Suchergebnisse - Data Structure—Graphs and Networks General Terms Algorithms*

Overlapping community detection in networks: the state of the art and comparative study

Autoren: Jierui Xie The Pennsylvania State University CiteSeerX Archives

Weitere Verfasser: Jierui Xie The Pennsylvania State University CiteSeerX Archives

Quelle: http://www.cs.rpi.edu/~szymansk/papers/acm-cs.13.pdf.

Schlagwörter: Categories and Subject Descriptors, A.1 [General Literature, Introductory and Survey, I.5.3 [Clustering, Clustering—Algorithms, H.3.3 [Clustering, Information Search and Retrieval—Clustering, E.1[Data, Data Structures—Graphs and networks General Terms, Algorithms, Performance Additional Key Words and Phrases, Overlapping community detection, social networks ACM Reference Format

Dateibeschreibung: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.432.7976

Verfügbarkeit: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.432.7976
http://www.cs.rpi.edu/~szymansk/papers/acm-cs.13.pdf

Overlapping community detection in networks: the state of the art and comparative study

Autoren: Jierui Xie Stephen Kelley Boleslaw K. Szymanski et al.

Weitere Verfasser: Jierui Xie Stephen Kelley Boleslaw K. Szymanski et al.

Quelle: http://cgi2.cs.rpi.edu/%7Eszymansk/papers/acm-cs.13.pdf.

Schlagwörter: Categories and Subject Descriptors, A.1 [General Literature, INTRODUCTORY AND SUR- VEY, I.5.3 [Clustering, Clustering—Algorithms, H.3.3 [Clustering, Information Search and Retrieval—Clustering, E.1[Data, DATA STRUCTURES—Graphs and networks General Terms, Algorithms, Performance Additional Key Words and Phrases, overlapping community detection, social networks

Dateibeschreibung: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.261.3847

Verfügbarkeit: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.261.3847
http://cgi2.cs.rpi.edu/%7Eszymansk/papers/acm-cs.13.pdf

Rendered Path: Range-Free Localization in Anisotropic Sensor Networks with Holes

Autoren: Mo Li The Pennsylvania State University CiteSeerX Archives

Weitere Verfasser: Mo Li The Pennsylvania State University CiteSeerX Archives

Quelle: http://www.cse.ust.hk/~limo/papers/REP_Mobicom07.pdf.

Schlagwörter: Categories and Subject Descriptors C.2.1 [Computer Communication Networks, Network Architecture and Design – Distributed networks, Wireless communication, C.2.4 [Computer Communication Networks, Distributed Systems- Distributed applications, E.1 [Data, Data Structures – Graph and networks. General Terms Algorithms, Design, Theory Keywords Wireless Sensor Network, Range-free, Localization, Anisotropic

Dateibeschreibung: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.133.1889; http://www.cse.ust.hk/~limo/papers/REP_Mobicom07.pdf

Verfügbarkeit: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.133.1889
http://www.cse.ust.hk/~limo/papers/REP_Mobicom07.pdf

Data-Driven Early Warning Approach for Antimicrobial Resistance Prediction–Anomaly Detection Based on High-Level Indicators.

Autoren: Csorba, Szilveszter Vribék, Krisztián Farkas, Máté et al.

Quelle: Veterinary Sciences. Oct2025, Vol. 12 Issue 10, p935. 17p.

High-Precision Prediction of Total Nitrogen Based on Distance Correlation and Machine Learning Models—A Case Study of Dongjiang River, China.

Autoren: Chen, Yuanpei Yao, Weike Chen, Yiling

Quelle: Water (20734441); Apr2025, Vol. 17 Issue 8, p1131, 22p

Schlagwörter: CONVOLUTIONAL neural networks, LONG short-term memory, WATER quality management, FEATURE selection, STANDARD deviations, HYPOXIA (Water), WATER quality monitoring

Integrating multi-modal data fusion approaches for analysis of dairy cattle vocalizations.

Autoren: Jobarteh, Bubacarr Mincu-Iorga, Madalina Gavojdian, Dinu et al.

Quelle: Frontiers in Veterinary Science. 2025, p1-13. 13p.

Quantitative prediction of intracellular dynamics and synaptic currents in a small neural circuit.

Autoren: Burghi, Thiago B. Schapiro, Kyra Ivanova, Maria et al.

Quelle: Frontiers in Computational Neuroscience; 2025, p1-19, 19p

Schlagwörter: CENTRAL pattern generators, DEEP learning, RECURRENT neural networks, CELLULAR mechanics, MACHINE learning, NEURAL circuitry, GANGLIA, NEURAL transmission

Automated Stuttering Detection Using Deep Learning Techniques.

Autoren: Alhakbani, Noura Alnashwan, Raghad Al-Nafjan, Abeer et al.

Quelle: Journal of Clinical Medicine; May2025, Vol. 14 Issue 10, p3552, 20p

Schlagwörter: LONG short-term memory, MACHINE learning, DEEP learning, CONVOLUTIONAL neural networks, ARTIFICIAL intelligence

Multi-Factor Prediction of Water Inflow from the Working Face Based on an Improved SSA-RG-MHA Model.

Autoren: Ding, Yingying Yin, Shangxian Dai, Zhenxue et al.

