Suchergebnisse - "Algorithm combining and selection"

A PM2.5 Concentration Inversion Algorithm Combining Feature Selection and Optimized Deep Forest

Autoren: Jiaqi Wu Shurui Fan Kewen Xia et al.

Quelle: 2025 10th International Conference on Electronic Technology and Information Science (ICETIS). :288-292

Research on P300 Brain-Computer Interface Classification Algorithm Combining Channel Selection and Deep Learning

Autoren: Qi Li Meiqi Sun Yu Song et al.

Quelle: 2022 16th ICME International Conference on Complex Medical Engineering (CME). :298-301

How Far Can You Get by Combining Change Detection Algorithms?

Autoren: Bianco, S Ciocca, G Schettini, R.

Quelle: Lecture Notes in Computer Science ISBN: 9783319685595

Schlagwörter: FOS: Computer and information sciences, G.1.6, Computer Vision and Pattern Recognition (cs.CV), 8. Economic growth, Computer Science - Computer Vision and Pattern Recognition, 0202 electrical engineering, electronic engineering, information engineering, I.4.8, Algorithm combining and selection, CDNET, Change detection, Genetic programming, Video surveillance, Theoretical Computer Science, Computer Science (all), 02 engineering and technology

Zugangs-URL: http://arxiv.org/pdf/1505.02921
http://arxiv.org/abs/1505.02921
https://arxiv.org/pdf/1505.02921
https://ui.adsabs.harvard.edu/abs/2015arXiv150502921B/abstract
https://arxiv.org/abs/1505.02921
https://boa.unimib.it/handle/10281/176510
https://arxiv.org/pdf/1505.02921.pdf
https://rd.springer.com/chapter/10.1007/978-3-319-68560-1_9
https://doi.org/10.1007/978-3-319-68560-1_9
https://link.springer.com/chapter/10.1007/978-3-319-68560-1_9
https://arxiv.org/abs/1505.02921
http://springerlink.com/content/0302-9743/copyright/2005/
https://hdl.handle.net/10281/176510
https://doi.org/10.1007/978-3-319-68560-1_9

Improving Network Attack Detection Using Hybrid Feature Selection and Deep Learning Methods.

Autoren: Al-Sadi, Ameer Mosa Al-Saadi, Ahmed

Quelle: International Journal of Intelligent Engineering & Systems; 2025, Vol. 18 Issue 4, p736-762, 27p

Schlagwörter: ARTIFICIAL neural networks, FEATURE selection, ANOMALY detection (Computer security), SMART cities, CLOUD computing

Fault Diagnosis Using Dynamic Principal Component Analysis and GA Feature Selection Modeling for Industrial Processes.

Autoren: Liu, Chenpeng Bai, Jianjun Wu, Feng

Quelle: Processes; Dec2022, Vol. 10 Issue 12, p2570, 20p

Schlagwörter: FAULT diagnosis, PRINCIPAL components analysis, MANUFACTURING processes, FEATURE selection, CHEMICAL processes, EIGENVECTORS

GEMMA-SQL: A Novel Text-to-SQL Model Based on Large Language Models.

Autoren: Pandey, Hari Mohan Gupta, Anshul Sarkar, Subham et al.

Quelle: Applied Artificial Intelligence; Dec2025, Vol. 39 Issue 1, p1-38, 38p

Tradition of Data-Intensive Use: The Example of Domain Thermophysics. Methods and Algorithms.

Autoren: Erkimbaev, A. O. Zitserman, V. Yu. Kobzev, G. A.

Quelle: Automatic Documentation & Mathematical Linguistics; Aug2025, Vol. 59 Issue 4, p231-251, 21p

Cold Chain Logistics Path Optimization with Adaptive Speed and Hybrid Genetic Algorithm Solution.

Autoren: Sun, Yuhui Pan, Dazhi

Quelle: Mathematics (2227-7390); Jun2025, Vol. 13 Issue 12, p1981, 24p

Schlagwörter: VEHICLE routing problem, CUSTOMER satisfaction, OVERHEAD costs, ENVIRONMENTAL economics, FUEL costs

A utility maximization approach for information-communication tradeoff in Wireless Body Area Networks.

Autoren: Wang, Hui Agoulmine, Nazim Deen, M. et al.

Quelle: Personal & Ubiquitous Computing; Dec2014, Vol. 18 Issue 8, p1963-1976, 14p, 3 Diagrams, 4 Graphs

Schlagwörter: BODY area networks, BIOSENSORS, COMPUTER simulation, ELECTRIC power consumption, MEDICAL technology, DIAGNOSTIC equipment

Joint user and antenna selection for multiuser MIMO downlink with block diagonalization.

Autoren: Liu, Wei Zou, Jun Luo, Han-wen et al.

