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Platform Employment Governance:A Dual-Dimensional Approach Through Labor Law and Algorithmic Regulation 认领 引用
1
作者 Li Wanjing Zhang Qun 《Contemporary Social Sciences》 2026年第3期115-135,共21页
Platform employment relies on algorithmic management for task allocation,dynamic pricing,and behavioral monitoring,thereby exposing platform workers to unstable earnings,excessive labor intensity,and occupational safe... Platform employment relies on algorithmic management for task allocation,dynamic pricing,and behavioral monitoring,thereby exposing platform workers to unstable earnings,excessive labor intensity,and occupational safety risks.In addressing the labor risks associated with platform employment,both existing labor law and algorithmic regulation exhibit significant limitations.A complementary governance framework that combines the respective strengths of labor law and algorithmic regulation can therefore be developed under the guiding principles of procedural justice and substantive justice,thereby establishing a dual-dimensional governance model for platform employment.At the substantive level,the bottom-line protections provided by labor standards can be combined with the technical advantages of algorithmic regulation to achieve bottom-line labor protections through substantive code review aimed at limiting algorithmic power.At the procedural level,the democratic advantages of collective bargaining can be combined with the organizational advantages of algorithmic regulation to balance labor protection and flexibility in platform employment through worker autonomy and algorithmic procedural control. 展开更多
关键词 platform employment algorithmic management labor law algorithmic regulation worker protection
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On the impact of algorithmic management on the determination of personal subordination 认领 引用
2
作者 Qi'nan Cui 《Advances in Social Behavior Research》 2026年第7期116-123,共8页
In platform-based employment,algorithmic management is embedded in the labor process through mechanisms such as order dispatch,pricing,evaluation,rewards and punishments,which poses interpretive pressure on the tradit... In platform-based employment,algorithmic management is embedded in the labor process through mechanisms such as order dispatch,pricing,evaluation,rewards and punishments,which poses interpretive pressure on the traditional determination of personal subordination centered on explicit command,fixed workplace and direct management.Starting from the traditional judgment logic of personal subordination and combining the theory of Weisungsrecht(right of instruction)in German law,this paper points out that algorithmic management does not eliminate personal subordination,but reconstructs the exercise form of the right of instruction in a technical and depersonalized manner.The determination of personal subordination in platform-based employment should shift from the identification of specific instructions to the investigation of structural domination and real autonomy,and take traditional elements such as working hours,workplace and organizational integration as supplementary or corrective factors to enhance the operability of labor relationship determination. 展开更多
关键词 algorithmic management personal subordination right of instruction labor relationship platformbased employment
Algorithmically Enhanced Data-Driven Prediction of Shear Strength for Concrete-Filled Steel Tubes 认领 引用
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作者 Shengkang Zhang Yong Jin +5 位作者 Soon Poh Yap Haoyun Fan Shiyuan Li Ahmed El-Shafie Zainah Ibrahim Amr El-Dieb 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第1期374-398,共25页
Concrete-filled steel tubes(CFST)are widely utilized in civil engineering due to their superior load-bearing capacity,ductility,and seismic resistance.However,existing design codes,such as AISC and Eurocode 4,tend to ... Concrete-filled steel tubes(CFST)are widely utilized in civil engineering due to their superior load-bearing capacity,ductility,and seismic resistance.However,existing design codes,such as AISC and Eurocode 4,tend to be excessively conservative as they fail to account for the composite action between the steel tube and the concrete core.To address this limitation,this study proposes a hybrid model that integrates XGBoost with the Pied Kingfisher Optimizer(PKO),a nature-inspired algorithm,to enhance the accuracy of shear strength prediction for CFST columns.Additionally,quantile regression is employed to construct prediction intervals for the ultimate shear force,while the Asymmetric Squared Error Loss(ASEL)function is incorporated to mitigate overestimation errors.The computational results demonstrate that the PKO-XGBoost model delivers superior predictive accuracy,achieving a Mean Absolute Percentage Error(MAPE)of 4.431%and R2 of 0.9925 on the test set.Furthermore,the ASEL-PKO-XGBoost model substantially reduces overestimation errors to 28.26%,with negligible impact on predictive performance.Additionally,based on the Genetic Algorithm(GA)and existing equation models,a strength equation model is developed,achieving markedly higher accuracy than existing models(R2=0.934).Lastly,web-based Graphical User Interfaces(GUIs)were developed to enable real-time prediction. 展开更多
关键词 Asymmetric squared error loss genetic algorithm machine learning pied kingfisher optimizer quantile regression
