Expert Systems最新文献

{"title":"Addressing Vagueness and Uncertainty in the Banking Industry: Combining Fuzzy Modulatory Data Envelopment Analysis and Fuzzy Multivariate Regression","authors":"Peter Wanke,&nbsp;Yong Tan,&nbsp;Barnabé Walheer","doi":"10.1111/exsy.70249","DOIUrl":"10.1111/exsy.70249","url":null,"abstract":"<div>\u0000 \u0000 <p>This study develops a novel two-stage framework to evaluate financial health, distress and liquidity traps in the banking industry by integrating a Fuzzy Modulatory Data Envelopment Analysis model with a Fuzzy Multivariate Lognormal Regression. The methodology incorporates fuzzy set theory with alpha-cuts to capture vagueness and uncertainty in inputs, outputs and intermediate variables, addressing inherent data imprecision in financial systems. An empirical analysis of 93 Chinese banks (2014–2023) reveals key drivers of inefficiency, including labour costs, capital adequacy and market concentration, while highlighting the moderating effects of competition and regulatory measures. Results demonstrate improved efficiency trends and convergence in operational practices, influenced by regulatory compliance and macroeconomic policies. The framework further identifies contextual factors—such as the Herfindahl–Hirschman Index and CAMELS ratings—impacting inefficiencies under varying levels of uncertainty, offering a comprehensive risk management and policy evaluation tool. This research contributes to operational research by bridging gaps in banking efficiency analysis and providing actionable insights for enhancing financial stability and resilience under uncertain market conditions.</p>\u0000 </div>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"43 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Addressing Vagueness and Uncertainty in the Banking Industry: Combining Fuzzy Modulatory Data Envelopment Analysis and Fuzzy Multivariate Regression","authors":"Peter Wanke,&nbsp;Yong Tan,&nbsp;Barnabé Walheer","doi":"10.1111/exsy.70249","DOIUrl":"https://doi.org/10.1111/exsy.70249","url":null,"abstract":"<div>\u0000 \u0000 <p>This study develops a novel two-stage framework to evaluate financial health, distress and liquidity traps in the banking industry by integrating a Fuzzy Modulatory Data Envelopment Analysis model with a Fuzzy Multivariate Lognormal Regression. The methodology incorporates fuzzy set theory with alpha-cuts to capture vagueness and uncertainty in inputs, outputs and intermediate variables, addressing inherent data imprecision in financial systems. An empirical analysis of 93 Chinese banks (2014–2023) reveals key drivers of inefficiency, including labour costs, capital adequacy and market concentration, while highlighting the moderating effects of competition and regulatory measures. Results demonstrate improved efficiency trends and convergence in operational practices, influenced by regulatory compliance and macroeconomic policies. The framework further identifies contextual factors—such as the Herfindahl–Hirschman Index and CAMELS ratings—impacting inefficiencies under varying levels of uncertainty, offering a comprehensive risk management and policy evaluation tool. This research contributes to operational research by bridging gaps in banking efficiency analysis and providing actionable insights for enhancing financial stability and resilience under uncertain market conditions.</p>\u0000 </div>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"43 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on the Game Theory of Enterprise Information Security Investment Considering Information Complementarity","authors":"Cuiyou Yao,&nbsp;Lin Yu,&nbsp;Dongpu Fu,&nbsp;Yanhong Yang,&nbsp;Haiqing Cao,&nbsp;Fulei Shi","doi":"10.1111/exsy.70253","DOIUrl":"10.1111/exsy.70253","url":null,"abstract":"<div>\u0000 \u0000 <p>The vigorous development of Internet information technology has brought a lot of convenience and fun to people's lives. However, in the modern information world, the problem of information security has always existed. Given the prevalence of information security problems and their consequences, enterprises often invest in information security technologies to strengthen their information systems. However, the security vulnerabilities of information systems cannot be eliminated, so the choice of investment strategies by enterprises is of great significance. Based on the evolutionary game method, this study analyses, from a microscopic perspective, the investment strategy selection process of enterprises when there are security vulnerabilities in information system in the context of the complementarity of information assets between enterprises, and simulates the impact of enterprises' initial investment intention and potential losses as well as breach probabilities and cost differentials on the evolutionary outcomes. The research shows that an enterprise is more willing to choose an investment strategy that minimises the sum of investment costs and expected losses. The higher the enterprise's initial high investment intention or potential losses, the more likely it is to choose a high investment strategy, whilst its partner enterprise is less likely to choose a high investment strategy. In addition, when security investments effectively reduce breach probabilities, enterprises are more inclined to adopt high-investment strategies, whilst higher hacker operational costs can help alleviate enterprises' security investment pressure.