Suchergebnisse - Sequential last squares programming algorithm*

End-effector Cartesian stiffness shaping - sequential least squares programming approach

Autoren: Nikola Knezevic Branko Lukic Kosta Jovanovic et al.

Quelle: Serbian Journal of Electrical Engineering, Vol 18, Iss 1, Pp 1-14 (2021)

Schlagwörter: cartesian stiffness control, sequential last squares programming, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, physical human-robot interaction, 0210 nano-technology, robot redundancy, 01 natural sciences, TK1-9971, 0104 chemical sciences

Zugangs-URL: http://www.doiserbia.nb.rs/ft.aspx?id=1451-48692101001K
https://doaj.org/article/8f37c41634d84faab7906989ada91e90
https://sjee.ftn.kg.ac.rs/index.php/sjee/article/view/570
https://sjee.ftn.kg.ac.rs/index.php/sjee/article/download/570/528

Sequential hierarchical least-squares programming for prioritized non-linear optimal control.

Autoren: Pfeiffer, Kai Kheddar, Abderrahmane

Quelle: Optimization Methods & Software; Oct2024, Vol. 39 Issue 5, p1104-1142, 39p

Schlagwörter: INTERIOR-point methods, QUADRATIC programming, INVERSE problems, ALGORITHMS, MATRICES (Mathematics)

End-effector Cartesian stiffness shaping: Sequential least squares programming approach

Autoren: Knežević, Nikola Lukić, Branko Jovanović, Kosta et al.

Quelle: Serbian Journal of Electrical Engineering (2021) 18(1):1-14 ; ISSN: 1451-4869

Schlagwörter: Cartesian Stiffness Control, Robot Redundancy, Physical Human-Robot Interaction, Sequential Last Squares Programming

Dateibeschreibung: application/pdf; txt

Verfügbarkeit: http://scindeks.ceon.rs/article.aspx?artid=1451-48692101001K

Shaping the future energy markets with hybrid multimicrogrids by sequential least squares programming

Autoren: Paolo Fracas Kyle V. Camarda Edwin Zondervan

Quelle: Physical Sciences Reviews. 8:121-156

Schlagwörter: SLSQP, 13. Climate action, 9. Industry and infrastructure, interconnected hybrid microgrids, techno-economic assessment, SDG 7 - Affordable and Clean Energy, microgrid optimization, renewable energy systems, 01 natural sciences, 7. Clean energy, NLA, distributed energy resources, 0105 earth and related environmental sciences

Zugangs-URL: https://research.utwente.nl/en/publications/shaping-the-future-energy-markets-with-hybrid-multimicrogrids-by-
https://www.narcis.nl/publication/RecordID/oai%3Aris.utwente.nl%3Apublications%2Fbbe56d29-aca2-4fbb-a375-0f954099e825

Research on Prediction of Dissolved Gas Concentration in a Transformer Based on Dempster–Shafer Evidence Theory-Optimized Ensemble Learning.

Autoren: Zhang, Pan Hu, Kang Yang, Yuting et al.

Quelle: Electronics (2079-9292); Apr2025, Vol. 14 Issue 7, p1266, 16p

Schlagwörter: MACHINE learning, ENSEMBLE learning, DISTRIBUTION (Probability theory), HEALTH status indicators, ALGORITHMS, DEEP learning

A Deep Learning-Based Ensemble System for Brent and WTI Crude Oil Price Analysis and Prediction.

Autoren: Zhang, Yiwen Lahmiri, Salim

Quelle: Entropy; Nov2025, Vol. 27 Issue 11, p1122, 18p

Schlagwörter: DEEP learning, ENSEMBLE learning, PETROLEUM sales & prices, ENERGY consumption, BOOSTING algorithms, CONVOLUTIONAL neural networks, MATHEMATICAL optimization, LONG short-term memory

Benchmarking of different optimizers in the variational quantum algorithms for applications in quantum chemistry.

Autoren: Singh, Harshdeep Majumder, Sonjoy Mishra, Sabyashachi

Quelle: Journal of Chemical Physics; 7/28/2023, Vol. 159 Issue 4, p1-12, 12p

Schlagwörter: QUANTUM chemistry, GROUND state energy, STOCHASTIC approximation, HYDROGEN fluoride, ALGORITHMS, QUANTUM perturbations

A Smooth-Delayed Phase-Type Mixture Model for Human-Driven Process Duration Modeling.

Autoren: Wang, Dongwei McClean, Sally Yang, Lingkai et al.

Quelle: Algorithms; Sep2025, Vol. 18 Issue 9, p575, 28p

Schlagwörter: HUMAN behavior, PARAMETER estimation, UNITS of time, STATISTICAL models, BAYESIAN analysis, HUMAN behavior models

Shaping the future energy markets with hybrid multimicrogrids by sequential least squares programming.

Autoren: Fracas, Paolo Camarda, Kyle V. Zondervan, Edwin

Quelle: Physical Sciences Reviews; Jan2023, Vol. 8 Issue 1, p121-156, 36p

Hybrid Optimization Approaches for Impeller Design in Turbomachinery: Methods, Metrics, and Design Strategies.

Autoren: Remache, Abel Pérez-Sánchez, Modesto Hidalgo, Víctor Hugo et al.