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Algorithmic opacity and employees’knowledge hiding:medication by job insecurity and moderation by employee-AI collaboration 认领 引用
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作者 Chunhong Guo Huifang Liu Jingfu Guo 《Journal of Psychology in Africa》 2025年第3期411-418,共8页
We explored the effects of algorithmic opacity on employees’playing dumb and evasive hiding rather than rationalized hiding.We examined the mediating role of job insecurity and the moderating role of employee-AI coll... We explored the effects of algorithmic opacity on employees’playing dumb and evasive hiding rather than rationalized hiding.We examined the mediating role of job insecurity and the moderating role of employee-AI collaboration.Participants were 421 full-time employees(female=46.32%,junior employees=31.83%)from a variety of organizations and industries that interact with AI.Employees filled out data on algorithm opacity,job insecurity,knowledge hiding,employee-AI collaboration,and control variables.The results of the structural equation modeling indicated that algorithm opacity exacerbated employees’job insecurity,and job insecurity mediated between algorithm opacity and playing dumb and evasive hiding rather than rationalized hiding.The relationship between algorithmic opacity and playing dumb and evasive hiding was more positive when the level of employee-AI collaboration was higher.These findings suggest that employee-AI collaboration reinforces the indirect relationship between algorithmic opacity and playing dumb and evasive hiding.Our study contributes to research on human and AI collaboration by exploring the dark side of employee-AI collaboration. 展开更多
关键词 algorithmic opacity job insecurity knowledge hiding employee-AI collaboration
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Non-Neural 3D Nasal Reconstruction:A Sparse Landmark Algorithmic Approach for Medical Applications 认领 引用 被引量：1
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作者 Nguyen Khac Toan Ho Nguyen Anh Tuan Nguyen Truong Thinh 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第5期1273-1295,共23页
This paper presents a novel method for reconstructing a highly accurate 3D nose model of the human from 2D images and pre-marked landmarks based on algorithmic methods.The study focuses on the reconstruction of a 3D n... This paper presents a novel method for reconstructing a highly accurate 3D nose model of the human from 2D images and pre-marked landmarks based on algorithmic methods.The study focuses on the reconstruction of a 3D nose model tailored for applications in healthcare and cosmetic surgery.The approach leverages advanced image processing techniques,3D Morphable Models(3DMM),and deformation techniques to overcome the limita-tions of deep learning models,particularly addressing the interpretability issues commonly encountered in medical applications.The proposed method estimates the 3D coordinates of landmark points using a 3D structure estimation algorithm.Sub-landmarks are extracted through image processing techniques and interpolation.The initial surface is generated using a 3DMM,though its accuracy remains limited.To enhance precision,deformation techniques are applied,utilizing the coordinates of 76 identified landmarks and sub-landmarks.The resulting 3D nose model is constructed based on algorithmic methods and pre-marked landmarks.Evaluation of the 3D model is conducted by comparing landmark distances and shape similarity with expert-determined ground truth on 30 Vietnamese volunteers aged 18 to 47,all of whom were either preparing for or required nasal surgery.Experimental results demonstrate a strong agreement between the reconstructed 3D model and the ground truth.The method achieved a mean landmark distance error of 0.631 mm and a shape error of 1.738 mm,demonstrating its potential for medical applications. 展开更多
关键词 Nose reconstruction 3D reconstruction medical applications algorithmic reconstruction enhanced 3D model
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Algorithmic crypto trading using information‑driven bars,triple barrier labeling and deep learning 认领 引用
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作者 Przemysław Grądzki Piotr Wojcik Stefan Lessmann 《Financial Innovation》 2025年第1期3979-4021,共43页
This paper investigates the optimization of data sampling and target labeling techniques to enhance algorithmic trading strategies in cryptocurrency markets,focusing on Bitcoin(BTC)and Ethereum(ETH).Traditional data s... This paper investigates the optimization of data sampling and target labeling techniques to enhance algorithmic trading strategies in cryptocurrency markets,focusing on Bitcoin(BTC)and Ethereum(ETH).Traditional data sampling methods,such as time bars,often fail to capture the nuances of the continuously active and highly volatile cryptocurrency market and force traders to wait for arbitrary points in time.To address this,we propose an alternative approach using information-driven sampling methods,including the CUSUM filter,range bars,volume bars,and dollar bars,and evaluate their performance using tick-level data from January 2018 to June 2023.Additionally,we introduce the Triple Barrier method for target labeling,which offers a solution tailored for algorithmic trading as opposed to the widely used