Suchergebnisse - automatisation machine learning algorithm based on genetic algorithms

Adaptive load consumption modelling on the user side: contributions to load forecasting modelling based on supervised mixture of experts and genetic programming

Autoren: Giacometto Torres, Francisco Javier

Weitere Verfasser: University/Department: Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica

Thesis Advisors: Romeral Martínez, José Luis

Quelle: TDX (Tesis Doctorals en Xarxa)

Schlagwörter: Energy management, Machine learning, Knowledge discovery algorithms, Short time load forecasting, Ensemble learning, Àrees temàtiques de la UPC::Enginyeria electrònica

Time: 621.3

Dateibeschreibung: application/pdf

Zugangs-URL: http://hdl.handle.net/10803/457631
https://dx.doi.org/10.5821/dissertation-2117-111507

Adaptive load consumption modelling on the user side: contributions to load forecasting modelling based on supervised mixture of experts and genetic programming

Autoren: Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica Romeral Martínez, José Luis Giacometto Torres, Francisco

Quelle: TDX (Tesis Doctorals en Xarxa)

Index Begriffe: Àrees temàtiques de la UPC::Enginyeria electrònica, Energy management, Machine learning, Knowledge discovery algorithms, Short time load forecasting, Ensemble learning, Aprenentatge automàtic, Algorismes genètics, Doctoral thesis

URL: http://hdl.handle.net/2117/111507
http://hdl.handle.net/10803/457631

A Log Parsing Framework for ALICE O2 Facilities

Autoren: Tinnakorn Marlaithong V. Chibante Barroso Phond Phunchongharn

Quelle: IEEE Access, Vol 11, Pp 69439-69457 (2023)

Schlagwörter: Artificial intelligence, System Logs, Computer Networks and Communications, online log parser, 7. Clean energy, Machine learning, Key (lock), Data mining, Log Analysis, Parsing, Automated Testing, Automated Software Testing Techniques, Geography, TF-IDF, ALICE experiment, FLP cluster, Computer science, TK1-9971, Intrusion Detection, Programming language, Algorithm, Operating system, machine learning, Log Analysis and System Performance Diagnosis, Computer Science, Physical Sciences, Network Intrusion Detection and Defense Mechanisms, Alice (programming language), Electrical engineering. Electronics. Nuclear engineering, Benchmark (surveying), Software, Geodesy

Zugangs-URL: https://doaj.org/article/e6c4a5566c4443af89fd6c147fe5cac6

Improving Brain Magnetic Resonance Image (MRI) Segmentation via a Novel Algorithm based on Genetic and Regional Growth.

Autoren: A., Javadpour A., Mohammadi

Quelle: Journal of Biomedical Physics & Engineering; Jun2016, Vol. 6 Issue 2, p95-108, 14p

Schlagwörter: MAGNETIC resonance imaging of the brain, IMAGE segmentation, DIAGNOSIS of brain diseases

A deep-learning algorithm (AIFORIA) for classification of hematopoietic cells in bone marrow aspirate smears based on nine cell classes—a feasible approach for routine screening?

Autoren: Saft, Leonie Vaara, Emma Ljung, Elin et al.

Quelle: Journal of Hematopathology; 3/29/2025, Vol. 18 Issue 1, p1-12, 12p

Proceedings of the 2025 3rd International Conference on Image, Algorithms, and Artificial Intelligence (ICIAAI 2025)

Autoren: Yanan Sun

Resource Type: eBook.

Categories: COMPUTERS / General

MedShapeNet  - a large-scale dataset of 3D medical shapes for computer vision.

Autoren: Li J Zhou Z Yang J et al.

Quelle: Biomedizinische Technik. Biomedical engineering [Biomed Tech (Berl)] 2024 Dec 30; Vol. 70 (1), pp. 71-90. Date of Electronic Publication: 2024 Dec 30 (Print Publication: 2025).

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Walter de Gruyter Publishers Country of Publication: Germany NLM ID: 1262533 Publication Model: Electronic-Print Cited Medium: Internet ISSN: 1862-278X (Electronic) Linking ISSN: 00135585 NLM ISO Abbreviation: Biomed Tech (Berl) Subsets: MEDLINE

MeSH-Schlagworte: Imaging, Three-Dimensional*/methods , Image Processing, Computer-Assisted*/methods, Humans ; Algorithms ; Printing, Three-Dimensional ; Brain Neoplasms/diagnostic imaging

A survey of ontology learning techniques and applications

Autoren: Muhammad Nabeel Asim Muhammad Wasim Muhammad Usman Ghani Khan et al.

