scholarly journals Using Fuzzy Logic Method to Investigate the Effect of Economic Sanctions on Business Cycles in the Islamic Republic of Iran

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
M. I. Saeed Iranmanesh ◽  
A. Norallah Salehi ◽  
B. Seyyed Abdolmajid Jalaee
Keyword(s):  
Fuzzy Logic ◽  
Business Cycles ◽  
Economic Sanctions ◽  
Economic Sanction ◽  
Islamic Republic ◽  
Islamic Republic Of Iran ◽  
Fuzzy Logic Method ◽  
The Impact ◽  
Large Sections ◽  
Logic Method

One of the main economic issues in Iran is the issue of economic sanctions. These sanctions have been imposed by various institutions and countries around the world in various forms since 1979 against Iran. Economic sanctions have affected large sections of Iran’s economy. Meanwhile, economic sanctions against Iran have had far-reaching effects on trade cycles in Iran. The purpose of this article is to investigate the impact of economic sanctions on the structure of business cycles in Iran. The sanction index is a tool for studying quantitative sanctions. The opinions of 15 experts in sanctions economics were collected using fuzzy questionnaires. And the sanction index was obtained. The fuzzy logic method in the MATLAB software space calculated the economic sanction index for 1979–2019. The self-regression calculated the effect of economic sanctions on business cycles. There are two scenarios in this article. In scenario 1, sanctions increased inflation, reduced production, and reduced investment. Also, during the embargo period, the recessions are longer. The second scenario of the research shows the economy without sanctions. The results showed that, in these conditions, inflation has less effect on production and investment. And the economy will experience a long period of prosperity without sanctions.

scholarly journals The impact of international economic sanctions on national economies. The Islamic Republic of Iran - a case in point

2020 ◽  
Vol 14 (1) ◽  
pp. 1014-1023
Author(s):  
Flavius Caba-Maria ◽  
Radu-Cristian Muşetescu
Keyword(s):  
United States ◽  
Economic Sanctions ◽  
United Nations Security Council ◽  
Economic Policies ◽  
Islamic Republic ◽  
Nuclear Program ◽  
Economic Statecraft ◽  
Islamic Republic Of Iran ◽  
National Economies ◽  
The Impact

AbstractThis paper explores the impact of economic sanctions on national economies, with specific focus on Iran. It starts by conceptualizing sanctions in the set of economic policies and include them in the framework of economic statecraft, according to literature available. Several hypotheses that attempt to anticipate the form of sanctions are advanced, according to the intensity of geopolitical competition among the states. The analysis uses the case study of the regime of United States’ sanctions against the Islamic Republic of Iran. Tehran and P5+1 powers (the permanent members of the United Nations Security Council and Germany) agreed on a deal regulating the nuclear program of Iran - Joint Comprehensive Plan of Action, meaning that Iran would reduce its nuclear activities drastically in exchange of lifting economic sanctions. In spite of the initial enthusiasm, United States announced in May 2018 the unilateral withdrawal from the deal and reinstating the sanctions regime, spiking new tensions in the relation with Iran. As a result, the paper discusses the context in which Iran tries to pursue economic goals in order to ensure resilience, while the US imposes more pressure. In addition, the study also approaches the dilemma whether sanctions can ultimately generate political answers and at what costs. In this context, it is identifying several alternatives in the Iranian case, together with noting the limits of conceptual refinements in terms of sanctions’ theory.

scholarly journals Using WSR-88D Polarimetric Data to Identify Bird-Contaminated Doppler Velocities

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Yuan Jiang ◽  
Qin Xu ◽  
Pengfei Zhang ◽  
Kang Nai ◽  
Liping Liu
Keyword(s):  
Fuzzy Logic ◽  
Real Data ◽  
Radar Data ◽  
Second Step ◽  
Doppler Velocity ◽  
Data Quality Control ◽  
Fuzzy Logic Method ◽  
Automated Technique ◽  
Migrating Birds ◽  
Logic Method

As an important part of Doppler velocity data quality control for radar data assimilation and other quantitative applications, an automated technique is developed to identify and remove contaminated velocities by birds, especially migrating birds. This technique builds upon the existing hydrometeor classification algorithm (HCA) for dual-polarimetric WSR-88D radars developed at the National Severe Storms Laboratory, and it performs two steps. In the first step, the fuzzy-logic method in the HCA is simplified and used to identify biological echoes (mainly from birds and insects). In the second step, another simple fuzzy logic method is developed to detect bird echoes among the biological echoes identified in the first step and thus remove bird-contaminated velocities. The membership functions used by the fuzzy logic method in the second step are extracted from normalized histograms of differential reflectivity and differential phase for birds and insects, respectively, while the normalized histograms are constructed by polarimetric data collected during the 2012 fall migrating season and sorted for bird and insects, respectively. The performance and effectiveness of the technique are demonstrated by real-data examples.

scholarly journals Feature Extraction in Six Blocks to Detect and Recognize English Numbers

2021 ◽  
pp. 3790-3803
Author(s):  
Heba Kh. Abbas ◽  
Haidar J. Mohamad
Keyword(s):  
Fuzzy Logic ◽  
Feature Extraction ◽  
Computational Cost ◽  
Absolute Error ◽  
Suggested Method ◽  
Support Vector ◽  
Horizontal Line ◽  
Svm Algorithm ◽  
Fuzzy Logic Method ◽  
Logic Method

    The Fuzzy Logic method was implemented to detect and recognize English numbers in this paper. The extracted features within this method make the detection easy and accurate. These features depend on the crossing point of two vertical lines with one horizontal line to be used from the Fuzzy logic method, as shown by the Matlab code in this study. The font types are Times New Roman, Arial, Calabria, Arabic, and Andalus with different font sizes of 10, 16, 22, 28, 36, 42, 50 and 72. These numbers are isolated automatically with the designed algorithm, for which the code is also presented. The number’s image is tested with the Fuzzy algorithm depending on six-block properties only. Groups of regions (High, Medium, and Low) for each number showed unique behavior to recognize any number. Normalized Absolute Error (NAE) equation was used to evaluate the error percentage for the suggested algorithm. The lowest error was 0.001% compared with the real number. The data were checked by the support vector machine (SVM) algorithm to confirm the quality and the efficiency of the suggested method, where the matching was found to be 100% between the data of the suggested method and SVM. The six properties offer a new method to build a rule-based feature extraction technique in different applications and detect any text recognition with a low computational cost.

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