next-bar prediction.We empirically assess the effectiveness of these data sampling and labeling methods to craft profitable trading strategies.The results demonstrate that the innovative combination of CUSUM-filtered data with Triple Barrier labeling outperforms traditional time bars and next-bar prediction,achieving consistently positive trading performance even after accounting for transaction costs.Moreover,our system enables making trading decisions at any point in time on the basis of market conditions,providing an advantage over traditional methods that rely on fixed time intervals.Furthermore,the paper contributes to the ongoing debate on the applicability of Transformer models to time series classification in the context of algorithmic trading by evaluating various Transformer architectures—including the vanilla Transformer encoder,FEDformer,and Autoformer—alongside other deep learning architectures and classical machine learning models,revealing insights into their relative performance. 展开更多
关键词 Cryptocurrencies Algorithmic trading Deep learning Information-driven bars Triple barrier method
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Large Language Models for Effective Detection of Algorithmically Generated Domains:A Comprehensive Review 认领 引用 被引量：1
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作者 Hamed Alqahtani Gulshan Kumar 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第8期1439-1479,共41页
Domain Generation Algorithms(DGAs)continue to pose a significant threat inmodernmalware infrastructures by enabling resilient and evasive communication with Command and Control(C&C)servers.Traditional detection me... Domain Generation Algorithms(DGAs)continue to pose a significant threat inmodernmalware infrastructures by enabling resilient and evasive communication with Command and Control(C&C)servers.Traditional detection methods-rooted in statistical heuristics,feature engineering,and shallow machine learning-struggle to adapt to the increasing sophistication,linguistic mimicry,and adversarial variability of DGA variants.The emergence of Large Language Models(LLMs)marks a transformative shift in this landscape.Leveraging deep contextual understanding,semantic generalization,and few-shot learning capabilities,LLMs such as BERT,GPT,and T5 have shown promising results in detecting both character-based and dictionary-based DGAs,including previously unseen(zeroday)variants.This paper provides a comprehensive and critical review of LLM-driven DGA detection,introducing a structured taxonomy of LLM architectures,evaluating the linguistic and behavioral properties of benchmark datasets,and comparing recent detection frameworks across accuracy,latency,robustness,and multilingual performance.We also highlight key limitations,including challenges in adversarial resilience,model interpretability,deployment scalability,and privacy risks.To address these gaps,we present a forward-looking research roadmap encompassing adversarial training,model compression,cross-lingual benchmarking,and real-time integration with SIEM/SOAR platforms.This survey aims to serve as a foundational resource for advancing the development of scalable,explainable,and operationally viable LLM-based DGA detection systems. 展开更多
关键词 Adversarial domains cyber threat detection domain generation algorithms large language models machine learning security
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Regulating Algorithmic Online Manipulation in the Digital Market-Responses of the EU and China 认领 引用 被引量：1
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作者 Gu Chenhao Wu Qian 《科技与法律（中英文）》 CSSCI 2025年第2期138-148,共11页
The original intention of the algorithmic recommender system is to grapple with the negative impacts caused by information overload,but the system also can be used as"hypernudge",a new form of online manipul... The original intention of the algorithmic recommender system is to grapple with the negative impacts caused by information overload,but the system also can be used as"hypernudge",a new form of online manipulation,to inten⁃tionally exploit people's cognitive and decision-making gaps to influence their decisions in practice,which is particu⁃larly detrimental to the sustainable development of the digital market.Limiting harmful algorithmic online manipula⁃tion in digital markets has become a challenging task.Globally,both the EU and China have responded to this issue,and the differences between them are so evident that their governance measures can serve as the typical case.The EU focuses on improving citizens'digital literacy and their ability to integrate into digital social life to independently ad⁃dress this issue,and expects to address harmful manipulation behavior through binding and applicable hard law,which is part of the digital strategy.By comparison,although there exist certain legal norms that have made relevant stipula⁃tions on manipulation issues,China continues to issue specific departmental regulations to regulate algorithmic recom⁃mender services,and pays more attention to addressing collective harm caused by algorithmic online manipulation through a multiple co-governance approach led by the government or industry associations to implement supervision. 展开更多
关键词 algorithm manipulation digital market the EU China
