Comprehensive simulations are conducted both in single and multi-layer networks to investigate the learning performance of our algorithm, whose results demonstrate that our algorithm possesses higher learning efficiency and stronger parameter robustness than traditional algorithms....
Soft sensors, functioning as virtual instruments, utilize algorithms and computational models to estimate unobservable or impractical values by processing data derived from physical sensors [1,2]. In the Internet of Things (IoT) domain, where obtaining direct measurements can often be impractical or ec...
13 used four machine learning algorithms, SVR, MLP, GBR, and XGBoost, to predict the compressive and tensile strength of HPC. Comparative studies showed that based on the GBR and XGBoost training models, the performance was better than that of the models based on SVR and MLP for this ...
Pacific Defense, alongside its affiliate Perceptronics, has been awarded a follow-on contract by the Air Force Life Cycle Management Center (AFLCMC) for the development of advanced Electronic Warfare (EW) mission systems. This contract expands on previou
Wildfire susceptibility mapping using two empowered machine learning algorithms Article 14 July 2022 Innovative SVM optimization with differential gravitational fireworks for superior air pollution classification Article Open access 18 October 2024 1
In this study, we propose a dynamical memory strategy to efficiently control the size of the support set in a kernel-based Perceptron learning algorithm. T... W He - 《Neural Networks》 被引量: 0发表: 2011年 Residual Algorithms: Reinforcement Learning with Function Approximation approximation sys...
In literature, the independent implementation of supervised or unsupervised learning algorithms over the years in various fault classification task has been proven to yield some level of satisfactory results [5]. However, these two major forms of learning possess their strength and limitations. For ins...
Data-driven algorithms provide advanced alternatives with statistical inference and machine learning techniques [6, 7]. In recent years, data-driven soft sensors including principal component regression (PCR), partial least squares (PLS) regression, support vector machine (SVM), extreme learning machine...
An optical realization of a single layer pattern classifier is described in which Perceptron learning is implemented to train the system weights. Novel use... JH Hong,S Campbell,P Yeh - 《Applied Optics》 被引量: 113发表: 1990年 Steady-state analysis of a single-layer perceptron based on a...
Standard machine learning algorithms have limited knowledge extraction capability in discriminating cancer stages based on genomic characterizations, due to the strongly correlated nature of high-dimensional genomic data. Moreover, activation of pathways