Quelle: Water (20734441); Jul2025, Vol. 17 Issue 13, p1976, 35p

Schlagwörter: COMPUTATIONAL fluid dynamics, FINITE element method, RESPONSE surfaces (Statistics), MATHEMATICAL programming, CENTRIFUGAL pumps, MACHINE learning, TURBOMACHINES, EVOLUTIONARY algorithms

Virtual reality-assisted visualization of flood susceptibility using optimized machine learning models.

Autoren: Razavi-Termeh, Seyed Vahid Safari Bazargani, Jalal Sadeghi-Niaraki, Abolghasem et al.

Quelle: Applied Water Science; Oct2025, Vol. 15 Issue 10, p1-21, 21p

Schlagwörter: VIRTUAL reality, MACHINE learning, OPTIMIZATION algorithms, FLOOD risk, ENVIRONMENTAL mapping, GEOGRAPHICAL positions, RANDOM forest algorithms

Geografische Kategorien: FARS (Iran)

Predictive analysis of pulmonary fibrosis progression using gradient boosting classifier and DICOM images.

Autoren: Ramyea, R. Kasthuri, N. Kumar, Kandasamy Senthil et al.

Quelle: AIP Conference Proceedings; 3/27/2024, Vol. 2966 Issue 1, p1-8, 8p

Schlagwörter: PULMONARY fibrosis, ASBESTOS, COAL dust, BOOSTING algorithms, DISEASE risk factors, TREE growth

Enhancing spatial prediction of groundwater-prone areas through optimization of a boosting algorithm with bio-inspired metaheuristic algorithms.

Autoren: Razavi-Termeh, Seyed Vahid Sadeghi-Niaraki, Abolghasem Abba, Sani I. et al.

Quelle: Applied Water Science; Nov2024, Vol. 14 Issue 11, p1-25, 25p

Schlagwörter: METAHEURISTIC algorithms, STANDARD deviations, BOOSTING algorithms, RECEIVER operating characteristic curves, ARTIFICIAL intelligence

Large‐Scale Drought Forecasting in the U.S. Southern Plains Through a Hybrid Cluster‐Based Wavelet‐Machine Learning Approach.

Autoren: Lee, SangHyun Danandeh Mehr, Ali Moriasi, Daniel et al.

Quelle: Water Resources Research; Nov2025, Vol. 61 Issue 11, p1-23, 23p

Schlagwörter: DROUGHT forecasting, MACHINE learning, WAVELET transforms, CLIMATE change adaptation, HYDROLOGIC models, PLAINS, SPATIAL variation, EVAPOTRANSPIRATION

Applications and Considerations of Artificial Intelligence in Veterinary Sciences: A Narrative Review.

Autoren: Akbarein, Hesameddin Taaghi, Mohammad Hussein Mohebbi, Mahyar et al.

Quelle: Veterinary Medicine & Science. May2025, Vol. 11 Issue 3, p1-29. 29p.

Schlagworte: Machine learning, Artificial intelligence, Veterinary medicine, Resource allocation, Medical research

Streamflow drought index-based prediction of hydrological drought using M5P and gene expression programming models.

Autoren: Singh, Balraj Rai, Priya Singh, Sandeep et al.

Quelle: Applied Water Science; Aug2025, Vol. 15 Issue 8, p1-15, 15p

Schlagwörter: DROUGHT forecasting, WATER management, DROUGHTS, WATER shortages, STATISTICAL measurement

Geografische Kategorien: UTTARAKHAND (India), INDIA

Computer vision algorithms to help decision-making in cattle production.

Autoren: Guarnido-Lopez, P Pi, Y Tao, J et al.

Quelle: Animal Frontiers. Dec2024, Vol. 14 Issue 6, p11-22. 12p.

Predicting EGFR L858R/T790M/C797S Inhibitory Effect of Osimertinib Derivatives by Mixed Kernel SVM Enhanced with CLPSO.

Autoren: Li, Shaokang Dong, Wenzhe Qu, Aili

Quelle: Pharmaceuticals (14248247); Aug2025, Vol. 18 Issue 8, p1092, 22p

Schlagwörter: OSIMERTINIB, EPIDERMAL growth factor receptors, OPTIMIZATION algorithms, MOLECULAR docking, CHEMICAL inhibitors, SUPPORT vector machines, GENETIC mutation

Prediction of Maximum Scour Around Circular Bridge Piers Using Semi-Empirical and Machine Learning Models.

Autoren: Nandi, Buddhadev Das, Subhasish

Quelle: Water (20734441); Sep2025, Vol. 17 Issue 17, p2610, 30p

Schlagwörter: BRIDGE foundations & piers, MACHINE learning, ARTIFICIAL neural networks, STRUCTURAL reliability, EMPIRICAL research, HYDRAULIC measurements, PREDICTIVE validity

A Probabilistic Approach to Surrogate‐Assisted Multi‐Objective Optimization of Complex Groundwater Problems.

Autoren: Macasieb, Reygie Q. White, Jeremy T. Pasetto, Damiano et al.

Quelle: Water Resources Research; May2025, Vol. 61 Issue 5, p1-32, 32p

Schlagwörter: WATER management, GROUNDWATER management, KRIGING, COASTAL zone management, EVOLUTIONARY algorithms