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Algorithmic Empathy:Reconstructing Mainstream Media Communication Logic Through AI-Driven Technology for Precision Emotional Matching and Enhanced Communication Efficiency 认领 引用
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作者 XIAO Shufang 《Journalism and Mass Communication》 2025年第3期189-195,共7页
This study investigates how artificial intelligence(AI)algorithms enable mainstream media to achieve precise emotional matching and improve communication efficiency through reconstructed communication logic.As digital... This study investigates how artificial intelligence(AI)algorithms enable mainstream media to achieve precise emotional matching and improve communication efficiency through reconstructed communication logic.As digital intelligence technology rapidly evolves,mainstream media organizations are increasingly leveraging AI-driven empathy algorithms to enhance audience engagement and optimize content delivery.This research employs a mixed-methods approach,combining quantitative analysis of algorithmic performance metrics with qualitative examination of media communication patterns.Through systematic review of 150 academic papers and analysis of data from 12 major media platforms,this study reveals that algorithmic empathy systems can improve emotional resonance by 34.7%and increase audience engagement by 28.3%compared to traditional communication methods.The findings demonstrate that AI algorithms reconstruct media communication logic through three primary pathways:emotional pattern recognition,personalized content curation,and real-time sentiment adaptation.However,the study also identifies significant challenges including algorithmic bias,emotional authenticity concerns,and ethical implications of automated empathy.The research contributes to understanding how mainstream media can leverage AI technology to build high-quality empathetic communication while maintaining journalistic integrity and social responsibility. 展开更多
关键词 algorithmic empathy artificial intelligence mainstream media communication logic emotional matching digital intelligence technology media convergence sentiment analysis
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Research on the Responsibility Traceability Mechanism Based on AI and the Application Boundary of Algorithmic Ethics in Medical Decision Making 认领 引用
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作者 Baochen Huang Zhikai Huang 《Proceedings of Business and Economic Studies》 2025年第4期280-298,共19页
With the rapid advancement of medical artificial intelligence(AI)technology,particularly the widespread adoption of AI diagnostic systems,ethical challenges in medical decision-making have garnered increasing attentio... With the rapid advancement of medical artificial intelligence(AI)technology,particularly the widespread adoption of AI diagnostic systems,ethical challenges in medical decision-making have garnered increasing attention.This paper analyzes the limitations of algorithmic ethics in medical decision-making and explores accountability mechanisms,aiming to provide theoretical support for ethically informed medical practices.The study highlights how the opacity of AI algorithms complicates the definition of decision-making responsibility,undermines doctor-patient trust,and affects informed consent.By thoroughly investigating issues such as the algorithmic“black box”problem and data privacy protection,we develop accountability assessment models to address ethical concerns related to medical resource allocation.Furthermore,this research examines the effective implementation of AI diagnostic systems through case studies of both successful and unsuccessful applications,extracting lessons on accountability mechanisms and response strategies.Finally,we emphasize that establishing a transparent accountability framework is crucial for enhancing the ethical standards of medical AI systems and protecting patients’rights and interests. 展开更多
关键词 Algorithmic ethics Medical decision-making Liability tracing Medical AI Patient rights protection
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Energy focusing of flexural waves via algorithmically optimized coding metasurface lenses 认领 引用
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作者 Zi-Rui Wang Di-Chao Chen +1 位作者 Rui Hong Da-Jian Wu 《Chinese Physics B》 SCIE EI CAS CSCD 2025年第9期277-282,共6页
Efficient elastic wave focusing is crucial in materials and physical engineering.Elastic coding metasurfaces,which are innovative planar artificial structures,show great potential for use in the field of wave focusing... Efficient elastic wave focusing is crucial in materials and physical engineering.Elastic coding metasurfaces,which are innovative planar artificial structures,show great potential for use in the field of wave focusing.However,elastic coding lenses(ECLs)still suffer from low focusing performance,thickness comparable to wavelength,and frequency sensitivity.Here,we consider both the structural and material properties of the coding unit,thus realizing further compression of the thickness of the ECL.We chose the simplest ECL,which consists of only two encoding units.The coding unit 0 is a straight structure constructed using a carbon fiber reinforced composite material,and the coding unit 1 is a zigzag structure constructed using an aluminum material,and the thickness of the ECL constructed using them is only 1/8 of the wavelength.Based on the theoretical design,the arrangement of coding units is further optimized using genetic algorithms,which significantly improves the focusing performance of the lens at different focus and frequencies.This study provides a more effective way to control vibration and noise in advanced structures. 展开更多
