Výsledky vyhľadávania - Automatic machinery learning algorithm based on genetic algorithms

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

Autori: Muhammad Sajid Iqbal Arslan Ahmed Amin

Zdroj: Measurement + Control, Vol 55 (2022)

Predmety: 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

Prístupová URL adresa: https://doaj.org/article/a221c489f2b74ebd81630adbd298e0bb

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

Autori: Naohiro Fujinuma Samuel E. Lofland

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

Predmety: 0301 basic medicine, correlation analyses, SHapley Additive exPlanations, Computer engineering. Computer hardware, 0303 health sciences, Artificial Intelligence and Robotics, Control engineering systems. Automatic machinery (General), 7. Clean energy, carbon dioxide reduction reaction, genetic algorithms, TK7885-7895, 03 medical and health sciences, machine learning, Materials Science and Engineering, TJ212-225

Popis súboru: application/pdf

Prístupová URL adresa: https://doaj.org/article/a276dc412fe24f4085557a914382bc89

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

Autori: Bilal Turan Taisuke Masuda Lei Wu a ďalší

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

Predmety: 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

Prístupová URL adresa: 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

Research on Efficiency Improvement Technology of Wide Range Centrifugal Pump Based on Genetic Algorithm and Internal Flow Loss Diagnosis.

Autori: Liu, Zhenbo Ji, Leilei Pu, Wei a ďalší

Zdroj: Water (20734441); Dec2024, Vol. 16 Issue 23, p3402, 28p

Predmety: PRODUCTION losses, ROTATING machinery, GENETIC algorithms, CENTRIFUGAL pumps, ROTATIONAL motion, MECHANICAL energy

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

Autori: Sun, Yueping Guo, Peixuan Wang, Yantong a ďalší

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

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

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

Autori: Peng Zhang Mengyu Jin Ming Wang a ďalší

Zdroj: Measurement + Control, Vol 58 (2025)

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

Prístupová URL adresa: https://doaj.org/article/3035953ce3c7462bbe79970cb38ea0e8

Intelligent Monitoring System for Deep Foundation Pit Based on Digital Twin.

Autori: Pan, Peng Sun, Shuo-Hui Feng, Jie-Xun a ďalší

Zdroj: Buildings (2075-5309); Feb2025, Vol. 15 Issue 3, p366, 24p

Predmety: BUILDING foundations, OPTIMIZATION algorithms, BORED piles, ELASTIC modulus, DIGITAL twin

Design of nonlinear control system for motion trajectory of industrial handling robot.

Autori: Zhao, Haoming Zhang, Xinling

Zdroj: Advanced Control for Applications; Jun2024, Vol. 6 Issue 2, p1-15, 15p

Predmety: INDUSTRIAL robots, AUTOMATIC machinery, LAGRANGE equations, ANGULAR acceleration, TORQUE

基于遗传算法优化 Canny 算子的织绣文物纹样抽取方法研究. (Chinese)

Alternate Title: Research on the extraction method of woven and embroidered artifacts' patterns based on genetic algorithm optimization of Canny operator. (English)

Autori: 张 宇 张 健 齐 林

Zdroj: Journal of Silk; 2024, Vol. 61 Issue 6, p1-12, 12p

Design Optimization of Steering Mechanisms for Articulated Off-Road Vehicles Based on Genetic Algorithms.

Autori: Zhou, Chen Liu, Xinhui Xu, Feixiang

Zdroj: Algorithms; Feb2018, Vol. 11 Issue 2, p22, 13p

Predmety: GENETIC algorithms, STEERING gear, OFF-road vehicles, EVOLUTIONARY algorithms, LEARNING classifier systems

Comprehensive Planning of Laboratory Equipment Based on Genetic Algorithms.

Autori: Mi, Tiantian

Zdroj: Computational Intelligence & Neuroscience; 9/12/2022, p1-11, 11p

Predmety: LABORATORY equipment & supplies, POLYNOMIAL time algorithms, ALGORITHMS, HEURISTIC algorithms, COMBINATORIAL optimization, GENETIC algorithms

Hyperparameter Optimization for Deep Learning-based Automatic Melanoma Diagnosis System

Autori: Takashi Nagaoka

Zdroj: Advanced Biomedical Engineering. 2020, 9:225

A Summary of PID Control Algorithms Based on AI-Enabled Embedded Systems.