</p>\u0000 </div>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"43 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on the Game Theory of Enterprise Information Security Investment Considering Information Complementarity","authors":"Cuiyou Yao,&nbsp;Lin Yu,&nbsp;Dongpu Fu,&nbsp;Yanhong Yang,&nbsp;Haiqing Cao,&nbsp;Fulei Shi","doi":"10.1111/exsy.70253","DOIUrl":"10.1111/exsy.70253","url":null,"abstract":"<div>\u0000 \u0000 <p>The vigorous development of Internet information technology has brought a lot of convenience and fun to people's lives. However, in the modern information world, the problem of information security has always existed. Given the prevalence of information security problems and their consequences, enterprises often invest in information security technologies to strengthen their information systems. However, the security vulnerabilities of information systems cannot be eliminated, so the choice of investment strategies by enterprises is of great significance. Based on the evolutionary game method, this study analyses, from a microscopic perspective, the investment strategy selection process of enterprises when there are security vulnerabilities in information system in the context of the complementarity of information assets between enterprises, and simulates the impact of enterprises' initial investment intention and potential losses as well as breach probabilities and cost differentials on the evolutionary outcomes. The research shows that an enterprise is more willing to choose an investment strategy that minimises the sum of investment costs and expected losses. The higher the enterprise's initial high investment intention or potential losses, the more likely it is to choose a high investment strategy, whilst its partner enterprise is less likely to choose a high investment strategy. In addition, when security investments effectively reduce breach probabilities, enterprises are more inclined to adopt high-investment strategies, whilst higher hacker operational costs can help alleviate enterprises' security investment pressure.</p>\u0000 </div>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"43 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ChatGPT Across Domains: A Systematic Review of Applications, Evaluation Approaches, and Open Challenges","authors":"Shirin Abbasi,&nbsp;Amir Masoud Rahmani","doi":"10.1111/exsy.70244","DOIUrl":"https://doi.org/10.1111/exsy.70244","url":null,"abstract":"<div>\u0000 \u0000 <p>In recent years, there has been a rise in the use of ChatGPT for education, healthcare, smart cities and emerging technologies. However, no available studies or reviews have provided a consistent and reliable depiction of the situation regarding its usage and evaluation. The reporting of datasets, evaluation indicators, factors influencing performance and conditions of deployment has also varied from study to study. This fragmented state of affairs seriously inhibits attempts to assess ChatGPT's capabilities and limitations and thus improve the design of future versions. Earlier reviews were often conducted in a way pertaining to a single area or were mainly descriptive, with less emphasis on methodological evaluation and issues in deployment and ethics. To fill this void, we undertook a systematic review, according to PRISMA guidelines, limiting our searches to English-language journal articles published during 2021–2025 by reputable publishers. Such studies focused directly on GPT models, provided assessment conditions and were cited extensively as preprints, while the exclusion criteria encompassed poorly linked studies, those not in English and studies employing ChatGPT as an adjunct. An analysis of these studies revealed that the vast majority of research has taken place in the area of education (32%) and health (28%). The review revealed significant variation in assessment accuracy across domains, frequent challenges with doubtful sensitivity, unpredictable and rapid changes and risks associated with specific domains that impact reliability and safety. This study's primary contribution is an effort to develop an integrated analytical framework that puts together these interdisciplinary results in a streamlined manner for interpreting the capabilities and limitations of ChatGPT. Because of the methodological heterogeneity of existing studies, the results can be viewed as qualitative trends instead of standard quantitative evidence. The results thereby accentuate the need for consistent criteria, domain-informed evaluation practices and stronger methodological reporting to underpin a more reliable deployment of ChatGPT-based systems.