Advances and trends in Artificial Intelligence : Artificial Intelligence practices : 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, Kuala Lumpur, Malaysia, July 26–29, 2021, proceedings, part I / Hamido Fujita, Ali Selamat, Jerry Chun-Wei Lin, Moonis Ali (eds.)

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(34. : IEA/AIE (34. : 2021 : Online) [VerfasserIn]

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Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: Lecture notes in computer science ; Lecture notes in artificial intelligence ; 12798 | Springer eBook CollectionVerlag: Cham : Springer, [2021]Copyright-Datum: © 2021Beschreibung: 1 Online-Ressource (xx, 636 Seiten) : Diagramme, IllustrationenISBN:

9783030794576

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Konferenzschrift

Andere physische Formen: 9783030794569 | 9783030794583 | Erscheint auch als: 9783030794569 Druck-Ausgabe | Erscheint auch als: 9783030794583 Druck-Ausgabe | Erscheint auch als: Advances and trends in artificial intelligence ; Part 1: Artificial intelligence practices. Druck-Ausgabe Cham : Springer, 2021. xx, 636 SeitenDDC-Klassifikation:

006.3 23

DOI: DOI: 10.1007/978-3-030-79457-6Online-Ressourcen:

Zusammenfassung: Knowledge Discovery and Pattern Mining -- Fast Mining of Top-k Frequent Balanced Association Rules -- Towards Increasing Open Data Adoption through Stream Data Integration and Imputation -- Towards Efficient Discovery of Periodic-Frequent Patterns in Columnar Temporal Databases -- Data-Driven Simulation of Ride-Hailing Services using Imitation and Reinforcement Learning -- Discovering Spatial High Utility Itemsets in High-Dimensional Spatiotemporal Databases -- A Single-Stage Tree-Structure-Based Approach to Determine Fuzzy Average-Utility Itemsets -- Mining Episode Rules From Event Sequences Under Non-Overlapping Frequency -- Distributed mining of high utility time interval sequential patterns with multiple minimum utility thresholds -- Artificial Intelligence and Machine Learning -- Emergency Analysis: Multitask Learning with Deep Convolutional Neural Networks for Fire Emergency Scene Parsing -- Comparison of Consolidation Methods for Predictive Learning of Time Series -- Evolutionary Optimization of Convolutional Neural Network Architecture Design for Thoracic X-Ray Image Classification -- Understanding the Effects of Mitigation on De-identified Data -- Combining Siamese Network and Correlation Filter for Complementary Object Tracking -- Closed-Form Expressions for Global and Local Interpretation of Tsetlin Machines -- Explainable Reinforcement Learning with the Tsetlin Machine -- Sematic, Topology, and Ontology Models -- Semantic Technologies towards Missing Values Imputation -- An Improved Integer Programming Formulation for Inferring Chemical Compounds with Prescribed Topological Structures -- Automatic Classification for Ontology Generation by Pretrained Language Model -- Deep Learning Architecture for Topological Optimized Mechanical Design Generation with Complex Shape Criterion -- Computational Ontology and BIM Technology in Data-Driven Indoor Route Planning -- Collaborative Maintenance of EDOAL Alignments in VocBench -- DIKG2: a Semantic Data Integration Approach for Knowledge Graphs Generation from Web Forms -- Ontology-based Resume Searching System for Job Applicants in Information Technology -- An Approach to Expressing Metamodels’ Semantics in a Concept System -- Medical and Health-Related Applications -- Birth-death MCMC Approach for Multivariate Beta Mixture Models in Medical Applications -- Intelligent Asthma Self-Management System for Personalised Weather-based Healthcare using Machine Learning -- Deep Forecasting of COVID-19: Canadian Case Study -- COVID-19 Genome Analysis using Alignment-Free Methods -- Deep Efficient Neural Networks for Explainable COVID-19 detection on CXR Images -- Predicting Psychological Distress from Ecological Factors: A Machine Learning Approach -- Graphic and Social Network Analysis -- Configuration model of employee competences in a social media team -- The Extended Graph Generalization as a Representation of the Metamodels’ Extensional Layer -- WawPart: Workload-Aware Partitioning of Knowledge Graphs -- Analysis of Sentimental Behaviour over Social Data Using Machine Learning Algorithms -- Signal and Bioinformatic Processing -- A Large-scale Dataset for Hate Speech Detection on Vietnamese Social Media Texts -- Determining 2-Optimality Consensus for DNA structure -- Evolutionary Computation -- Utilizing Center-Based Sampling Theory to Enhance Particle Swarm Classification of Textual Data -- Conditional Preference Networks: Refining Solution Orderings beyond Pareto Dominance -- Enhancing Multi-Objective Evolutionary Neural Architecture Search with Surrogate Models and Potential Point-Guided Local Searches -- Insightful and Practical Multi-Objective Convolutional Neural Network Architecture Search with Evolutionary Algorithms -- Method for Automatic Furniture Placement Based on Simulated Annealing and Genetic Algorithm -- Attack and Security -- Recent Research on Phishing Detection through Machine Learning Algorithm -- A Transaction Classification Model of Federated Learning -- On the Assessment of Robustness of Telemedicine Applications against Adversarial Machine Learning Attacks -- A 1D-CNN Based Deep Learning for Detecting VSI-DDoS Attacks in IoT Applications -- Natural Language and Text Processing -- Hierarchical Transformer Encoders for Vietnamese Spelling Correction -- Fast and Memory-efficient TFIDF Calculation for Text Analysis of Large Datasets -- Collapsed Gibbs Sampling of Beta-Liouville Multinomial for Short Text Clustering -- Constructive and Toxic Speech Detection for Open-domain Social Media Comments in Vietnamese -- Fuzzy Inference and Theory -- The behaviour of the product t-norm in combination with several implications in Fuzzy PID controller -- Hub and Spoke Logistics Network Design for Urban Region with Clustering-Based Approach -- Sensor and Communication Networks -- Smartphone Sensor-Based Fall Detection using Machine Learning Algorithms -- IPR-SN: Intelligent Packet Routing in Satellite Networks Based on Distributed Deep Reinforcement Learning.Zusammenfassung: This two-volume set of LNAI 12798 and 12799 constitutes the thoroughly refereed proceedings of the 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, held virtually and in Kuala Lumpur, Malaysia, in July 2021. The 87 full papers and 19 short papers presented were carefully reviewed and selected from 145 submissions. The IEA/AIE 2021 conference will continue the tradition of emphasizing on applications of applied intelligent systems to solve real-life problems in all areas. These areas include the following: Part I, Artificial Intelligence Practices: Knowledge discovery and pattern mining; artificial intelligence and machine learning; sematic, topology, and ontology models; medical and health-related applications; graphic and social network analysis; signal and bioinformatics processing; evolutionary computation; attack security; natural language and text processing; fuzzy inference and theory; and sensor and communication networks Part II, From Theory to Practice: Prediction and recommendation; data management, clustering and classification; robotics; knowledge based and decision support systems; multimedia applications; innovative applications of intelligent systems; CPS and industrial applications; defect, anomaly and intrusion detection; financial and supply chain applications; Bayesian networks; BigData and time series processing; and information retrieval and relation extraction.PPN: PPN: 1765221218Package identifier: Produktsigel: ZDB-2-LNC | ZDB-2-SCS | ZDB-2-SXCS | ZDB-2-SEB

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