Autori: Zhou, Yi

Zdroj: Security & Communication Networks; 4/23/2022, p1-7, 7p

Predmety: ANT algorithms, MANUFACTURING processes, INTELLIGENT control systems, ALGORITHMS, ADAPTIVE control systems, PREDICTIVE control systems, GENETIC algorithms, PID controllers

Generative Inverse Design of Metamaterials with Functional Responses by Interpretable Learning

Autori: Wei (Wayne) Chen Rachel Sun Doksoo Lee a ďalší

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

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

Popis súboru: electronic resource

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

Prístupová URL adresa: https://doaj.org/article/167af797d8594616b2f3a967e86667b0

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

Autori: Xukang Yang Anqi Jiang Wanlu Jiang a ďalší

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

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

Popis súboru: electronic resource

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

Prístupová URL adresa: https://doaj.org/article/53c2c28d089542728eefe2d4c29e2835

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

Autori: Jini Mol G. Ajith Bosco Raj T.

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

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

Popis súboru: electronic resource

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

Prístupová URL adresa: https://doaj.org/article/f0ca2a0189ee4810b9f4232cda2a060a

Research on the Photovoltaic MPPT Method Based on Improved BP-SVM-ELM Combination Prediction

Autori: DAI Bowang ZHAO Xianggui ZHU Qiliang

Zdroj: Kongzhi Yu Xinxi Jishu, Vol 36, Pp 44-49 (2019)

Predmety: photovoltaic power generation, maximum power point tracking, combination prediction, genetic algorithm, neural networks, support vector machine, extreme learning machine, Control engineering systems. Automatic machinery (General), TJ212-225, Technology

Popis súboru: electronic resource

Relation: http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2019.01.009; https://doaj.org/toc/2096-5427

Prístupová URL adresa: https://doaj.org/article/f61d244560f74a2f9fc281a657d03854

Prediction of Stem Cell State Using Cell Image‐Based Deep Learning

Autori: Minjae Kim Yong Namkung Donghun Hyun a ďalší

Zdroj: Advanced Intelligent Systems, Vol 5, Iss 7, Pp n/a-n/a (2023)

Predmety: cell culture, cell morphology, convolutional neural networks, deep learning, prediction, stem cells, Computer engineering. Computer hardware, TK7885-7895, Control engineering systems. Automatic machinery (General), TJ212-225

Popis súboru: electronic resource

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

Prístupová URL adresa: https://doaj.org/article/d5345520286e4fccb2ef003283444480

Dual Neural Network Framework with SPICE Integration for Fast and Accurate Transistor Modeling

Autori: Rodion Novkin Hussam Amrouch

Zdroj: Advanced Intelligent Systems, Vol 7, Iss 10, Pp n/a-n/a (2025)

Predmety: circuit simulation, design technology co‐optimization, machine learning, neural network, transistor compact model, Computer engineering. Computer hardware, TK7885-7895, Control engineering systems. Automatic machinery (General), TJ212-225

Popis súboru: electronic resource

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

Prístupová URL adresa: https://doaj.org/article/edeea3d843ea467a8358720f7a8c905c

An intelligent fault identification method of rolling bearings based on SVM optimized by improved GWO

Autori: Haisong Huang Qingsong Fan Jianan Wei a ďalší

Zdroj: Systems Science & Control Engineering, Vol 7, Iss 1, Pp 289-303 (2019)

Predmety: Improved grey wolf optimization algorithm, support vector machine, parameter optimization, bearing fault diagnosis, Control engineering systems. Automatic machinery (General), TJ212-225, Systems engineering, TA168

Popis súboru: electronic resource

Relation: https://doaj.org/toc/2164-2583

Prístupová URL adresa: https://doaj.org/article/6d208fd2421344f69807289cf9a8eced