Quelle: Journal of Shanghai Jiaotong University (Science); Dec2011, Vol. 16 Issue 6, p691-695, 5p

Enhancing IoT Security in Vehicles: A Comprehensive Review of AI-Driven Solutions for Cyber-Threat Detection.

Autoren: Abreu, Rafael Simão, Emanuel Serôdio, Carlos et al.

Quelle: AI; Dec2024, Vol. 5 Issue 4, p2279-2299, 21p

Schlagwörter: ARTIFICIAL intelligence, FEDERATED learning, DATA privacy, MACHINE learning, INFRASTRUCTURE (Economics), DEEP learning

Topology Optimization with Explicit Components Considering Stress Constraints.

Autoren: Ma, Yubao Li, Zhiguo Wei, Yuxuan et al.

Quelle: Applied Sciences (2076-3417); Aug2024, Vol. 14 Issue 16, p7171, 17p

Schlagwörter: STRAINS & stresses (Mechanics), STRESS concentration, CONCEPTUAL structures, ENGINEERING design, CONCENTRATION functions, STRUCTURAL optimization

A resource allocation scheme based on predatory search algorithm for ultra-dense D2D communications.

Autoren: Li, Xujie Sun, Ying Zhou, Lingjie et al.

Quelle: Wireless Networks (10220038); Jul2024, Vol. 30 Issue 5, p3357-3365, 9p

Schlagwörter: RESOURCE allocation, TELECOMMUNICATION systems, SEARCH algorithms

A multi-population evolutionary algorithm for multi-objective constrained portfolio optimization problem.

Autoren: Hemici, Meriem Zouache, Djaafar

Quelle: Artificial Intelligence Review; Dec2023 Suppl 3, Vol. 56, p3299-3340, 42p

Schlagwörter: PORTFOLIO management (Investments), CONSTRAINED optimization, EVOLUTIONARY algorithms, STATISTICS, FINANCIAL markets

一种多模型融合的风电系统永磁同步发电机数字 孪生建模方法. (Chinese)

Alternate Title: Digital twin modeling method of wind power system permanent magnet synchronous generator based on multi model fusion. (English)

Autoren: 刘利强 尹彦博 齐咏生 et al.

Quelle: Electric Machines & Control / Dianji Yu Kongzhi Xuebao; Nov2023, Vol. 27 Issue 11, p149-162, 14p

Schlagwörter: PERMANENT magnet generators, DIGITAL twin, REDUCED-order models, WIND power

Inversion of Rayleigh Wave Dispersion Curves via Long Short-Term Memory Combined with Particle Swarm Optimization.

Autoren: Fu, Yu Yang, Angen Yao, Zhenan et al.

Quelle: Computational Intelligence & Neuroscience; 12/23/2022, p1-15, 15p

Schlagwörter: PARTICLE swarm optimization, RAYLEIGH waves, CURVES, DISPERSION (Chemistry), GENETIC algorithms, DEEP learning, GEOLOGICAL modeling

Geografische Kategorien: WYOMING

Fault Diagnosis Using Dynamic Principal Component Analysis and GA Feature Selection Modeling for Industrial Processes

Autoren: Chenpeng Liu Jianjun Bai Feng Wu

Quelle: Processes, Vol 10, Iss 2570, p 2570 (2022)

Schlagwörter: fault diagnosis, PCA, DPCA, genetic algorithms, feature selection, Chemical technology, TP1-1185, Chemistry, QD1-999

Relation: https://www.mdpi.com/2227-9717/10/12/2570; https://doaj.org/toc/2227-9717; https://doaj.org/article/9663f6b810a24e4a83b3ae3cf9fcddb6

Verfügbarkeit: https://doi.org/10.3390/pr10122570
https://doaj.org/article/9663f6b810a24e4a83b3ae3cf9fcddb6

Fluid-structure-acoustic interactions in an ex vivo porcine phonation model.

Autoren: Semmler, Marion Berry, David A. Schützenberger, Anne et al.

Quelle: Journal of the Acoustical Society of America; Mar2021, Vol. 149 Issue 3, p1657-1673, 17p

Schlagwörter: VOCAL tract, VOCAL cords, LARYNX, AIR flow, ACOUSTICS

Combinational Hybrid Signal Selection With Updated Reachability Lists for Post-Silicon Debug.

Autoren: Beigmohammadi, Siamack Alizadeh, Bijan

Quelle: IEEE Transactions on Computer-Aided Design of Integrated Circuits & Systems; Jan2020, Vol. 39 Issue 1, p272-276, 5p

Schlagwörter: LOGIC circuits, RADIO frequency

A machine learning approach for fast future grid small-signal stability scanning.

Autoren: Liu, Ruidong Verbic, Gregor Ma, Jin

Quelle: 2016 IEEE International Conference on Power System Technology (POWERCON); 2016, p1-6, 6p