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检索条件"任意字段=13th International Conference on Knowledge-Based Intelligent Information and Engineering Systems"

共 10151 条记录，以下是41-50 订阅

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1st international Workshop on Hybrid Artificial Intelligence and Enterprise Modelling for intelligent information systems, HybridAIMS, 1st Workshop on knowledge Graphs for Semantics-Driven systems engineering, KG4SDSE, Blockchain and Decentralized Governance Design for information systems, BC4IS and DGD, associated with the 35th international conference on Advanced information systems engineering, CAiSE 2023

1st International Workshop on Hybrid Artificial Intelligence...

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1st international Workshop on Hybrid Artificial Intelligence and Enterprise Modelling for intelligent information systems, HybridAIMS, 1st Workshop on knowledge Graphs for Semantics-Driven systems engineering, KG4SDSE, Blockchain and Decentralized Governance Design for information systems, BC4IS and DGD, associated with the 35th international conference on Advanced information systems engineering, CAiSE 2023

ISBN: (纸本)9783031349843

the proceedings contain 19 papers. the special focus in this conference is on Hybrid Artificial Intelligence and Enterprise Modelling for intelligent information systems. the topics include: A Linked Data based Advanced Credit Rationale;interactive Machine Learning of knowledge Graph-based Explainable Process Analysis;a Weighted knowledge Graph for Representing the Results of a Systematic Literature Review;knowledge engineering Formalizing DECENT Meta Model;using knowledge Graphs for Record Linkage: Challenges and Opportunities;employing knowledge Graphs for Capturing Semantic Aspects of Robotic Process Automation;Regulation-Friendly Privacy-Preserving Blockchain based on zk-SNARK;blockchain Governance Design a Computer Science Perspective;the MEV Saga: Can Regulation Illuminate the Dark Forest?;enriching Enterprise Architecture Models with Healthcare Domain knowledge;supporting Reuse of Business Process Models by Semantic Annotation;position Paper - Hybrid Artificial Intelligence for Realizing a Leadership Assistant for Platform-based Leadership Consulting;developing a Maturity Assessment Tool to Enable the Management of Artificial Intelligence for Organizations;mapping Time-Series Data on Process Patterns to Generate Synthetic Data;Towards Crisis Response and Intervention Using knowledge Graphs - CRISP Case Study;the RAI Way: A Technical Analysis and Design Method for Building Enterprise Semantic Layers;Towards Recommendations for knowledge-Graph-based Requirements Management in Construction: A Report on the EU DigiChecks Project.

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A Framework for Ontology-based engineering systems: Advances and Open Questions About knowledge Capture and Use in Aerospace Manufacturing 5th

A Framework for Ontology-Based Engineering Systems: Advances...

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5th international conference on Innovative intelligent Industrial Production and Logistics

作者： Mas, Fernando Arista, Rebeca Skrzek, Murillo Oliva, Manuel Morales-Palma, Domingo Szejka, Anderson Luis Univ Seville Seville Spain Airbus SAS Toulouse France Pontif Catholic Univ Parana PUCPR Curitiba Parana Brazil Airbus Def & Space Seville Spain CT Engn Grp Madrid Spain

ISBN: (纸本)9783031807749;9783031807756

Modern Ontology-based engineering (OBE) systems, built over the foundations of knowledge-based engineering (KBE), leverage ontology-based technologies and the semantic web to capture and formalise knowledge holistically. this comprehensive knowledge repository can subsequently feed design and decision support tools with robust generative features. However, the integration and reuse of knowledge poses challenges for which it is necessary to develop appropriate methods and tools capable of handling diverse types of knowledge from both human experience and databases. the objective of this paper is to discuss the current limitations of OBE systems to address knowledge integration and reuse, based on the research and experiences of the authors in the aerospace manufacturing industry. this aims to provide a set of Research Questions (RQ) and the author's position to them, to serve as future research work and topics of discussion for the scientific community.

关键词： Ontology-based engineering (OBE) knowledge-based engineering (KBE) Models for Manufacturing (MfM) Ontologies

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Tensor Decomposition-based Feature Transfer Learning for BCI Applications 13

Tensor Decomposition-Based Feature Transfer Learning for BCI...

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13th international conference on intelligent Control and information Processing, ICICIP 2025

作者： Bonab, Zahra Sohrabi Shamsollahi, Mohammad Bagher Department of Electrical Engineering Sharif University of Technology Tehran Iran

ISBN: (纸本)9798331516147

Event-Related Potential (ERP) detection and enhancement remain significant challenges in EEG signal processing due to the complex and multidimensional nature of ERP signals. this paper addresses these challenges by proposing a novel framework that combines low-rank tensor representation with heuristic feature transfer learning for efficient ERP processing. By leveraging tensor decomposition, we capture intricate multidimensional patterns in ERP data, facilitating the extraction of informative features. these features greatly reduce processing time, making the method particularly suitable for online Brain-Computer Interface (BCI) applications. We also present a feature transfer learning mechanism utilizing tensor decomposition, which facilitates the efficient adaptation of features trained on multiple subjects to new subjects, requiring only a small amount of calibration data. this approach leverages shared classification structures across subjects, allowing for rapid deployment and minimizing the need for extensive retraining. Our results demonstrate that the proposed method achieves reasonable ERP detection accuracy while drastically reducing computational overhead, presenting a robust solution for real-time BCI systems. © 2025 IEEE.