关键词 coding metasurface elastic wave focusing genetic algorithm
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Artificial intelligence in the service of entrepreneurial finance:knowledge structure and the foundational algorithmic paradigm 认领 引用
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作者 Robert Kudelić Tamara Šmaguc Sherry Robinson 《Financial Innovation》 2025年第1期2021-2063,共43页
The study conducts a bibliometric review of artificial intelligence applications in two areas:the entrepreneurial finance literature,and the corporate finance literature with implications for entrepreneurship.A rigoro... The study conducts a bibliometric review of artificial intelligence applications in two areas:the entrepreneurial finance literature,and the corporate finance literature with implications for entrepreneurship.A rigorous search and screening of the web of science core collection identified 1,890 journal articles for analysis.The bibliometrics provide a detailed view of the knowledge field,indicating underdeveloped research directions.An important contribution comes from insights through artificial intelligence methods in entrepreneurship.The results demonstrate a high representation of artificial neural networks,deep neural networks,and support vector machines across almost all identified topic niches.In contrast,applications of topic modeling,fuzzy neural networks,and growing hierarchical self-organizing maps are rare.Additionally,we take a broader view by addressing the problem of applying artificial intelligence in economic science.Specifically,we present the foundational paradigm and a bespoke demonstration of the Monte Carlo randomized algorithm. 展开更多
关键词 Bibliometrics Artificial intelligence Entrepreneurship Finance Randomized algorithm
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Nonlinear Model Algorithmic Control of a pH Neutralization Process 认领 引用 被引量：11
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作者 邹志云 于蒙 +4 位作者 王志甄 刘兴红 郭宇晴 张风波 郭宁 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2013年第4期395-400,共6页
Control of pH neutralization processes is challenging in the chemical process industry because of their inherent strong nonlinearity. In this paper, the model algorithmic control (MAC) strategy is extended to nonlinea... Control of pH neutralization processes is challenging in the chemical process industry because of their inherent strong nonlinearity. In this paper, the model algorithmic control (MAC) strategy is extended to nonlinear processes using Hammerstein model that consists of a static nonlinear polynomial function followed in series by a linear impulse response dynamic element. A new nonlinear Hammerstein MAC algorithm (named NLH-MAC) is presented in detail. The simulation control results of a pH neutralization process show that NLH-MAC gives better control performance than linear MAC and the commonly used industrial nonlinear propotional plus integral plus derivative (PID) controller. Further simulation experiment demonstrates that NLH-MAC not only gives good control response, but also possesses good stability and robustness even with large modeling errors. 展开更多
关键词 model algorithmic control nonlinear model predictive control Hammerstein model pH neutralization process control simulation
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On the E-Valuation of Certain E-Business Strategies on Firm Performance by Adaptive Algorithmic Modeling: An Alternative Strategic Managerial Approach 认领 引用 被引量：1
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作者 Alexandra Lipitakis Evangelia A.E.C. Lipitakis 《Computer Technology and Application》 2012年第1期38-46,共9页
This paper describes an innovative adaptive algorithmic modeling approach, for solving a wide class of e-business and strategic management problems under uncertainty conditions. The proposed methodology is based on ba... This paper describes an innovative adaptive algorithmic modeling approach, for solving a wide class of e-business and strategic management problems under uncertainty conditions. The proposed methodology is based on basic ideas and concepts of four key-field interrelated sciences, i.e., computing science, applied mathematics, management sciences and economic sciences. Furthermore, the fundamental scientific concepts of adaptability and uncertainty are shown to play a critical role of major importance for a （near） optimum solution of a class of complex e-business/services and strategic management problems. Two characteristic case studies, namely measuring e-business performance under certain environmental pressures and organizational constraints and describing the relationships between technology, innovation and firm performance, are considered as effective applications of the proposed adaptive algorithmic modeling approach. A theoretical time-dependent model for the evaluation of firm e-business performances is also proposed. 展开更多
关键词 Adaptive algorithms algorithmic modeling e-business problems e-service strategy management methodologies hybrid algorithmic modeling strategy management （SM） methodologies time-dependent performance evaluation model.
