AIMC Topic: Computer Simulation
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Large Tanker Motion Model Identification Using Generalized Ellipsoidal Basis Function-Based Fuzzy Neural Networks.
IEEE transactions on cybernetics
Jan 1, 2015
In this paper, the motion dynamics of a large tanker is modeled by the generalized ellipsoidal function-based fuzzy neural network (GEBF-FNN). The reference model of tanker motion dynamics in the form of nonlinear difference equations is established ...
Neural network for constrained nonsmooth optimization using Tikhonov regularization.
Neural networks : the official journal of the International Neural Network Society
Dec 31, 2014
This paper presents a one-layer neural network to solve nonsmooth convex optimization problems based on the Tikhonov regularization method. Firstly, it is shown that the optimal solution of the original problem can be approximated by the optimal solu...
Comparison of two simulation systems to support robotic-assisted surgical training: a pilot study (Swine model).
Journal of minimally invasive gynecology
Dec 24, 2014
OBJECTIVE: To compare the efficacy of simulation-based training between the Mimic dV- Trainer and traditional dry lab da Vinci robot training.
Adaptive control of uncertain nonaffine nonlinear systems with input saturation using neural networks.
IEEE transactions on neural networks and learning systems
Dec 19, 2014
This paper presents a tracking control methodology for a class of uncertain nonlinear systems subject to input saturation constraint and external disturbances. Unlike most previous approaches on saturated systems, which assumed affine nonlinear syste...
Incorporating Wind Power Forecast Uncertainties Into Stochastic Unit Commitment Using Neural Network-Based Prediction Intervals.
IEEE transactions on neural networks and learning systems
Dec 18, 2014
Penetration of renewable energy resources, such as wind and solar power, into power systems significantly increases the uncertainties on system operation, stability, and reliability in smart grids. In this paper, the nonparametric neural network-base...
RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease.
Science (New York, N.Y.)
Dec 18, 2014
To facilitate precision medicine and whole-genome annotation, we developed a machine-learning technique that scores how strongly genetic variants affect RNA splicing, whose alteration contributes to many diseases. Analysis of more than 650,000 intron...
Genetic Code
MutL Protein Homolog 1
RNA Splice Sites
Genetic Markers
Humans
Nuclear Proteins
Child Development Disorders, Pervasive
Mutation, Missense
Genetic Variation
Artificial Intelligence
Adaptor Proteins, Signal Transducing
Colorectal Neoplasms, Hereditary Nonpolyposis
Quantitative Trait Loci
Genome-Wide Association Study
Molecular Sequence Annotation
Computer Simulation
DNA
Muscular Atrophy, Spinal
RNA Splicing
Polymorphism, Single Nucleotide
Introns
Exons
RNA-Binding Proteins
Models, Genetic
Online monitoring and control of particle size in the grinding process using least square support vector regression and resilient back propagation neural network.
ISA transactions
Dec 17, 2014
Particle size soft sensing in cement mills will be largely helpful in maintaining desired cement fineness or Blaine. Despite the growing use of vertical roller mills (VRM) for clinker grinding, very few research work is available on VRM modeling. Thi...
Ten-dimensional anthropomorphic arm control in a human brain-machine interface: difficulties, solutions, and limitations.
Journal of neural engineering
Dec 16, 2014
OBJECTIVE: In a previous study we demonstrated continuous translation, orientation and one-dimensional grasping control of a prosthetic limb (seven degrees of freedom) by a human subject with tetraplegia using a brain-machine interface (BMI). The cur...
Improving propensity score estimators' robustness to model misspecification using super learner.
American journal of epidemiology
Dec 16, 2014
The consistency of propensity score (PS) estimators relies on correct specification of the PS model. The PS is frequently estimated using main-effects logistic regression. However, the underlying model assumptions may not hold. Machine learning metho...
Mode-dependent stochastic stability criteria of fuzzy Markovian jumping neural networks with mixed delays.
ISA transactions
Dec 12, 2014
This paper investigates the stochastic stability of fuzzy Markovian jumping neural networks with mixed delays in mean square. The mixed delays include time-varying delay and continuously distributed delay. By using the Lyapunov functional method, Jen...
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