Suchergebnisse - (automatic OR automation) machinery learning algorithm based on genetics algorithms

Genetic algorithm based active fault-tolerant control system for air fuel ratio control of internal combustion engines

Autoren: Muhammad Sajid Iqbal Arslan Ahmed Amin

Quelle: Measurement + Control, Vol 55 (2022)

Schlagwörter: MATLAB, Artificial intelligence, 0209 industrial biotechnology, Control (management), 02 engineering and technology, Process Fault Detection and Diagnosis in Industries, Redundancy (engineering), Automotive engineering, Quantum mechanics, 7. Clean energy, Reliability engineering, Fault (geology), Internal Combustion Engines, Engineering, Fault Isolation, Actuator, Machine learning, Control theory (sociology), T1-995, Constraint Handling, Technology (General), FOS: Chemical engineering, Seismology, Fluid Flow and Transfer Processes, Control engineering systems. Automatic machinery (General), Chemical Kinetics of Combustion Processes, Control engineering, Physics, Fault tolerance, Observer (physics), Geology, FOS: Earth and related environmental sciences, Chemical Engineering, Fault Detection, Internal combustion engine, Computer science, Operating system, Model Predictive Control in Industrial Processes, Genetic algorithm, Control and Systems Engineering, 13. Climate action, TJ212-225, Electrical engineering, Physical Sciences, Fault detection and isolation, Robust Control

Zugangs-URL: https://doaj.org/article/a221c489f2b74ebd81630adbd298e0bb

A pillar-based microfluidic chip for T-cells and B-cells isolation and detection with machine learning algorithm

Autoren: Bilal Turan Taisuke Masuda Lei Wu et al.

Quelle: ROBOMECH Journal, Vol 5, Iss 1, Pp 1-9 (2018)

Schlagwörter: Technology, Artificial intelligence, Support vector machine, Industrial engineering. Management engineering, Microfluidics, 02 engineering and technology, Histogram of Oriented Gradients features, Biochemistry, Metastasis, Automation, Engineering, TJ1-1570, Nanotechnology, Mechanical engineering and machinery, TJ227-240, Paper-Based Microfluidics, Microfluidic Devices, Cell counting, Cancer, Life Sciences, Comprehensive Integration of Single-Cell Transcriptomic Data, T58.5-58.64, Algorithm, Chemistry, TJ212-225, Physical Sciences, Paper-Based Diagnostic Devices, 0210 nano-technology, Biomedical engineering, B-cells, Biomedical Engineering, Information technology, T55.4-60.8, Microfluidic Techniques for Particle Manipulation and Separation, Cell cycle, FOS: Medical engineering, Lab-on-a-Chip, Biochemistry, Genetics and Molecular Biology, Machine learning, Genetics, Image (mathematics), T1-995, Machine design and drawing, Molecular Biology, Biology, Technology (General), FOS: Nanotechnology, Histogram, Control engineering systems. Automatic machinery (General), T-cells, Circulating tumor cell, Computer science, Materials science, T59.5, Microfluidic chip, Biological system, FOS: Biological sciences, Cell

Zugangs-URL: https://robomechjournal.springeropen.com/track/pdf/10.1186/s40648-018-0124-8
https://doaj.org/article/743f31083b254b22819d5237f0e861e0
https://robomechjournal.springeropen.com/articles/10.1186/s40648-018-0124-8
https://link.springer.com/article/10.1186/s40648-018-0124-8
https://link.springer.com/content/pdf/10.1186/s40648-018-0124-8.pdf

Multi-Voyage Path Planning for River Crab Aquaculture Feeding Boats.

Autoren: Sun, Yueping Guo, Peixuan Wang, Yantong et al.

Quelle: Fishes (MDPI AG). Aug2025, Vol. 10 Issue 8, p420. 27p.

Schlagwörter: *GENETIC algorithms, *REINFORCEMENT learning, *FRESHWATER crabs, *ROBOTIC path planning, *MATHEMATICAL optimization, *MARICULTURE, *OBSTACLE avoidance (Robotics)

Wearable blood pressure sensors for cardiovascular monitoring and machine learning algorithms for blood pressure estimation.

Autoren: Min S An J Lee JH et al.

Quelle: Nature reviews. Cardiology [Nat Rev Cardiol] 2025 Sep; Vol. 22 (9), pp. 629-648. Date of Electronic Publication: 2025 Feb 18.

Publikationsart: Journal Article; Review

Info zur Zeitschrift: Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101500075 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1759-5010 (Electronic) Linking ISSN: 17595002 NLM ISO Abbreviation: Nat Rev Cardiol Subsets: MEDLINE

MeSH-Schlagworte: Machine Learning* , Wearable Electronic Devices* , Blood Pressure*/physiology , Blood Pressure Determination*/instrumentation , Blood Pressure Determination*/methods , Blood Pressure Monitors* , Blood Pressure Monitoring, Ambulatory*/instrumentation, Humans ; Algorithms ; Predictive Value of Tests ; Equipment Design

A machine learning approach to population pharmacokinetic modelling automation.

