Decision Making Advances最新文献

Implementation of Effective Supply Chain Management Practice in the National Oil Corporation in Developing Country: An Integrated BWM-AROMAN approach 在发展中国家的国家石油公司实施有效的供应链管理实践：综合 BWM-AROMAN 方法

Decision Making Advances Pub Date : 2024-06-10 DOI: 10.31181/dma21202439

C. K. Kiptum, Mouhamed Bayane Bouraima, Badi Ibrahim, Elizabeth Abosede Oloketuyi, Opeyemi Oluyemisis Makinde, Yanjun Qiu

引用次数: 0

Multi-Attribute Decision-Making for T-Spherical Fuzzy Information Utilizing Schweizer-Sklar Prioritized Aggregation Operators for Recycled Water 利用 Schweizer-Sklar 优先级聚合运算符为 T 型非球面模糊信息做出再生水多属性决策

Decision Making Advances Pub Date : 2024-02-15 DOI: 10.31181/dma21202425

Mehwish Sarfraz

{"title":"Multi-Attribute Decision-Making for T-Spherical Fuzzy Information Utilizing Schweizer-Sklar Prioritized Aggregation Operators for Recycled Water","authors":"Mehwish Sarfraz","doi":"10.31181/dma21202425","DOIUrl":"https://doi.org/10.31181/dma21202425","url":null,"abstract":"To handle problematic and ambiguous data, Schweizer and Sklar added a parameter p in 1960, which helped to develop the theory of SS t-norm (SSTN) and t-conorm (SSTCN). The parameter p=-1.1 can be used to easily derive the information of the Hamacher and Lukasiewicz t-norms. Furthermore, prioritized aggregation operators (PAOs) choose which data will be collected into a singleton set. The main contribution of this work is the construction of new aggregation operators for T-spherical fuzzy (T-SF) information based on SS t-norm and t-conorm. Moreover, the fundamental characteristics of the operators are identified. Further, we developed MADM (Multi-Attribute Decision-Making) models and deduced several useful properties from the operators T-SFSSPA, T-SFSSWPA, T-SFSSPG, and T-SFSSWPG. Finally, using an actual case study, we were able to draw the conclusion that, in comparison to the ground-breaking and current methods to enhance the value and capability of the diagnosed operators, the proposed MADM algorithm performs noticeably better than the operators in place for resolving the water recycling problem in a way that is easy to understand.","PeriodicalId":132082,"journal":{"name":"Decision Making Advances","volume":"356 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139834490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transfer Learning Empowered Bone Fracture Detection 转移学习助力骨折检测

Decision Making Advances Pub Date : 2024-02-12 DOI: 10.31181/dma21202426

Muhammad Daniyal Baig, Hafiz Burhan ul Haq, Waseem Akram, Awais Shahzad

引用次数: 0

Analysis of Critical Success Factors of Logistics 4.0 using D-number based Pythagorean Fuzzy DEMATEL method 使用基于 D 数的毕达哥拉斯模糊 DEMATEL 法分析物流 4.0 的关键成功因素

Decision Making Advances Pub Date : 2024-02-12 DOI: 10.31181/dma21202430

B. Nila, Jagannath Roy

{"title":"Analysis of Critical Success Factors of Logistics 4.0 using D-number based Pythagorean Fuzzy DEMATEL method","authors":"B. Nila, Jagannath Roy","doi":"10.31181/dma21202430","DOIUrl":"https://doi.org/10.31181/dma21202430","url":null,"abstract":"Logistics 4.0 is a concept related to Industry 4.0, encompassing skills and notions of supply chain organization, integrating logistics with advanced technology in order to satisfy consumer demand for customized goods and services. Industry 4.0 is transforming businesses and supply chains through advanced technologies like analytics, big data, Internet of things, and cyber-physical systems, enhancing warehousing, manufacturing, and logistics. Logistics 4.0 can be regulated by properly analyzing specific Critical Success Factors using a Multi-Criteria Decision Making model in uncertain or ambiguous circumstances. Hence, it is necessary to explore the CSFs while bringing logistics 4.0 into action. These CSFs are interlinked, and this interlinkage is examined through the D-number-based Pythagorean fuzzy Decision Making Trial and Evaluation Laboratory method, which is suitable for group decision-making in incomplete and uncertain data. The proposed research paradigm incorporates the abilities of Trapezoidal Pythagorean Fuzzy Numbers for dealing with fuzziness and D-Numbers for getting an improved and further precise decision from a heterogeneous group of decision-makers using their linguistic choices. Additionally, it is adaptive and versatile in managing the intrinsic uncertainty brought on by ambiguous and subjective information.","PeriodicalId":132082,"journal":{"name":"Decision Making Advances","volume":"79 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139783615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Marine Object Detection using YOLOv4 Adapted Convolutional Neural Network 利用 YOLOv4 适配卷积神经网络进行海洋物体探测

