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Call Center Model
The queuing system in this chapter is shown in Fig. 10.1. This application was adopted from an example in [1]. -
Emergency Room Model
The system in this chapter was adapted from an example in [1]. The flow through the system is shown in Fig. 13.1. Patients arrive, according to the... -
Fuzzy Sets
In this chapter we have collected together the basic ideas from fuzzy sets and fuzzy functions needed for the book. Any reader familiar with fuzzy... -
Oil Tanker Problem
This model has been adapted from an example in [5]. The system is shown in Fig. 18.1. This figure shows one cycle for an oil tanker. Let us follow an... -
Preemptive Service
A small city has a small municipal garage that does maintenance and repair on city owned vehicles. There are two types of vehicles: (1) TYPE 1 is the... -
Supermarket Model
The flow through this supermarket is shown in Fig. 21.1. This model is adapted after an example in [1]. We first describe the crisp system. Customers... -
Process Failure/Spare Parts Problem
A process in a manufacturing plant contains a very important part, which we shall now call the (spare) PART, which can fail from time to time. When... -
Fuzzy Systems Theory
In this chapter we consider systems whose performance depends on probability distributions and some of the parameters in these probability... -
13 Random Vibrations of Multi-Story Structures
The procedure described in Sec.11 is now applied to both a multi degree of freedom system (12-story building, 36 degrees of freedom) and a large... -
1 Objectives
Complex deterministic systems under deterministic loading are generally analyzed by the finite element method. This is mainly due to the most... -
B Lyapunov Matrix Differential Equation
The state space equation of the system defined in (6.18) is given by, see e.g. [91],... -
MDGCL: Graph Contrastive Learning Framework with Multiple Graph Diffusion Methods
In recent years, some classical graph contrastive learning(GCL) frameworks have been proposed to address the problem of sparse labeling of graph data...
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Parameters optimization and precision enhancement of Takagi–Sugeno fuzzy neural network
Takagi–Sugeno fuzzy neural network (TSFNN) has been widely used in intelligent prediction. The prediction accuracy of TSFNN is impacted by its model...
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Forecasting short- and medium-term streamflow using stacked ensemble models and different meta-learners
Streamflow forecasting holds a pivotal role in the effective management of water resources, flood control, hydropower generation, agricultural...
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Fake and propaganda images detection using automated adaptive gaining sharing knowledge algorithm with DenseNet121
An additional tool for swaying public opinion on social media is to present recent developments in the creation of natural language. The term “Deep...
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Quantifying the stochastic trends of climate extremes over Yemen: a comprehensive assessment using ERA5 data
Climate change is worsening existing vulnerabilities in develo** countries such as Yemen. This study examined the spatial distribution trends of...
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Subgraph generation applied in GraphSAGE deal with imbalanced node classification
In graph neural network applications, GraphSAGE applies inductive learning and has been widely applied in important research topics such as node...
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High pressure suppression of plasticity due to an overabundance of shear embryo formation
High pressure shear band formation is a critical phenomenon in energetic materials due to its influence on both mechanical strength and...
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Statistical inference on multicomponent stress–strength reliability with non-identical component strengths using progressively censored data from Kumaraswamy distribution
In this article, we draw inferences on stress–strength reliability in a multicomponent system with non-identical strength components based on the...