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  • Open Access

    ARTICLE

    Differentially Private Support Vector Machines with Knowledge Aggregation

    Teng Wang, Yao Zhang, Jiangguo Liang, Shuai Wang, Shuanggen Liu*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3891-3907, 2024, DOI:10.32604/cmc.2024.048115

    Abstract With the widespread data collection and processing, privacy-preserving machine learning has become increasingly important in addressing privacy risks related to individuals. Support vector machine (SVM) is one of the most elementary learning models of machine learning. Privacy issues surrounding SVM classifier training have attracted increasing attention. In this paper, we investigate Differential Privacy-compliant Federated Machine Learning with Dimensionality Reduction, called FedDPDR-DPML, which greatly improves data utility while providing strong privacy guarantees. Considering in distributed learning scenarios, multiple participants usually hold unbalanced or small amounts of data. Therefore, FedDPDR-DPML enables multiple participants to collaboratively learn a global model based on weighted… More >

  • Open Access

    ARTICLE

    Agricultural Investment Project Decisions Based on an Interactive Preference Disaggregation Model Considering Inconsistency

    Xingli Wu1,{{sup}}#{{/sup}}, Huchang Liao1,{{sup}}#{{/sup}}, Shuxian Sun1, Zhengjun Wan2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3125-3146, 2024, DOI:10.32604/cmes.2023.047031

    Abstract Agricultural investment project selection is a complex multi-criteria decision-making problem, as agricultural projects are easily influenced by various risk factors, and the evaluation information provided by decision-makers usually involves uncertainty and inconsistency. Existing literature primarily employed direct preference elicitation methods to address such issues, necessitating a great cognitive effort on the part of decision-makers during evaluation, specifically, determining the weights of criteria. In this study, we propose an indirect preference elicitation method, known as a preference disaggregation method, to learn decision-maker preference models from decision examples. To enhance evaluation ease, decision-makers merely need to compare pairs of alternatives with which… More >

  • Open Access

    ARTICLE

    An Intelligent MCGDM Model in Green Suppliers Selection Using Interactional Aggregation Operators for Interval-Valued Pythagorean Fuzzy Soft Sets

    Rana Muhammad Zulqarnain1, Wen-Xiu Ma1,2,3,*, Imran Siddique4, Hijaz Ahmad5,6, Sameh Askar7

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1829-1862, 2024, DOI:10.32604/cmes.2023.030687

    Abstract Green supplier selection is an important debate in green supply chain management (GSCM), attracting global attention from scholars, especially companies and policymakers. Companies frequently search for new ideas and strategies to assist them in realizing sustainable development. Because of the speculative character of human opinions, supplier selection frequently includes unreliable data, and the interval-valued Pythagorean fuzzy soft set (IVPFSS) provides an exceptional capacity to cope with excessive fuzziness, inconsistency, and inexactness through the decision-making procedure. The main goal of this study is to come up with new operational laws for interval-valued Pythagorean fuzzy soft numbers (IVPFSNs) and create two interaction… More >

  • Open Access

    ARTICLE

    Flexible Global Aggregation and Dynamic Client Selection for Federated Learning in Internet of Vehicles

    Tariq Qayyum1, Zouheir Trabelsi1,*, Asadullah Tariq1, Muhammad Ali2, Kadhim Hayawi3, Irfan Ud Din4

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1739-1757, 2023, DOI:10.32604/cmc.2023.043684

    Abstract Federated Learning (FL) enables collaborative and privacy-preserving training of machine learning models within the Internet of Vehicles (IoV) realm. While FL effectively tackles privacy concerns, it also imposes significant resource requirements. In traditional FL, trained models are transmitted to a central server for global aggregation, typically in the cloud. This approach often leads to network congestion and bandwidth limitations when numerous devices communicate with the same server. The need for Flexible Global Aggregation and Dynamic Client Selection in FL for the IoV arises from the inherent characteristics of IoV environments. These include diverse and distributed data sources, varying data quality,… More >

  • Open Access

    ARTICLE

    A Novel Method for Determining Tourism Carrying Capacity in a Decision-Making Context Using q−Rung Orthopair Fuzzy Hypersoft Environment

    Salma Khan1, Muhammad Gulistan1, Nasreen Kausar2, Seifedine Kadry3,4,5, Jungeun Kim6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1951-1979, 2024, DOI:10.32604/cmes.2023.030896

    Abstract Tourism is a popular activity that allows individuals to escape their daily routines and explore new destinations for various reasons, including leisure, pleasure, or business. A recent study has proposed a unique mathematical concept called a q−Rung orthopair fuzzy hypersoft set (ROFHS) to enhance the formal representation of human thought processes and evaluate tourism carrying capacity. This approach can capture the imprecision and ambiguity often present in human perception. With the advanced mathematical tools in this field, the study has also incorporated the Einstein aggregation operator and score function into the ROFHS values to support multi-attribute decision-making algorithms. By implementing… More >