Decision Making Advances Pub Date : 2024-02-12 DOI: 10.31181/dma21202428

Muhammad Daniyal Baig, Hafiz Burhan ul Haq

{"title":"Marine Object Detection using YOLOv4 Adapted Convolutional Neural Network","authors":"Muhammad Daniyal Baig, Hafiz Burhan ul Haq","doi":"10.31181/dma21202428","DOIUrl":"https://doi.org/10.31181/dma21202428","url":null,"abstract":"This research presents an innovative application of the YOLOv4 object detection model for the identification and classification of marine objects within a dataset encompassing seven distinct classes. The study focuses on enhancing the robustness and accuracy of object detection in challenging marine environments, leveraging the unique capabilities of YOLOv4. Pre-processing steps involve resizing raw images, applying data augmentations, and normalizing pixel values to ensure optimal model training. Specifically tailored for underwater scenarios, additional color space transformations address variations in lighting conditions. The model is trained to detect marine objects such as fish, corals, and underwater structures, contributing to advancements in underwater exploration, environmental monitoring, and marine resource management. Experimental results demonstrate the effectiveness of the proposed approach, showcasing YOLOv4's ability to accurately identify and classify marine objects across the specified seven classes. This research not only expands the applicability of YOLOv4 in the marine domain but also provides valuable insights for the development of intelligent systems for underwater object detection.","PeriodicalId":132082,"journal":{"name":"Decision Making Advances","volume":"40 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139784078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of Critical Success Factors of Logistics 4.0 using D-number based Pythagorean Fuzzy DEMATEL method 使用基于 D 数的毕达哥拉斯模糊 DEMATEL 法分析物流 4.0 的关键成功因素

Decision Making Advances Pub Date : 2024-02-12 DOI: 10.31181/dma21202430

B. Nila, Jagannath Roy

{"title":"Analysis of Critical Success Factors of Logistics 4.0 using D-number based Pythagorean Fuzzy DEMATEL method","authors":"B. Nila, Jagannath Roy","doi":"10.31181/dma21202430","DOIUrl":"https://doi.org/10.31181/dma21202430","url":null,"abstract":"Logistics 4.0 is a concept related to Industry 4.0, encompassing skills and notions of supply chain organization, integrating logistics with advanced technology in order to satisfy consumer demand for customized goods and services. Industry 4.0 is transforming businesses and supply chains through advanced technologies like analytics, big data, Internet of things, and cyber-physical systems, enhancing warehousing, manufacturing, and logistics. Logistics 4.0 can be regulated by properly analyzing specific Critical Success Factors using a Multi-Criteria Decision Making model in uncertain or ambiguous circumstances. Hence, it is necessary to explore the CSFs while bringing logistics 4.0 into action. These CSFs are interlinked, and this interlinkage is examined through the D-number-based Pythagorean fuzzy Decision Making Trial and Evaluation Laboratory method, which is suitable for group decision-making in incomplete and uncertain data. The proposed research paradigm incorporates the abilities of Trapezoidal Pythagorean Fuzzy Numbers for dealing with fuzziness and D-Numbers for getting an improved and further precise decision from a heterogeneous group of decision-makers using their linguistic choices. Additionally, it is adaptive and versatile in managing the intrinsic uncertainty brought on by ambiguous and subjective information.","PeriodicalId":132082,"journal":{"name":"Decision Making Advances","volume":"70 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139843443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Marine Object Detection using YOLOv4 Adapted Convolutional Neural Network 利用 YOLOv4 适配卷积神经网络进行海洋物体探测

