scholarly journals A Hybrid Model Algorithm for Hypersonic Glide Vehicle Maneuver Tracking Based on the Aerodynamic Model

2017 ◽  
Vol 7 (2) ◽  
pp. 159 ◽  
Author(s):  
Yu Fan ◽  
Fang Lu ◽  
Wuxuan Zhu ◽  
Guangzhou Bai ◽  
Liang Yan
Keyword(s):  
Hybrid Model ◽  
Aerodynamic Model ◽  
Vehicle Maneuver ◽  
Model Algorithm

scholarly journals The Hybrid Model Algorithm on Sharia Insurance

2018 ◽  
Vol 1090 ◽  
pp. 012080
Author(s):  
Rini Cahyandari ◽  
Riva Lesta Ariany ◽  
Sukono ◽  
Yudha Satya Perkasa
Keyword(s):  
Hybrid Model ◽  
Model Algorithm

scholarly journals Surrogate Modelling for Wing Planform Multidisciplinary Optimisation Using Model-Based Engineering

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
G. Pagliuca ◽  
T. Kipouros ◽  
M. A. Savill
Keyword(s):  
Hybrid Model ◽  
Early Stage ◽  
Aircraft Design ◽  
Test Case ◽  
Lattice Method ◽  
Stage Design ◽  
Mass Estimation ◽  
Model Based ◽  
Aerodynamic Model ◽  
Early Stage Design

Optimisation is aimed at enhancing aircraft design by identifying the most promising wing planforms at the early stage while discarding the least performing ones. Multiple disciplines must be taken into account when assessing new wing planforms, and a model-based framework is proposed as a way to include mass estimation and longitudinal stability alongside aerodynamics. Optimisation is performed with a particle swarm optimiser, statistical methods are exploited for mass estimation, and the vortex lattice method (VLM) with empirical corrections for transonic flow provides aerodynamic performance. Three surrogates of the aerodynamic model are investigated. The first one is based on radial basis function (RBF) interpolation, and it relies on a precomputed database to evaluate the performance of new wing planforms. The second one is based on an artificial neural network, and it needs precomputed data for a training step. The third one is a hybrid model which switches automatically between VLM and RBF, and it does not need any precomputation. Its switching criterion is defined in an objective way to avoid any arbitrariness. The investigation is reported for a test case based on the common research model (CRM). Reference results are produced with the aerodynamic model based on VLM for two- and three-objective optimisations. Results from all surrogate models for the same benchmark optimisation are compared so that their benefits and limitations are both highlighted. A discussion on specific parameters, such as number of samples for example, is given for each surrogate. Overall, a model-based implementation with a hybrid model is proposed as a compromise between versatility and an arbitrary level of accuracy for wing early-stage design.

Classroom Lighting Energy-Saving Control System Based on Machine Vision Technology

2018 ◽  
pp. 143-149 ◽  
Author(s):  
Ruijie CHENG
Keyword(s):  
Control System ◽  
Machine Vision ◽  
Energy Saving ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Lighting Control ◽  
Lighting Energy ◽  
Neural Network Algorithm ◽  
Energy Saving Control ◽  
Model Algorithm

In order to further improve the energy efficiency of classroom lighting, a classroom lighting energy saving control system based on machine vision technology is proposed. Firstly, according to the characteristics of machine vision design technology, a quantum image storage model algorithm is proposed, and the Back Propagation neural network algorithm is used to analyze the technology, and a multi­feedback model for energy­saving control of classroom lighting is constructed. Finally, the algorithm and lighting model are simulated. The test results show that the design of this paper can achieve the optimization of the classroom lighting control system, different number of signals can comprehensively control the light and dark degree of the classroom lights, reduce the waste of resources of classroom lighting, and achieve the purpose of energy saving and emission reduction. Technology is worth further popularizing in practice.

Solow economy model

2019 ◽  
pp. 150-157
Author(s):  
Oleksandr Synenko ◽  
Kateryna Yarema ◽  
Yuliia Bezsmertna
Keyword(s):  
Economic Growth ◽  
Regression Analysis ◽  
Solow Model ◽  
Economy Model ◽  
Accelerated Depreciation ◽  
Basic Parameters ◽  
The Subject ◽  
Investment Process ◽  
The Impact ◽  
Model Algorithm

The subject of the research is the approach to the possibility of using the Solow model to perform the regression analysis on the example of the Ukrainian economy model. The purpose of writing this article is to investigate the notion of regres- sion analysis, Solow’s economy model, algorithm for performing regression analy- sis on the example of Ukraine’s economy model. This model can be adapted for the economy of enterprises. Methodology. The research methodology is system-struc- tural and comparative analyzes (to study the structure of GDP); monograph (when studying methods of regression analysis on the example of the Ukrainian economy); economic analysis (when assessing the impact of factors on Ukraine’s GDP). The scientific novelty consists the features of the use of the Solow model on the ex- ample of Ukrainian economy are determined. An algorithm for calculating the basic parameters of a model using the Excel application package is disclosed. The main recommendations on the development of the national economy and economic growth through the use of macroeconomic instruments are given. Conclusions. The use of the Solow model enables forecasting and analysis. The results obtained re- vealed the problem of low resource return of capital as a resource, along with the means of macroeconomic regulation of the investment process, using which can improve the situation. A special place in these funds belongs to the accelerated depreciation and interest rate policies.

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