Pub Date : 2023-09-22DOI: 10.24818/18423264/57.3.23.19
KUMAR Vineet, GUPTA Anjana, TANEJA Harish Chander
{"title":"A Novel Similarity Measure and Score Function of Pythagorean Fuzzy Sets and Their Application in Assignment Problem","authors":"KUMAR Vineet, GUPTA Anjana, TANEJA Harish Chander","doi":"10.24818/18423264/57.3.23.19","DOIUrl":"https://doi.org/10.24818/18423264/57.3.23.19","url":null,"abstract":"","PeriodicalId":51029,"journal":{"name":"Economic Computation and Economic Cybernetics Studies and Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136017152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-22DOI: 10.24818/18423264/57.3.23.09
HU Haiju, ZHU Weipeng, LI Yakun, ZHOU Jia
. A sustainable supply chain of Traditional Chinese Medicine (TCM) is vital for public health. However, for many years, TCM manufacturers have suffered from the quality cheating behaviours of their suppliers (Chinese herbal medicine providers). Aiming at managing those quality cheating behaviours and improving the potency of TCM effectively, a four-dimensional evolutionary game model composed of Chinese herbal medicine suppliers and TCM manufacturers was established, and two quality inspection methods were introduced: chemical inspection and biological assay inspection were introduced to screen unqualified and low-potency Chinese herbal medicines (CHM), respectively. The model results are obtained through the analysis of stable strategy and evolution paths, and the influence of some parameters such as the percentage of suppliers selected, rewards, and punishments on the evolutionary stable state was analysed by numerical simulation experiments in the MATLAB software. The results showed that TCM manufacturers can reach an optimal state: purchasing high-potency CHM at the lowest possible inspection costs. The government regulators and manufacturers can improve the quality of CHM by changing the above parameters.
{"title":"A Four-dimensional Evolutionary Game Analysis of Quality Cheating Behavior in Traditional Chinese Medicine Supply Chain","authors":"HU Haiju, ZHU Weipeng, LI Yakun, ZHOU Jia","doi":"10.24818/18423264/57.3.23.09","DOIUrl":"https://doi.org/10.24818/18423264/57.3.23.09","url":null,"abstract":". A sustainable supply chain of Traditional Chinese Medicine (TCM) is vital for public health. However, for many years, TCM manufacturers have suffered from the quality cheating behaviours of their suppliers (Chinese herbal medicine providers). Aiming at managing those quality cheating behaviours and improving the potency of TCM effectively, a four-dimensional evolutionary game model composed of Chinese herbal medicine suppliers and TCM manufacturers was established, and two quality inspection methods were introduced: chemical inspection and biological assay inspection were introduced to screen unqualified and low-potency Chinese herbal medicines (CHM), respectively. The model results are obtained through the analysis of stable strategy and evolution paths, and the influence of some parameters such as the percentage of suppliers selected, rewards, and punishments on the evolutionary stable state was analysed by numerical simulation experiments in the MATLAB software. The results showed that TCM manufacturers can reach an optimal state: purchasing high-potency CHM at the lowest possible inspection costs. The government regulators and manufacturers can improve the quality of CHM by changing the above parameters.","PeriodicalId":51029,"journal":{"name":"Economic Computation and Economic Cybernetics Studies and Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136017156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-22DOI: 10.24818/18423264/57.3.23.02
ZHU Dan, LI Hongchang
{"title":"Research on the Mechanism of Government Incentive Measures to Rail Transit Station Renewal based on TOD Mode – An Evolutionary Game Analysis","authors":"ZHU Dan, LI Hongchang","doi":"10.24818/18423264/57.3.23.02","DOIUrl":"https://doi.org/10.24818/18423264/57.3.23.02","url":null,"abstract":"","PeriodicalId":51029,"journal":{"name":"Economic Computation and Economic Cybernetics Studies and Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136017157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-22DOI: 10.24818/18423264/57.3.23.18
BAKIR Muhammed Rasid, BAKIRTAS Ibrahim, OLMEZ Emre
{"title":"Statistical Techniques vs. Machine Learning Models: A Comparative Analysis for Exchange Rate Forecasting in Fragile Five Countries","authors":"BAKIR Muhammed Rasid, BAKIRTAS Ibrahim, OLMEZ Emre","doi":"10.24818/18423264/57.3.23.18","DOIUrl":"https://doi.org/10.24818/18423264/57.3.23.18","url":null,"abstract":"","PeriodicalId":51029,"journal":{"name":"Economic Computation and Economic Cybernetics Studies and Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136017150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Assessment Model of Regional Sustainable Development Through the Benchmarking Analysis of the Environmental Situation from 2017 and 2021","authors":"IACOB Silvia Elena, HREBENCIUC Andrei, MOROIANU Nicolae, STOICA Georgiana Daniela, ANDREIANA Violeta-Andreea","doi":"10.24818/18423264/57.3.23.15","DOIUrl":"https://doi.org/10.24818/18423264/57.3.23.15","url":null,"abstract":"","PeriodicalId":51029,"journal":{"name":"Economic Computation and Economic Cybernetics Studies and Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136017153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-22DOI: 10.24818/18423264/57.3.23.11