Quelle: Database (Oxford)

Schlagwörter: FOS: Computer and information sciences, Artificial intelligence, Biomedical Ontologies and Text Mining, QoS-Aware Web Services Composition and Semantic Matching, Review, Epistemology, 02 engineering and technology, Ontology learning, Machine Learning, Suggested Upper Merged Ontology, Artificial Intelligence, Surveys and Questionnaires, Biochemistry, Genetics and Molecular Biology, 0202 electrical engineering, electronic engineering, information engineering, Data Mining, Humans, Industry, Information retrieval, Semantic Web Stack, Molecular Biology, Natural Language Processing, Semantic Web, Ontology engineering, Ontology, Natural language processing, Life Sciences, Linguistics, Semantics (computer science), Open Biomedical Ontologies, Knowledge representation and reasoning, Computer science, Ontology-based data integration, Process ontology, FOS: Philosophy, ethics and religion, Programming language, World Wide Web, Semantic Matching, OWL-S, Philosophy, Databases as Topic, Vocabulary, Controlled, Computer Science, Physical Sciences, Phenotype Ontology, Upper ontology, Semantic Web and Ontology Development, Ontology Inference Layer, Information Systems

Zugangs-URL: https://academic.oup.com/database/article-pdf/doi/10.1093/database/bay101/27329264/bay101.pdf
https://pubmed.ncbi.nlm.nih.gov/30295720
https://dblp.uni-trier.de/db/journals/biodb/biodb2018.html#AsimWKMA18
https://www.mendeley.com/catalogue/46f6a153-d695-332c-8d2d-16be99d68d7e/
https://pubmed.ncbi.nlm.nih.gov/30295720/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6173224
https://doi.org/10.1093/database/bay101
https://europepmc.org/article/MED/30295720

Method of and server for training a machine learning algorithm for estimating uncertainty of a sequence of models

Tools and Algorithms for the Construction and Analysis of Systems : 27th International Conference, TACAS 2021, Held As Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2021, Luxembourg City, Luxembourg, March 27 – April 1, 2021, Proceedings, Part I

Autoren: Jan Friso Groote Kim Guldstrand Larsen

Resource Type: eBook.

Schlagworte: System analysis--Congresses, Artificial intelligence, System design--Congresses, Computer software--Verification--Congresses

Categories: COMPUTERS / Computer Science, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Hardware / General

Improvisation of classification performance based on feature optimization for differentiation of Parkinson's disease from other neurological diseases using gait characteristics

Autoren: Satyabrata Aich Moon-il Joo Hee-Cheol Kim et al.

Schlagwörter: Gait charecteristics, Machine learning, Feature optimization, Parkinson's disease, Neurological disorders

Relation: https://zenodo.org/records/4093194; oai:zenodo.org:4093194

Verfügbarkeit: https://doi.org/10.11591/ijece.v9i6.pp5176-5184
https://zenodo.org/records/4093194

Multivariate Statistical Machine Learning Methods for Genomic Prediction

Autoren: Osval Antonio Montesinos López Abelardo Montesinos López José Crossa

Resource Type: eBook.

Schlagworte: Genomics, Agriculture, Biometry, Plant genetics--Statistical methods, Multivariate analysis--Data processing, Machine learning

Categories: TECHNOLOGY & ENGINEERING / Agriculture / General, COMPUTERS / Data Science / Bioinformatics, MEDICAL / Biostatistics, SCIENCE / Life Sciences / Botany, SCIENCE / Life Sciences / Genetics & Genomics

Deep Learning-Based Post-Processing of Real-Time MRI to Assess and Quantify Dynamic Wrist Movement in Health and Disease.

Autoren: Radke, Karl Ludger Wollschläger, Lena Marie Nebelung, Sven et al.

Quelle: Diagnostics (2075-4418); Jun2021, Vol. 11 Issue 6, p1077-1077, 1p

Schlagwörter: MAGNETIC resonance imaging, LIGAMENT injuries, WRIST, CONVOLUTIONAL neural networks, CARPAL bones, BLAND-Altman plot

Learning Spatiotemporal Representations of C. elegans From Bright-Field Microscopy Data Using Deep Learning Methods

Autoren: Deserno, Maurice

Schlagwörter: ddc:570, ddc:004

Dateibeschreibung: application/pdf

Zugangs-URL: https://kups.ub.uni-koeln.de/78293/

Heuristic Learning Based on Genetic Programming.

Autoren: Frank Schmiedle Nicole Drechsler Daniel Große et al.

Quelle: Genetic Programming & Evolvable Machines; Dec2002, Vol. 3 Issue 4, p363-388, 26p

Method of and system for generating training images for instance segmentation machine learning algorithm

METHOD OF AND SYSTEM FOR GENERATING TRAINING IMAGES FOR INSTANCE SEGMENTATION MACHINE LEARNING ALGORITHM

METHOD OF AND SERVER FOR TRAINING A MACHINE LEARNING ALGORITHM FOR ESTIMATING UNCERTAINTY OF A SEQUENCE OF MODELS

From Pairwise Comparisons of Complex Behavior to an Overall Performance Rank: A Novel Alloy Design Strategy.

Autoren: Herschberg, Rafael Rateau, Lisa Martinelli, Laure et al.

Quelle: Metals (2075-4701); Dec2024, Vol. 14 Issue 12, p1412, 30p

Schlagwörter: ALLOY testing, COMBINATORIAL optimization, GAUSSIAN processes, STRENGTH of materials, GENETIC algorithms

A Genetic Programming-Based Iterative Approach for the Integrated Process Planning and Scheduling Problem.

Autoren: Zhu, Xuedong Guo, Xinxing Wang, Weihao et al.

Quelle: IEEE Transactions on Automation Science & Engineering; Jul2022, Vol. 19 Issue 3, p2566-2580, 15p

Schlagwörter: PRODUCTION planning, PRODUCTION scheduling, AUTOMATION, FLEXIBLE manufacturing systems, GENETIC algorithms, LINEAR programming, MANUFACTURING processes, STATISTICAL decision making, GENETIC programming