关键词： Event Related Potentials (ERPs) Feature Extraction Feature Transfer Learning Tensor Decomposition

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7th international conference on intelligent systems and knowledge engineering, ISKE 2012 with 1st international conference on Cognitive systems and information Processing, CSIP 2012

7th International Conference on Intelligent Systems and Know...

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7th international conference on intelligent systems and knowledge engineering, ISKE 2012 with 1st international conference on Cognitive systems and information Processing, CSIP 2012

ISBN: (纸本)9783642378287

the proceedings contain 67 papers. the special focus in this conference is on Cognitive systems and information Processing. the topics include: the incremental updating method for core computing based on information entropy in set-valued ordered information systems;an algebraic analysis for binary intuitionistic L-fuzzy relations;an improved classification method based on random forest for medical image;ideagraph: turning data into human insights for collective intelligence;a general hierarchy-set-based indoor location modeling approach;acquisition of class attributes based on chinese online encyclopedia and association rule mining;a delivery time computational model for pervasive computing in satellite networks;how people use visual landmarks for locomotion distance estimation: the case study of eye tracking;prediction analysis of the railway track state based on PCA-RBF neural network;a two-step agglomerative hierarchical clustering method for patent time-dependent data;a novel modular recurrent wavelet neural network and its application to nonlinear system identification;automated text data extraction based on unsupervised small sample learning;SLAM and navigation of a mobile robot for indoor environments;a novel approach for computing quality map of visual information fidelity index and a simulation of electromagnetic compatibility QoS model in cognitive radio network.

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Invariant Set Analysis and Control Synthesis of Multi-Equilibrium Switched systems under Control Constraints 13

Invariant Set Analysis and Control Synthesis of Multi-Equili...

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13th international conference on intelligent Control and information Processing, ICICIP 2025

作者： Han, Yuejiang Zhang, Lixian Ding, Yihang Dong, Yifei Liang, Ye School of Astronautics Harbin Institute of Technology Harbin China College of Computer and Control Engineering Northeast Forestry University Harbin China

ISBN: (纸本)9798331516147

this paper investigates the problems of invariant set analysis and control synthesis for multi-equilibrium switched systems under control constraints. A control strategy based on the invariant set method is proposed, accompanied by criteria formulated as linear matrix inequalities, ensuring that the state remains within the mode-dependent invariant sets. Furthermore, considering the control constraints in practical scenarios, a multi-equilibrium switched controller with control constraints (MESCC controller) is designed. Compared to existing works, the proposed method incorporates mode-dependent dwell time conditions and mode-dependent invariant sets, thereby offering enhanced design flexibility. An example of an aero-engine control system is presented to demonstrate the effectiveness and potential of the theoretical results. © 2025 IEEE.

关键词： Control system synthesis

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Research on visualization of minority music knowledge graph based on Neo4j 24

Research on visualization of minority music knowledge graph ...

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7th international conference on information Science and systems, ICISS 2024

作者： Mao, ChunXia Wen, ShuangBing Liu, Hong Hu, Tao Li, Jun College of Intelligent Systems Science and Engineering Hubei Minzu University China Hubei Engineering Research Center of Selenium Food Nutrition and Health Intelligent Technology Hubei Minzu University China School of Music and Dance Hubei Minzu University China The Key Laboratory of Performing Art Equipment and System Technology Ministry of Culture and Tourism Hubei Minzu University China

ISBN: (纸本)9798400717567

the digital age has created various channels for the sustainable development of traditional culture. A Neo4j-based knowledge graph for Tujia Intangible cultural heritage music was constructed to address the potential loss of Tujia Intangible cultural heritage music. the project involved integrating and consolidating Tujia Intangible cultural heritage music resources, organizing and cleaning the collected data, storing it in a Neo4j graph database, designing a knowledge base ontology model, and completing the construction of the Tujia Intangible cultural heritage music knowledge graph. the knowledge graph makes the knowledge of music and cultural heritage explicit from vast information resources, effectively expanding its dissemination breadth and promoting the protection and inheritance of intangible cultural heritage music in ethnic areas. © 2024 Copyright held by the owner/author(s).

关键词： knowledge graph

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A Novel LSTM Optimized by Neurodynamic Network for Heat Prediction of Power Equipment 13

A Novel LSTM Optimized by Neurodynamic Network for Heat Pred...