CHANPA Robabeh, JAMALI Mohammad Ali Jabraeil, HATAMLOU Abdolreza, ANARI Babak
{"title":"Cluster Head Selection Algorithm on the Basis of Mass Defense of Bees in IoT","authors":"CHANPA Robabeh, JAMALI Mohammad Ali Jabraeil, HATAMLOU Abdolreza, ANARI Babak","doi":"10.24818/18423264/57.3.23.11","DOIUrl":"https://doi.org/10.24818/18423264/57.3.23.11","url":null,"abstract":"","PeriodicalId":51029,"journal":{"name":"Economic Computation and Economic Cybernetics Studies and Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136017159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-21DOI: 10.24818/18423264/57.2.23.07
Atli Ayca Hatice
. The prediction of index or stock price movements is an attractive and significant research topic for academia and the business world. In recent years, many approaches based on machine learning have been developed to create an effective prediction model. A substantial part of the articles on movement prediction focuses on predicting up-and-down movements of the stock market index and stock prices. This study focuses on four kinds of price movements and proposes a prediction scheme for the emerging multi-class classification task. The proposed approach is mainly based on pairwise classification. The experiments have been conducted on three data sets, namely, the FTSE 100, KOSPI, and S&P 500 indices, using nine technical indicators as inputs. The prediction performance of the approach is compared with the performance of five traditional techniques, multilayer perceptron, support vector machine, naive Bayes, k-nearest neighbor, and regularised multinomial regression. Experimental results based on 11 years of historical data from the FTSE 100, KOSPI, and S&P 500 indices between 2010 and 2021 demonstrate the effectiveness of the proposed pairwise classification-based scheme. The proposed scheme has achieved an accuracy of more than 84%, higher than other techniques. To our knowledge, this study is the first to include the categories presented and to predict the direction of price movements based on such pairwise classification.
{"title":"Prediction of Stock Market Index Movement Using Pairwise Classification","authors":"Atli Ayca Hatice","doi":"10.24818/18423264/57.2.23.07","DOIUrl":"https://doi.org/10.24818/18423264/57.2.23.07","url":null,"abstract":". The prediction of index or stock price movements is an attractive and significant research topic for academia and the business world. In recent years, many approaches based on machine learning have been developed to create an effective prediction model. A substantial part of the articles on movement prediction focuses on predicting up-and-down movements of the stock market index and stock prices. This study focuses on four kinds of price movements and proposes a prediction scheme for the emerging multi-class classification task. The proposed approach is mainly based on pairwise classification. The experiments have been conducted on three data sets, namely, the FTSE 100, KOSPI, and S&P 500 indices, using nine technical indicators as inputs. The prediction performance of the approach is compared with the performance of five traditional techniques, multilayer perceptron, support vector machine, naive Bayes, k-nearest neighbor, and regularised multinomial regression. Experimental results based on 11 years of historical data from the FTSE 100, KOSPI, and S&P 500 indices between 2010 and 2021 demonstrate the effectiveness of the proposed pairwise classification-based scheme. The proposed scheme has achieved an accuracy of more than 84%, higher than other techniques. To our knowledge, this study is the first to include the categories presented and to predict the direction of price movements based on such pairwise classification.","PeriodicalId":51029,"journal":{"name":"Economic Computation and Economic Cybernetics Studies and Research","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42840589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-21DOI: 10.24818/18423264/57.2.23.12
Kocak Deniz
. Nowadays, when the conflicts and crises on the Russia-Ukraine line continue, many countries condemn Russia and take various military and economic measures against Russia. This negative picture reveals the importance of the defense system that aims to provide security and resist possible attacks on countries. The country’s defense systems can be shaped by different dynamics depending on the countries’ experiences in the historical process, their national incomes, the policies they follow, and their geopolitical situations. This study aims to effectively evaluate the defense performances of the actors that may be a party in the Russia-Ukraine war. For this purpose, the 2020 data of the countries in the categories such as military, economic, demographic, innovation, and negative peace are used in the MULTIMOORA method. The results show that countries such as America, Russia, and the United Kingdom are at the top of the performance rankings, and North Macedonia, Montenegro, and Latvia are at the bottom of the performance rankings.