  • Open Access

    ARTICLE

    Linguistic Knowledge Representation in DPoS Consensus Scheme for Blockchain

    Yixia Chen1,2, Mingwei Lin1,2,*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 845-866, 2023, DOI:10.32604/cmc.2023.040970

    Abstract The consensus scheme is an essential component in the real blockchain environment. The Delegated Proof of Stake (DPoS) is a competitive consensus scheme that can decrease energy costs, promote decentralization, and increase efficiency, respectively. However, how to study the knowledge representation of the collective voting information and then select delegates is a new open problem. To ensure the fairness and effectiveness of transactions in the blockchain, in this paper, we propose a novel fine-grained knowledge representation method, which improves the DPoS scheme based on the linguistic term set (LTS) and proportional hesitant fuzzy linguistic term set (PHFLTS). To this end,… More >

  • Open Access

    ARTICLE

    Automatic Aggregation Enhanced Affinity Propagation Clustering Based on Mutually Exclusive Exemplar Processing

    Zhihong Ouyang*, Lei Xue, Feng Ding, Yongsheng Duan

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 983-1008, 2023, DOI:10.32604/cmc.2023.042222

    Abstract Affinity propagation (AP) is a widely used exemplar-based clustering approach with superior efficiency and clustering quality. Nevertheless, a common issue with AP clustering is the presence of excessive exemplars, which limits its ability to perform effective aggregation. This research aims to enable AP to automatically aggregate to produce fewer and more compact clusters, without changing the similarity matrix or customizing preference parameters, as done in existing enhanced approaches. An automatic aggregation enhanced affinity propagation (AAEAP) clustering algorithm is proposed, which combines a dependable partitioning clustering approach with AP to achieve this purpose. The partitioning clustering approach generates an additional set… More >

  • Open Access

    PROCEEDINGS

    The Impact of Aggregation Platforms on the Ride-Sourcing Market with Different Models of Companies

    Xin Zhang1,2, Gege Jiang1,2,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.3, pp. 1-5, 2023, DOI:10.32604/icces.2023.09222

    Abstract With the booming development of the ride-sourcing (RS)industry, aggregation platforms that integrate RS companies have emerged in recent years, such as Gaode and Meituan. Aggregation platforms can consolidate resources and avoid fragmentation of the market. But the emergence of aggregation platforms has also changed the market structure and brought challenges. This paper explores the impact of aggregation platforms on the market with two models of companies: customer-to-customer (C2C) companies, and business-to-customer (B2C) companies. C2C companies adjust supply and demand to maximize revenue by determining travel fares and the cut taken from the travel fares, i.e., the commission. B2C companies will… More >

  • Open Access

    ARTICLE

    Pythagorean Fuzzy Einstein Aggregation Operators with Z-Numbers: Application in Complex Decision Aid Systems

    Shahzad Noor Abbasi1, Shahzaib Ashraf1,*, M. Shazib Hameed1, Sayed M. Eldin2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2795-2844, 2023, DOI:10.32604/cmes.2023.028963

    Abstract The primary goal of this research is to determine the optimal agricultural field selection that would most effectively support manufacturing producers in manufacturing production while accounting for unpredictability and reliability in their decision-making. The PFS is known to address the levels of participation and non-participation. To begin, we introduce the novel concept of a PFZN, which is a hybrid structure of Pythagorean fuzzy sets and the ZN. The PFZN is graded in terms of membership and non-membership, as well as reliability, which provides a strong advice in real-world decision support concerns. The PFZN is a useful tool for dealing with… More >

  • Open Access

    ARTICLE

    SFSDA: Secure and Flexible Subset Data Aggregation with Fault Tolerance for Smart Grid

    Dong Chen1, Tanping Zhou1,2,3,*, Xu An Wang1,2, Zichao Song1, Yujie Ding1, Xiaoyuan Yang1,2

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2477-2497, 2023, DOI:10.32604/iasc.2023.039238

    Abstract Smart grid (SG) brings convenience to users while facing great challenges in protecting personal private data. Data aggregation plays a key role in protecting personal privacy by aggregating all personal data into a single value, preventing the leakage of personal data while ensuring its availability. Recently, a flexible subset data aggregation (FSDA) scheme based on the Paillier homomorphic encryption was first proposed by Zhang et al. Their scheme can dynamically adjust the size of each subset and obtain the aggregated data in the corresponding subset. In this paper, firstly, an efficient attack with both theorems proving and experimentative verification is… More >

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