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13th international conference on intelligent Control and information Processing, ICICIP 2025

作者： Wei, Huang Zhu, Minghao Zheng, Shiyuan Qiu, Lingfeng Zhang, Yansheng Zhang, Zhijun Meizhou Power Supply Bureau Guangdong Power Grid Corporation Meizhou China School of Automation Science and Engineering South China University of Technology Guangzhou China

ISBN: (纸本)9798331516147

With the rapid development of smart grid and substation equipment, the heating problem of power equipment has become an important factor affecting the stability and safety of equipment. the traditional equipment monitoring method has lag, and it is difficult to predict the heating trend of the equipment in time. therefore, a long short-term memory based on neurodynamic network(NN-LSTM) is proposed to improve the accuracy of predicting the heating trend of power equipment. In this paper, the predictive ability of the LSTM network is improved by combining the neurodynamic optimization strategy. And it is applied to power load forecasting and transformer oil temperature forecasting. Experimental results show that NN-LSTM is superior to the traditional LSTM model on the two datasets, the mean square error is effectively reduced, and the prediction accuracy is higher. © 2025 IEEE.

关键词： Oil filled transformers

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Resolving Unseen Rumors with Retrieval-Augmented Large Language Models 13th

Resolving Unseen Rumors with Retrieval-Augmented Large Langu...

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13th international conference on Natural Language Processing and Chinese Computing

作者： Chen, Lei Wei, Zhongyu Fudan Univ Sch Data Sci Shanghai Peoples R China Fudan Univ Res Inst Intelligent & Complex Syst Shanghai Peoples R China

ISBN: (纸本)9789819794393;9789819794409

Social media has become the primary source of information for individuals, yet much of this information remains unverified. the rise of generative artificial intelligence has further accelerated the creation of unverified content. Adaptive rumor resolution systems are imperative for maintaining information integrity and public trust. Traditional methods have relied on encoder-based frameworks to enhance rumor representation and propagation characteristics. However, these models are often small in scale and lack generalizability for unforeseen events. Recent advances in Large Language Models show promise but are unreliable in discerning truth from falsehood. Our work leverages LLMs by creating a testbed for predicting unprecedented rumors and designing a retrieval-augmented framework that integrates historical knowledge and collective intelligence. Experiments on two real-world datasets demonstrate the effectiveness of our proposed framework.

关键词： Rumor Detection Retrieval-Augmented LLMs

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7th international conference on Know1edge-based intelligent information and engineering systems, KES 2003

7th International Conference on Know1edge-Based Intelligent ...

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7th international conference on knowledge-based intelligent information and engineering systems, KES 2003

ISBN: (纸本)3540408045

the proceedings contain 193 papers. the special focus in this conference is on Advances on Adaptive Resonance theory and Applications. the topics include: Putting the utility of match tracking in fuzzy ARTMAP training to the test;an ART-based hybrid network for medical pattern classification tasks with missing data;combining support vector machines and ARTMAP architectures for natural classification;ART-based neuro-fuzzy modelling applied to reinforcement learning;ART-based fuzzy classifier;intelligent assistance, retrieval, reminder and advice for fuzzy multicriteria decision-malting;facilitating electronic business planning with decision making support systems;a modeling approach based on a re-planning tool;a framework to assess intelligent decision-making support systems;an information market for multi-agent decision making;classification of decision-behavior patterns in multivariate computer log data using independent component analysis;design, integration and evaluation of an artificial intelligence-based control system for the improvement of the monitoring and quality control process in the manufacturing of metal casting components;fuzzy support systems for discretionary judicial decision malting;intelligent decision malting support through just-in-time knowledge management;integrating simulation and argumentation in organizational decision malting;perceptual grouping t o motion direction and speed in apertures;assignment of figural side to contours based on symmetry, parallelism, and convexity;neural network model restoring partly occluded patterns and face localization in the neural abstraction pyramid.

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Decentralized Federated Learning with Auto-switchable Local Optimizers 13

Decentralized Federated Learning with Auto-switchable Local ...

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13th international conference on intelligent Control and information Processing, ICICIP 2025

作者： Li, Ting Chang, Zhongyi Pan, Zhiyao Yang, Shaofu Xu, Wenying Chen, Zhongying School of Computer Science and Engineering Southeast University Nanjing211189 China

ISBN: (纸本)9798331516147

In this paper, we propose a novel decentralized learning algorithm over networks, termed as DLAGD, which combines the consensus mechanism with an auto-switchable local optimizer. Specifically, each node updates its local model parameter based on either gradient descent algorithm or Adam-like algorithm, which depends on a local switching function. Such switchable local optimizer can better capture the structure information of local loss function than existing algorithms relying on a fixed local optimizer, then has the potential to accelerate the convergence rate and improve the generalization performance. We theoretically prove that DLAGD can converge to the neighborhood of a stationary point at a sublinear rate for non-convex problems. Finally, numerical experiments are presented to show the superior performance of DLAGD in terms of the training rate and test accuracy. © 2025 IEEE.

关键词： Federated learning

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