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Study on the Splitting Methods for Separable Convex Optimization in a Unified Algorithmic Framework 认领 引用
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作者 Bingsheng He 《Analysis in Theory and Applications》 CSCD 2020年第3期262-282,共21页
It is well recognized the convenience of converting the linearly constrained convex optimization problems to a monotone variational inequality.Recently,we have proposed a unified algorithmic framework which can guide ... It is well recognized the convenience of converting the linearly constrained convex optimization problems to a monotone variational inequality.Recently,we have proposed a unified algorithmic framework which can guide us to construct the solution methods for solving these monotone variational inequalities.In this work,we revisit two full Jacobian decomposition of the augmented Lagrangian methods for separable convex programming which we have studied a few years ago.In particular,exploiting this framework,we are able to give a very clear and elementary proof of the convergence of these solution methods. 展开更多
关键词 Convex programming augmented Lagrangian method multi-block separable model Jacobian splitting unified algorithmic framework.
COMPUTATIONAL AND ALGORITHMIC ASPECTS OF CARDINAL SPLINE-WAVELETS 认领 引用
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作者 C.K.Chui Wang Jianzhong 《Analysis in Theory and Applications》 1993年第1期53-75,共23页
Pascal triangles are formulated for computing the coefficients of the B-spline series representation of the compactly supported spline-wavelets with minimum support and their derivatives.It is shown that with the al- ... Pascal triangles are formulated for computing the coefficients of the B-spline series representation of the compactly supported spline-wavelets with minimum support and their derivatives.It is shown that with the al- ternating signs removed,all these sequences are totally positive.On the other hand,truncations of the recipro- cal Euler-Frobenius polynomials lead to finite sequences for orthogonal wavelet decompositions.For this pur- pose,sharp estimates are given in terms of the exact reconstruction of these approximate decomposed compo- nents. 展开更多
关键词 COMPUTATIONAL AND ALGORITHMIC ASPECTS OF CARDINAL SPLINE-WAVELETS
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Unleashing the Power of Multi-Agent Reinforcement Learning for Algorithmic Trading in the Digital Financial Frontier and Enterprise Information Systems 认领 引用
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作者 Saket Sarin Sunil K.Singh +4 位作者 Sudhakar Kumar Shivam Goyal Brij Bhooshan Gupta Wadee Alhalabi Varsha Arya 《Computers, Materials & Continua》 SCIE EI 2024年第8期3123-3138,共16页
In the rapidly evolving landscape of today’s digital economy,Financial Technology(Fintech)emerges as a trans-formative force,propelled by the dynamic synergy between Artificial Intelligence(AI)and Algorithmic Trading... In the rapidly evolving landscape of today’s digital economy,Financial Technology(Fintech)emerges as a trans-formative force,propelled by the dynamic synergy between Artificial Intelligence(AI)and Algorithmic Trading.Our in-depth investigation delves into the intricacies of merging Multi-Agent Reinforcement Learning(MARL)and Explainable AI(XAI)within Fintech,aiming to refine Algorithmic Trading strategies.Through meticulous examination,we uncover the nuanced interactions of AI-driven agents as they collaborate and compete within the financial realm,employing sophisticated deep learning techniques to enhance the clarity and adaptability of trading decisions.These AI-infused Fintech platforms harness collective intelligence to unearth trends,mitigate risks,and provide tailored financial guidance,fostering benefits for individuals and enterprises navigating the digital landscape.Our research holds the potential to revolutionize finance,opening doors to fresh avenues for investment and asset management in the digital age.Additionally,our statistical evaluation yields encouraging results,with metrics such as Accuracy=0.85,Precision=0.88,and F1 Score=0.86,reaffirming the efficacy of our approach within Fintech and emphasizing its reliability and innovative prowess. 展开更多
关键词 Neurodynamic Fintech multi-agent reinforcement learning algorithmic trading digital financial frontier
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Feature selection for face recognition:a memetic algorithmic approach 认领 引用 被引量：3
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作者 Dinesh KUMAR Shakti KUMAR C.S.RAI 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS 2009年第8期1140-1152,共13页
