investment Value Assessment Based on Historical Data

Fuzzy Inference System for Investment Value Assessment Based on Historical Data

Applications of design and reverse engineering for the development of digital and smart tools for composite additive manufacturing

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