scholarly journals A Scheduling Model of Isochronous Frame Generation on Self-similar Traffic of AOS Multiplexing

2018 ◽  
Vol 14 (07) ◽  
pp. 15 ◽  
Author(s):  
Yuntao Zhao ◽  
Lishi Liu

As the first layer of AOS multiplexing, the frame scheduling performance has a great effect on the efficiency of multiplexing. Traditional researches about the scheduling model mainly focus on the source packet arrival model of Poisson process. In this paper, an ON/OFF source arrival model and Pareto distribution of AOS multiplexing in self-similar service traffic is used to establish a isochronous frame-generated method through rigorous theoretical analysis, which results in a calculable formula of average packet delay and MPDU average multiplex efficiency. According to simulation of MATLAB, the simulation curve coincides with that of theory. The novel model contributes to the improvement of average packet delay and MPDU average multiplex efficiency on AOS.

2021 ◽  
Vol 40 (5) ◽  
pp. 10043-10061
Author(s):  
Xiaoping Shi ◽  
Shiqi Zou ◽  
Shenmin Song ◽  
Rui Guo

 The asset-based weapon target assignment (ABWTA) problem is one of the important branches of the weapon target assignment (WTA) problem. Due to the current large-scale battlefield environment, the ABWTA problem is a multi-objective optimization problem (MOP) with strong constraints, large-scale and sparse properties. The novel model of the ABWTA problem with the operation error parameter is established. An evolutionary algorithm for large-scale sparse problems (SparseEA) is introduced as the main framework for solving large-scale sparse ABWTA problem. The proposed framework (SparseEA-ABWTA) mainly addresses the issue that problem-specific initialization method and genetic operators with a reward strategy can generate solutions efficiently considering the sparsity of variables and an improved non-dominated solution selection method is presented to handle the constraints. Under the premise of constructing large-scale cases by the specific case generator, two numerical experiments on four outstanding multi-objective evolutionary algorithms (MOEAs) show Runtime of SparseEA-ABWTA is faster nearly 50% than others under the same convergence and the gap between MOEAs improved by the mechanism of SparseEA-ABWTA and SparseEA-ABWTA is reduced to nearly 20% in the convergence and distribution.


2005 ◽  
Vol 9 (3) ◽  
pp. 273-275
Author(s):  
A. Gkelias ◽  
M. Dohler ◽  
V. Friderikos ◽  
A.H. Aghvami

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yitong Liu ◽  
Yang Yang ◽  
Dingyu Xue ◽  
Feng Pan

PurposeElectricity consumption prediction has been an important topic for its significant impact on electric policies. Due to various uncertain factors, the growth trends of electricity consumption in different cases are variable. However, the traditional grey model is based on a fixed structure which sometimes cannot match the trend of raw data. Consequently, the predictive accuracy is variable as cases change. To improve the model's adaptability and forecasting ability, a novel fractional discrete grey model with variable structure is proposed in this paper.Design/methodology/approachThe novel model can be regarded as a homogenous or non-homogenous exponent predicting model by changing the structure. And it selects the appropriate structure depending on the characteristics of raw data. The introduction of fractional accumulation enhances the predicting ability of the novel model. And the relative fractional order r is calculated by the numerical iterative algorithm which is simple but effective.FindingsTwo cases of power load and electricity consumption in Jiangsu and Fujian are applied to assess the predicting accuracy of the novel grey model. Four widely-used grey models, three classical statistical models and the multi-layer artificial neural network model are taken into comparison. The results demonstrate that the novel grey model performs well in all cases, and is superior to the comparative eight models.Originality/valueA fractional-order discrete grey model with an adaptable structure is proposed to solve the conflict between traditional grey models' fixed structures and variable development trends of raw data. In applications, the novel model has satisfied adaptability and predicting accuracy.


2021 ◽  
Author(s):  
Stanley Oifoghe ◽  
Nora Alarcon ◽  
Lucrecia Grigoletto

Abstract Hydrocarbons are bypassed in known fields. This is due to reservoir heterogeneities, complex lithology, and limitations of existing technology. This paper seeks to identify the scenarios of bypassed hydrocarbons, and to highlight how advances in reservoir characterization techniques have improved assessment of bypassed hydrocarbons. The present case study is an evaluation well drilled on the continental shelf, off the West African Coastline. The targeted thin-bedded reservoir sands are of Cenomanian age. Some technologies for assessing bypassed hydrocarbon include Gamma Ray Spectralog and Thin Bed Analysis. NMR is important for accurate reservoir characterization of thinly bedded reservoirs. The measured NMR porosity was 15pu, which is 42% of the actual porosity. Using the measured values gave a permeability of 5.3mD as against the actual permeability of 234mD. The novel model presented in this paper increased the porosity by 58% and the permeability by 4315%.


2009 ◽  
Vol 12 (4) ◽  
pp. 18-29
Author(s):  
Thanh Diep Cong Tu

In recent years, CPM - Continuous Passive Motion has been proved to be one of the most effective therapeutic methods for patients who have problems with motion such as spinal cord injury, ankle and knee injury, parkinson and so on. Many commercial CPM devices are found in market but all of them use motors as the main actuators. The lack of human compliance of electric actuators, which are commonly used in these machines, makes them potentially harmful to patients. An interesting alternative, to electric actuators for medical purposes, particularly promising for rehabilitation, is a pneumatic artificial muscle (PAM) actuator because of its high power/weight ratio and compliance properties. However, the highly nonlinear and hysteresis of PAM make it the challenging for design and control. In this study, a PID compensation using neural network control is studied to improve the control performance of the novel model of Knee CPM device.


2020 ◽  
Vol 57 (9) ◽  
pp. 091401
Author(s):  
石郑楠 Shi Zhengnan ◽  
延凤平 Yan Fengping ◽  
韩文国 Han Wenguo ◽  
张鲁娜 Zhang Luna

2013 ◽  
Vol 738 ◽  
pp. 141-144
Author(s):  
Guo Fang Kuang ◽  
Zhao Feng Sun

New building materials variety and yield is developing with hitherto unknown speed, construction engineering development if the effective use of new building materials will be excellent performance of new technology. Novel building materials can significantly reduce the weight of buildings, to promote the light construction structure created the conditions. IPv6 is not only a good solution to the problem of the lack of IP address, but also due to the introduction of encryption and authentication mechanisms to make it a better improvement in the network. The paper presents the novel model of building and energy engineering based on IPv6 technology. Experimental results show that the proposed method has high efficiency.


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