Decision Making Advances Pub Date : 2024-02-12 DOI: 10.31181/dma21202428

Muhammad Daniyal Baig, Hafiz Burhan ul Haq

{"title":"Marine Object Detection using YOLOv4 Adapted Convolutional Neural Network","authors":"Muhammad Daniyal Baig, Hafiz Burhan ul Haq","doi":"10.31181/dma21202428","DOIUrl":"https://doi.org/10.31181/dma21202428","url":null,"abstract":"This research presents an innovative application of the YOLOv4 object detection model for the identification and classification of marine objects within a dataset encompassing seven distinct classes. The study focuses on enhancing the robustness and accuracy of object detection in challenging marine environments, leveraging the unique capabilities of YOLOv4. Pre-processing steps involve resizing raw images, applying data augmentations, and normalizing pixel values to ensure optimal model training. Specifically tailored for underwater scenarios, additional color space transformations address variations in lighting conditions. The model is trained to detect marine objects such as fish, corals, and underwater structures, contributing to advancements in underwater exploration, environmental monitoring, and marine resource management. Experimental results demonstrate the effectiveness of the proposed approach, showcasing YOLOv4's ability to accurately identify and classify marine objects across the specified seven classes. This research not only expands the applicability of YOLOv4 in the marine domain but also provides valuable insights for the development of intelligent systems for underwater object detection.","PeriodicalId":132082,"journal":{"name":"Decision Making Advances","volume":"73 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139843992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sustainable Delivery Model Selection using AROMAN Approach 使用 AROMAN 方法选择可持续交付模式

Decision Making Advances Pub Date : 2024-02-12 DOI: 10.31181/dma21202429

M. Dobrodolac, S. Bošković, S. Jovčić, D. Lazarević

引用次数: 0

Sustainable Delivery Model Selection using AROMAN Approach 使用 AROMAN 方法选择可持续交付模式

Decision Making Advances Pub Date : 2024-02-12 DOI: 10.31181/dma21202429

M. Dobrodolac, S. Bošković, S. Jovčić, D. Lazarević

引用次数: 0

A Novel Hybrid Decision Making Framework for Comparing Market Performance of Metaverse Crypto Assets 一种比较虚拟世界加密资产市场表现的新型混合决策框架

Decision Making Advances Pub Date : 2023-12-15 DOI: 10.31181/dma1120238

D. Pamučar, S. Biswas

{"title":"A Novel Hybrid Decision Making Framework for Comparing Market Performance of Metaverse Crypto Assets","authors":"D. Pamučar, S. Biswas","doi":"10.31181/dma1120238","DOIUrl":"https://doi.org/10.31181/dma1120238","url":null,"abstract":"With proliferation of smartphone usage and rapidly increasing internet access, the financial sectors has been witnessing a transformational change in the last few years, leading to the digital economy. The cryptocurrencies (digital assets) and the metaverse assets that use blockchain technology extensively have emerged as an attractive investment option to the investors. The review of the extant literature shows a scantiness of research in comparing the performance of metaverse crypto assets based on market indicators. In this regard, the current work aims to provide a framework to compare the metaverse crypto assets based on their market performance. To this end, the present paper proposes a novel hybrid framework such as Logarithmic Percentage Change driven Compromise Solution based Appraisal (LOPCCSA). To compare the alternatives the variables like return, momentum of the daily closing price, market capitalization, trading volume and risk (in terms of historical volatility realized over the study period 2022). From the result we observe that the momentum of the closing prices and volatility of the price movements hold the higher importance as derived by calculation of objective weights. Theta Network (A10) comes out as the top performer ahead of ApeCoin (A1) or MANA (A3) or Internet Computer (A6). The comparison of the results obtained by LOPCCSA with other MCDM models show considerable consistency. The sensitivity analysis indicates that LOPCCSA provides a stable solution. The present paper is a distinct attempt that shall attract the decision makers and investors to carry out a deeper and comprehensive analysis of the metaverse crypto assets in near future.","PeriodicalId":132082,"journal":{"name":"Decision Making Advances","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121641987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11