Quelle: Water (20734441); Dec2024, Vol. 16 Issue 23, p3390, 22p

Schlagwörter: MINE water, STANDARD deviations, CRANES (Birds), WATER levels, SEARCH algorithms

An Efficient Water Quality Prediction and Assessment Method Based on the Improved Deep Belief Network—Long Short-Term Memory Model.

Autoren: Zhao, Zhiyao Fan, Bing Zhou, Yuqin

Quelle: Water (20734441); May2024, Vol. 16 Issue 10, p1362, 23p

Schlagwörter: WATER quality, BOLTZMANN machine, DEEP learning, WATER currents, EVOLUTIONARY computation, WATER levels, GAUSSIAN distribution

Prediction of the Height of Water-Conducting Fissure Zone for Shallow-Buried Coal Seams Under Fully Mechanized Caving Conditions in Northern Shaanxi Province.

Autoren: Chen, Wei Geng, Shujia Chen, Xi et al.

Quelle: Water (20734441); Feb2025, Vol. 17 Issue 3, p312, 24p

Schlagwörter: ARTIFICIAL neural networks, PARTICLE swarm optimization, SUPPORT vector machines, NONLINEAR regression, RANDOM forest algorithms

Analysis of River Management Method Based on Improved Bidirectional Long Short-Term Memory Network for Water Quality Prediction.

Autoren: Wang, Zhongya Liu, Shuang

Quelle: Water Conservation Science & Engineering; 3/8/2025, Vol. 10 Issue 1, p1-12, 12p

AI-driven epitope prediction: a system review, comparative analysis, and practical guide for vaccine development.

Autoren: Villanueva-Flores, Francisca Sanchez-Villamil, Javier I. Garcia-Atutxa, Igor

Quelle: NPJ Vaccines; 8/30/2025, Vol. 10 Issue 1, p1-15, 15p

Schlagwörter: VACCINE development, EPITOPES, PREDICTION models, TRANSFORMER models, CONVOLUTIONAL neural networks, ARTIFICIAL intelligence, GRAPH neural networks, DATA integration

Multi-label remote sensing classification with self-supervised gated multi-modal transformers.

Autoren: Liu, Na Yuan, Ye Wu, Guodong et al.

Quelle: Frontiers in Computational Neuroscience; 2025, p1-15, 15p

Schlagwörter: REMOTE sensing, MULTISENSOR data fusion, MULTISPECTRAL imaging, TRANSFORMER models, CLASSIFICATION, SUPERVISED learning, SYNTHETIC aperture radar

Daily Streamflow Forecasting Using Networks of Real-Time Monitoring Stations and Hybrid Machine Learning Methods.

Autoren: Zhang, Yue Zhou, Zimo Deng, Ying et al.

Quelle: Water (20734441); May2024, Vol. 16 Issue 9, p1284, 22p

Schlagwörter: CONVOLUTIONAL neural networks, DROUGHT forecasting, STREAMFLOW, MACHINE learning, STANDARD deviations, HYDROLOGIC cycle

Electroencephalographic Signal Data Augmentation Based on Improved Generative Adversarial Network.

Autoren: Du, Xiuli Wang, Xinyue Zhu, Luyao et al.

Quelle: Brain Sciences (2076-3425); Apr2024, Vol. 14 Issue 4, p367, 17p

Schlagwörter: GENERATIVE adversarial networks, DATA augmentation, CONVOLUTIONAL neural networks, ELECTROENCEPHALOGRAPHY, DEEP learning

Groundwater Level Estimation Using Improved Transformer Model: A Case Study of the Yellow River Basin.

Autoren: Zhou, Tianming Fu, Chun Liu, Yezhong et al.

Quelle: Water (20734441); Aug2025, Vol. 17 Issue 15, p2318, 23p

Schlagwörter: GROUNDWATER, TRANSFORMER models, DEEP learning, WATERSHEDS, WATER management, REMOTE sensing, STATISTICAL reliability, LONG short-term memory

Geografische Kategorien: YELLOW River (China)

A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification.

Autoren: Kadhim, Yezi Ali Guzel, Mehmet Serdar Mishra, Alok

Quelle: Diagnostics (2075-4418); Jul2024, Vol. 14 Issue 14, p1469, 25p

Schlagwörter: COMPUTER-aided diagnosis, METAHEURISTIC algorithms, CONVOLUTIONAL neural networks, DEEP learning, COMPUTER science

Advanced Mathematical Science for Mobility Society

Autoren: Kazushi Ikeda Yoshiumi Kawamura Kazuhisa Makino et al.

Resource Type: eBook.

Schlagworte: Quantitative research, Transportation--Data processing, Transportation--Mathematics, Traffic engineering, Transportation engineering

Categories: COMPUTERS / Computer Science, COMPUTERS / Database Administration & Management, MATHEMATICS / Applied, MATHEMATICS / Probability & Statistics / General, TECHNOLOGY & ENGINEERING / Civil / Highway & Traffic

Real-time multi-object detection and tracking in UAV systems: improved YOLOv11-EFAC and optimized tracking algorithms.

Autoren: Kıratlı, Rabia Eroğlu, Alperen

Quelle: Journal of Real-Time Image Processing; Oct2025, Vol. 22 Issue 5, p1-28, 28p