类的关系有泛化(Generalization)、实现(Realization)、依赖(Dependency)和关联(Association)。其中关联又分为一般关联关系和聚合关系(Aggregation),合成关系(Composition)。下面我们结合实例理解这些关系。 基本概念 类图(Class Diagram): 类图是面向对象系统建模中最常用和最......
The perceptron learning algorithm guarantees that such a synaptic vector will be found, provided it exists, starting from any initial synaptic weight [93,119]. The algorithm is applied independently to all neurons i = 1,…,N. Consider neuron i as a perceptron with synaptic weight (Jij), j...
Workflow diagram of the bee colony. Full size image The basic model of the ABC algorithm includes four stages: the initialization stage, the employed bee stage, the onlooker bee stage, and the scout bee stage. Below is a detailed introduction to each stage of the artificial bee colony algorit...
Neural Network is a nature-inspired predictive algorithm which is rooted in statistical technique similar to Logistic Regression, designed to mimic the workings of human brain, and contains series of mathematical equations used to simulate biological process such as learning and memory. ANN structure co...
A common way to increase the neural network efficiency is to adjust its weights with the iterative learning algorithm, known as back-propagation [34]. 2.2. Local binary patterns Local Binary Pattern (LBP) is a texture descriptor firstly proposed by Ojala, Pietikainen, and Harwood in Ref. [...
Scatter diagram of typical fire and non-fire aerosols Full size image Fig. 7 The flow chart of aerosol sample data collection and preprocessing Full size image 6.2 Establishment of MLP classification models In the construction of MLP models, the details are given in Table 8. Four types of MLP...
The Taylor diagrams applied to prepare a visual comprehension into performance measures which plots a series of points on a polar plot for the two sets of modeling results: (1) 3 data points for MLP; (2) 3 data points for MLP–FFA and (3) the observed value. The Taylor diagram represen...
The utilization of a non-gradient optimization algorithm incurs significant computational costs and may potentially pose “curse of dimensionality” due to the population size and number of iterations. However, recent advancements in machine learning (ML) have led to the gradual replacement of traditiona...
Fig. 2. Block Diagram for CORADMO based SCET. 3.1. Fuzzy inference system Fuzzy has four main components: fuzzy input values, fuzzy rule base, fuzzy fuzzification, and fuzzy defuzzification. Fuzziness is used to convert the network's sharp values into fuzzy ones. This process is known as fuz...
FIG.9is a schematic block diagram of a magnetic resonance imaging system, according to an exemplary implementation of the present disclosure. DETAILED DESCRIPTION To overcome the above challenges, the present disclosure uses a conditional unrolled architecture, termed Meta-MoDL. In one embodiment, the...