</p>\u0000 </div>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"43 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147585220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive Region-Aware Compression for Healthcare Applications in O-RAN","authors":"Omar Osman,&nbsp;Ahmed Badawy,&nbsp;Saeed Salem","doi":"10.1111/exsy.70246","DOIUrl":"10.1111/exsy.70246","url":null,"abstract":"<div>\u0000 \u0000 <p>Open Radio Access Network (O-RAN) fronthaul links face stringent bandwidth, latency, and computational constraints, which become particularly critical when transmitting high-resolution medical images. This paper proposes an adaptive region-aware image compression framework for healthcare imaging over O-RAN that reduces fronthaul load while preserving diagnostically relevant information. Each image is partitioned into Region-of-Interest (ROI) and Non-ROI areas and compressed using independent quantisation parameters. An optimisation model is formulated to minimise transmitted data size subject to ROI and Non-ROI quality constraints, end-to-end latency bounds and computational limits at O-RAN nodes. The framework is evaluated using two medical imaging datasets (chest X-rays and bone fracture X-rays), where empirical rate–distortion and quality models are derived and validated. Results demonstrate substantial fronthaul bandwidth reduction—achieving compression ratios up to 416:1—while maintaining ROI quality and diagnostic accuracy above 97%. These findings highlight the effectiveness of region-aware optimisation for bandwidth-efficient healthcare imaging in O-RAN environments.</p>\u0000 </div>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"43 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147579845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive Region-Aware Compression for Healthcare Applications in O-RAN","authors":"Omar Osman,&nbsp;Ahmed Badawy,&nbsp;Saeed Salem","doi":"10.1111/exsy.70246","DOIUrl":"https://doi.org/10.1111/exsy.70246","url":null,"abstract":"<div>\u0000 \u0000 <p>Open Radio Access Network (O-RAN) fronthaul links face stringent bandwidth, latency, and computational constraints, which become particularly critical when transmitting high-resolution medical images. This paper proposes an adaptive region-aware image compression framework for healthcare imaging over O-RAN that reduces fronthaul load while preserving diagnostically relevant information. Each image is partitioned into Region-of-Interest (ROI) and Non-ROI areas and compressed using independent quantisation parameters. An optimisation model is formulated to minimise transmitted data size subject to ROI and Non-ROI quality constraints, end-to-end latency bounds and computational limits at O-RAN nodes. The framework is evaluated using two medical imaging datasets (chest X-rays and bone fracture X-rays), where empirical rate–distortion and quality models are derived and validated. Results demonstrate substantial fronthaul bandwidth reduction—achieving compression ratios up to 416:1—while maintaining ROI quality and diagnostic accuracy above 97%. These findings highlight the effectiveness of region-aware optimisation for bandwidth-efficient healthcare imaging in O-RAN environments.</p>\u0000 </div>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"43 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147579846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ChatGPT Across Domains: A Systematic Review of Applications, Evaluation Approaches, and Open Challenges","authors":"Shirin Abbasi,&nbsp;Amir Masoud Rahmani","doi":"10.1111/exsy.70244","DOIUrl":"10.1111/exsy.70244","url":null,"abstract":"<div>\u0000 \u0000 <p>In recent years, there has been a rise in the use of ChatGPT for education, healthcare, smart cities and emerging technologies. However, no available studies or reviews have provided a consistent and reliable depiction of the situation regarding its usage and evaluation. The reporting of datasets, evaluation indicators, factors influencing performance and conditions of deployment has also varied from study to study. This fragmented state of affairs seriously inhibits attempts to assess ChatGPT's capabilities and limitations and thus improve the design of future versions. Earlier reviews were often conducted in a way pertaining to a single area or were mainly descriptive, with less emphasis on methodological evaluation and issues in deployment and ethics. To fill this void, we undertook a systematic review, according to PRISMA guidelines, limiting our searches to English-language journal articles published during 2021–2025 by reputable