The eigenface method that uses principal component analysis(PCA) has been the standard and popular method used in face recognition.This paper presents a PCA-memetic algorithm(PCA-MA) approach for feature selection.PCA... The eigenface method that uses principal component analysis(PCA) has been the standard and popular method used in face recognition.This paper presents a PCA-memetic algorithm(PCA-MA) approach for feature selection.PCA has been extended by MAs where the former was used for feature extraction/dimensionality reduction and the latter exploited for feature selection.Simulations were performed over ORL and YaleB face databases using Euclidean norm as the classifier.It was found that as far as the recognition rate is concerned,PCA-MA completely outperforms the eigenface method.We compared the performance of PCA extended with genetic algorithm(PCA-GA) with our proposed PCA-MA method.The results also clearly established the supremacy of the PCA-MA method over the PCA-GA method.We further extended linear discriminant analysis(LDA) and kernel principal component analysis(KPCA) approaches with the MA and observed significant improvement in recognition rate with fewer features.This paper also compares the performance of PCA-MA,LDA-MA and KPCA-MA approaches. 展开更多
关键词 Face recognition Memetic algorithm （MA） Principal component analysis （PCA） Linear discriminant analysis （LDA） Kernel principal component analysis （KPCA） Feature selection
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Algorithmic approach to discrete fracture network flow modeling in consideration of realistic connections in large-scale fracture networks 认领 引用 被引量：1
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作者 Qihua Zhang Shan Dong +2 位作者 Yaoqi Liu Junjie Huang Feng Xiong 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第9期3798-3811,共14页
Analyzing rock mass seepage using the discrete fracture network(DFN)flow model poses challenges when dealing with complex fracture networks.This paper presents a novel DFN flow model that incorporates the actual conne... Analyzing rock mass seepage using the discrete fracture network(DFN)flow model poses challenges when dealing with complex fracture networks.This paper presents a novel DFN flow model that incorporates the actual connections of large-scale fractures.Notably,this model efficiently manages over 20,000 fractures without necessitating adjustments to the DFN geometry.All geometric analyses,such as identifying connected fractures,dividing the two-dimensional domain into closed loops,triangulating arbitrary loops,and refining triangular elements,are fully automated.The analysis processes are comprehensively introduced,and core algorithms,along with their pseudo-codes,are outlined and explained to assist readers in their programming endeavors.The accuracy of geometric analyses is validated through topological graphs representing the connection relationships between fractures.In practical application,the proposed model is employed to assess the water-sealing effectiveness of an underground storage cavern project.The analysis results indicate that the existing design scheme can effectively prevent the stored oil from leaking in the presence of both dense and sparse fractures.Furthermore,following extensive modification and optimization,the scale and precision of model computation suggest that the proposed model and developed codes can meet the requirements of engineering applications. 展开更多
关键词 Discrete fracture network(DFN)flow model Geometric algorithm Fracture flow Water-sealing effect
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Algorithmic tangent modulus at finite strains based on multiplicative decomposition 认领 引用
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作者 李朝君 冯吉利 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2014年第3期345-358,共14页
The algorithmic tangent modulus at finite strains in current configuration plays an important role in the nonlinear finite element method. In this work, the exact tensorial forms of the algorithmic tangent modulus at ... The algorithmic tangent modulus at finite strains in current configuration plays an important role in the nonlinear finite element method. In this work, the exact tensorial forms of the algorithmic tangent modulus at finite strains are derived in the principal space and their corresponding matrix expressions are also presented. The algorithmic tangent modulus consists of two terms. The first term depends on a specific yield surface, while the second term is independent of the specific yield surface. The elastoplastic matrix in the principal space associated with the specific yield surface is derived by the logarithmic strains in terms of the local multiplicative decomposition. The Drucker-Prager yield function of elastoplastic material is used as a numerical example to verify the present algorithmic tangent modulus at finite strains. 展开更多
关键词 algorithmic tangent modulus matrix expression finite strain multiplicative decomposition
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