Autoren: Richardson S Irurzun Arana I Nowojewski A et al.

Quelle: Communications medicine [Commun Med (Lond)] 2025 Jul 31; Vol. 5 (1), pp. 327. Date of Electronic Publication: 2025 Jul 31.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Nature Portfolio Country of Publication: England NLM ID: 9918250414506676 Publication Model: Electronic Cited Medium: Internet ISSN: 2730-664X (Electronic) Linking ISSN: 2730664X NLM ISO Abbreviation: Commun Med (Lond) Subsets: PubMed not MEDLINE

AI-based model for automatic identification of multiple sclerosis based on enhanced sea-horse optimizer and MRI scans.

Autoren: Khattap MG Abd Elaziz M Hassan HGEMA et al.

Quelle: Scientific reports [Sci Rep] 2024 May 27; Vol. 14 (1), pp. 12104. Date of Electronic Publication: 2024 May 27.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

MeSH-Schlagworte: Multiple Sclerosis*/diagnostic imaging , Magnetic Resonance Imaging*/methods , Algorithms*, Humans ; Female ; Male ; Adult ; Artificial Intelligence ; Brain/diagnostic imaging ; Brain/pathology ; Image Interpretation, Computer-Assisted/methods ; Case-Control Studies ; Young Adult ; Middle Aged ; Image Processing, Computer-Assisted/methods

Exploring Potential Hub Genes and Molecular Mechanisms Linking Cardia Carcinoma With Sjögren's Syndrome Based on Comprehensive Bioinformatics Analysis and Machine Learning.

Autoren: Qian M Chen Y Wang Z et al.

Quelle: The journal of gene medicine [J Gene Med] 2025 Sep; Vol. 27 (9), pp. e70044.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: John Wiley & Sons Country of Publication: England NLM ID: 9815764 Publication Model: Print Cited Medium: Internet ISSN: 1521-2254 (Electronic) Linking ISSN: 1099498X NLM ISO Abbreviation: J Gene Med Subsets: MEDLINE

MeSH-Schlagworte: Sjogren's Syndrome*/genetics , Sjogren's Syndrome*/complications , Computational Biology*/methods , Machine Learning* , Stomach Neoplasms*/genetics , Stomach Neoplasms*/pathology , Stomach Neoplasms*/etiology , Cardia*/pathology, Humans ; Gene Regulatory Networks ; Protein Interaction Maps/genetics ; Gene Expression Regulation, Neoplastic ; Gene Expression Profiling ; Nomograms ; Biomarkers, Tumor/genetics ; Databases, Genetic

A clustering-aided multi-agent deep reinforcement learning for multi-objective parallel batch processing machines scheduling in semiconductor manufacturing

Autoren: Peng Zhang Mengyu Jin Ming Wang et al.

Quelle: Measurement + Control, Vol 58 (2025)

Schlagwörter: 0209 industrial biotechnology, Control engineering systems. Automatic machinery (General), TJ212-225, 0211 other engineering and technologies, T1-995, 02 engineering and technology, Technology (General)

Zugangs-URL: https://doaj.org/article/3035953ce3c7462bbe79970cb38ea0e8

An automated parallel genetic algorithm with parametric adaptation for distributed data analysis.

Autoren: Al-Terkawi L Migliavacca M

Quelle: Scientific reports [Sci Rep] 2025 Mar 29; Vol. 15 (1), pp. 10836. Date of Electronic Publication: 2025 Mar 29.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: PubMed not MEDLINE; MEDLINE

Advancing biological taxonomy in the AI era: deep learning applications, challenges, and future directions.

Autoren: Lu S Fang C Zeng H et al.

Quelle: Science China. Life sciences [Sci China Life Sci] 2025 Oct 23. Date of Electronic Publication: 2025 Oct 23.

Publikationsart: Journal Article; Review

Info zur Zeitschrift: Publisher: Science China Press, co-published with Springer Country of Publication: China NLM ID: 101529880 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1869-1889 (Electronic) Linking ISSN: 16747305 NLM ISO Abbreviation: Sci China Life Sci Subsets: MEDLINE

Gender identification of chicks using vocalisation signals, artificial intelligence and machine learning techniques: current status and future prospects.

Autoren: Kannan, A. Basu, Joyanta Roy, Rajib et al.

Quelle: World's Poultry Science Journal. Mar2025, Vol. 81 Issue 1, p87-102. 16p.

Feature fusion and selection using handcrafted vs. deep learning methods for multimodal hand biometric recognition.

Autoren: Artabaz S Sliman L

Quelle: Scientific reports [Sci Rep] 2025 Aug 10; Vol. 15 (1), pp. 29237. Date of Electronic Publication: 2025 Aug 10.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

MeSH-Schlagworte: Deep Learning* , Hand*/anatomy & histology , Biometric Identification*/methods , Biometry*/methods, Humans ; Algorithms ; Dermatoglyphics ; Reproducibility of Results

Deep learning in water protection of resources, environment, and ecology: achievement and challenges.