{"title":"Measuring Defense Performance: An International Comparison with the MULTIMOORA Method","authors":"Kocak Deniz","doi":"10.24818/18423264/57.2.23.12","DOIUrl":"https://doi.org/10.24818/18423264/57.2.23.12","url":null,"abstract":". Nowadays, when the conflicts and crises on the Russia-Ukraine line continue, many countries condemn Russia and take various military and economic measures against Russia. This negative picture reveals the importance of the defense system that aims to provide security and resist possible attacks on countries. The country’s defense systems can be shaped by different dynamics depending on the countries’ experiences in the historical process, their national incomes, the policies they follow, and their geopolitical situations. This study aims to effectively evaluate the defense performances of the actors that may be a party in the Russia-Ukraine war. For this purpose, the 2020 data of the countries in the categories such as military, economic, demographic, innovation, and negative peace are used in the MULTIMOORA method. The results show that countries such as America, Russia, and the United Kingdom are at the top of the performance rankings, and North Macedonia, Montenegro, and Latvia are at the bottom of the performance rankings.","PeriodicalId":51029,"journal":{"name":"Economic Computation and Economic Cybernetics Studies and Research","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41730057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-21DOI: 10.24818/18423264/57.2.23.17
K. Manoj, Patidar Manish, S. Narendra
. Orthogonal Frequency Division Multiplexing (OFDM) is a multi-carrier modulation technology that uses many subcarriers inside a single channel to broaden the notion of single subcarrier modulation. Because of its high-power transmission, the above approach produces out-of-band radiation. Therefore, a novel model named MIMO based enhanced OFDM communication system is introduced. In which random data bits are generated by a random data source, which is mapped using QPSK. Furthermore, to alleviate the carrier interference in MIMO-OFDM a novel Multi carrier interference mitigation method is presented. In which the Fourier, ICI estimation is done to separate the signal to time and frequency variant. Therefore, a novel Deep Frequency Time Offset estimation approach is created with two successive layers, and a Deep Neural Network (DNN) is used to estimate the residual carrier frequency offset and symbol timing offset. This reduces the time and frequency offset inaccuracy. Additionally, to alleviate out-of-band problems, a novel Low Complex Equalised demodulating approach is introduced. In which an extension windowing procedure is performed after adding CP, significantly reducing side lobe power and simplifying the process. Thus, the proposed OFDM carriers all the signal and transmits and receives with low out-of-band, carrier frequency offset in an efficient and equalised manner without any error and losses.
{"title":"Optimized MIMO Based Enhanced OFDM for Multi Carrier System with 5G Waveforms","authors":"K. Manoj, Patidar Manish, S. Narendra","doi":"10.24818/18423264/57.2.23.17","DOIUrl":"https://doi.org/10.24818/18423264/57.2.23.17","url":null,"abstract":". Orthogonal Frequency Division Multiplexing (OFDM) is a multi-carrier modulation technology that uses many subcarriers inside a single channel to broaden the notion of single subcarrier modulation. Because of its high-power transmission, the above approach produces out-of-band radiation. Therefore, a novel model named MIMO based enhanced OFDM communication system is introduced. In which random data bits are generated by a random data source, which is mapped using QPSK. Furthermore, to alleviate the carrier interference in MIMO-OFDM a novel Multi carrier interference mitigation method is presented. In which the Fourier, ICI estimation is done to separate the signal to time and frequency variant. Therefore, a novel Deep Frequency Time Offset estimation approach is created with two successive layers, and a Deep Neural Network (DNN) is used to estimate the residual carrier frequency offset and symbol timing offset. This reduces the time and frequency offset inaccuracy. Additionally, to alleviate out-of-band problems, a novel Low Complex Equalised demodulating approach is introduced. In which an extension windowing procedure is performed after adding CP, significantly reducing side lobe power and simplifying the process. Thus, the proposed OFDM carriers all the signal and transmits and receives with low out-of-band, carrier frequency offset in an efficient and equalised manner without any error and losses.","PeriodicalId":51029,"journal":{"name":"Economic Computation and Economic Cybernetics Studies and Research","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46248840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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