publishers. Such studies focused directly on GPT models, provided assessment conditions and were cited extensively as preprints, while the exclusion criteria encompassed poorly linked studies, those not in English and studies employing ChatGPT as an adjunct. An analysis of these studies revealed that the vast majority of research has taken place in the area of education (32%) and health (28%). The review revealed significant variation in assessment accuracy across domains, frequent challenges with doubtful sensitivity, unpredictable and rapid changes and risks associated with specific domains that impact reliability and safety. This study's primary contribution is an effort to develop an integrated analytical framework that puts together these interdisciplinary results in a streamlined manner for interpreting the capabilities and limitations of ChatGPT. Because of the methodological heterogeneity of existing studies, the results can be viewed as qualitative trends instead of standard quantitative evidence. The results thereby accentuate the need for consistent criteria, domain-informed evaluation practices and stronger methodological reporting to underpin a more reliable deployment of ChatGPT-based systems.</p>\u0000 </div>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"43 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147585271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decision-Oriented Renewable Scenario Generation Based on Multi-Scale Decomposition and WGAN-GP","authors":"Hao Hong,&nbsp;Bo Wang,&nbsp;Zhihang Yu,&nbsp;Jingshi Cui,&nbsp;Junzo Watada","doi":"10.1111/exsy.70241","DOIUrl":"10.1111/exsy.70241","url":null,"abstract":"<div>\u0000 \u0000 <p>Nowadays, with the growing penetration of renewable generation, economic dispatch is increasingly important in short-term power system operation. In this paper, a deep renewable scenario generation model combining Multi-Scale Decomposition mixer and Wasserstein Generative Adversarial Network with Gradient Penalty is proposed to achieve novel decision-oriented forecasting, thus realizing effective characterization of renewable temporal dynamics and economic performance. From the perspective of wind and solar generation, the validity of the proposed method is demonstrated on a real-world dataset with power station at regional level. Experimental results confirm the superiority of model performance through statistical indicators and power system scheduling test, compared with a number of scenario generation and time series forecasting benchmarks.</p>\u0000 </div>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"43 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147584974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EMGC: An Efficient Unsupervised Person Re-Identification Method Based on Multigrained Complementary Features","authors":"Quanbo Yuan,&nbsp;Jiamu Cheng,&nbsp;Xu Liu,&nbsp;Wenguang Qian,&nbsp;Huijuan Wang,&nbsp;Pengzhi Tian,&nbsp;Shuai Shi,&nbsp;Jianhua Wang,&nbsp;Aoxiang Song","doi":"10.1111/exsy.70239","DOIUrl":"10.1111/exsy.70239","url":null,"abstract":"<div>\u0000 \u0000 <p>Unsupervised person re-identification (Re-ID) aims to learn discriminative features from unlabelled data using pseudo-labels for pedestrian retrieval. However, existing methods fail to fully leverage fine-grained clues from multigranularity features when optimising pseudo-labels, which limits their performance. To address this issue, this paper proposes an Efficient Multigranularity Complementary feature-based unsupervised person Re-ID method (EMGC), which consists of two core modules: a Multigranularity Token Propagation module (MGTP) and a Complementary Feature Label Optimisation module (CFLO). The MGTP is built upon an improved Vision Transformer (ViT) and enhances feature representation capability while reducing computational complexity through a Multigranularity Architecture (MGA) and an Efficient Token Propagation strategy (ETP). Specifically, MGA captures both global and local features, while ETP reduces redundancy and improves computational efficiency via dynamic token selection. The CFLO introduces a Global and Partial Feature Complementary Pseudo-Label Optimisation framework (GPFC-PLO), which leverages fine-grained information from local features to improve pseudo-label quality, mitigate noise interference and enhance robustness. Extensive experiments on three person Re-ID datasets demonstrate the effectiveness of EMGC. The results show that it outperforms current state-of-the-art unsupervised methods in both performance and inference speed, significantly narrowing the performance gap with supervised approaches.</p>\u0000 </div>","PeriodicalId":51053,"journal":{"name":"Expert Systems","volume":"43 5","pages":""},"PeriodicalIF":2.3,"publicationDate":"2026-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147579729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}