Autoren: Fu X Jiang J Wu X et al.

Quelle: Environmental science and pollution research international [Environ Sci Pollut Res Int] 2024 Feb; Vol. 31 (10), pp. 14503-14536. Date of Electronic Publication: 2024 Feb 02.

Publikationsart: Journal Article; Review

Info zur Zeitschrift: Publisher: Springer Country of Publication: Germany NLM ID: 9441769 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1614-7499 (Electronic) Linking ISSN: 09441344 NLM ISO Abbreviation: Environ Sci Pollut Res Int Subsets: MEDLINE

MeSH-Schlagworte: Deep Learning*, Ecology ; Water Pollution/prevention & control ; Algorithms ; Water Resources

Mobile Robot Path Planning Method Based on Deep Reinforcement Learning Algorithm.

Autoren: Meng, Haitao Zhang, Hengrui

Quelle: Journal of Circuits, Systems & Computers; Oct2022, Vol. 31 Issue 15, p1-19, 19p

Schlagwörter: REINFORCEMENT learning, ROBOTIC path planning, MACHINE learning, MOBILE robots, REWARD (Psychology), ENERGY function

Unlocking the Potential of Zebrafish Research with Artificial Intelligence: Advancements in Tracking, Processing, and Visualization.

Autoren: Fan YL Hsu FR Wang Y et al.

Quelle: Medical & biological engineering & computing [Med Biol Eng Comput] 2023 Nov; Vol. 61 (11), pp. 2797-2814. Date of Electronic Publication: 2023 Aug 09.

Publikationsart: Journal Article; Review

Info zur Zeitschrift: Publisher: Springer Country of Publication: United States NLM ID: 7704869 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1741-0444 (Electronic) Linking ISSN: 01400118 NLM ISO Abbreviation: Med Biol Eng Comput Subsets: MEDLINE

MeSH-Schlagworte: Artificial Intelligence* , Deep Learning*, Animals ; Zebrafish ; Algorithms ; Neural Networks, Computer

Generative Inverse Design of Metamaterials with Functional Responses by Interpretable Learning

Autoren: Wei (Wayne) Chen Rachel Sun Doksoo Lee et al.

Quelle: Advanced Intelligent Systems, Vol 7, Iss 6, Pp n/a-n/a (2025)

Schlagwörter: functional responses, generative design, interpretable machine learning, inverse design, metamaterials, Computer engineering. Computer hardware, TK7885-7895, Control engineering systems. Automatic machinery (General), TJ212-225

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2640-4567

Zugangs-URL: https://doaj.org/article/167af797d8594616b2f3a967e86667b0

A fault detection strategy for an ePump during EOL tests based on a knowledge-based vibroacoustic tool and supervised machine learning classifiers.

Autoren: Borriello, Pasquale Tessicini, Fabrizio Ricucci, Giuseppe et al.

Quelle: Meccanica; Mar2024, Vol. 59 Issue 3, p279-304, 26p

A novel deep learning-based 1D-CNN-optimized GRU approach for heart disease prediction

Autoren: Jini Mol G. Ajith Bosco Raj T.

Quelle: Automatika, Vol 66, Iss 1, Pp 79-90 (2025)

Schlagwörter: 1D-CNN, genetic algorithm (GA), optimized GRU (OGRU), SMOTE-ENN, Control engineering systems. Automatic machinery (General), TJ212-225, Automation, T59.5

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/0005-1144; https://doaj.org/toc/1848-3380

Zugangs-URL: https://doaj.org/article/f0ca2a0189ee4810b9f4232cda2a060a

Physics‐Based Human‐in‐the‐Loop Machine Learning Combined with Genetic Algorithm Search for Multicriteria Optimization: Electrochemical CO2 Reduction Reaction

Autoren: Naohiro Fujinuma Samuel E. Lofland

Quelle: Advanced Intelligent Systems, Vol 5, Iss 5, Pp n/a-n/a (2023)

Schlagwörter: carbon dioxide reduction reaction, correlation analyses, genetic algorithms, machine learning, SHapley Additive exPlanations, Computer engineering. Computer hardware, TK7885-7895, Control engineering systems. Automatic machinery (General), TJ212-225

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2640-4567

Zugangs-URL: https://doaj.org/article/a276dc412fe24f4085557a914382bc89

Abnormal Detection and Fault Diagnosis of Adjustment Hydraulic Servomotor Based on Genetic Algorithm to Optimize Support Vector Data Description with Negative Samples and One-Dimensional Convolutional Neural Network

Autoren: Xukang Yang Anqi Jiang Wanlu Jiang et al.

Quelle: Machines, Vol 12, Iss 6, p 368 (2024)

Schlagwörter: adjustment hydraulic servomotor, fault detection, fault diagnosis, genetic algorithm, support vector data description, one-dimensional convolutional neural networks, Mechanical engineering and machinery, TJ1-1570

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2075-1702/12/6/368; https://doaj.org/toc/2075-1702

Zugangs-URL: https://doaj.org/article/53c2c28d089542728eefe2d4c29e2835