Comparative analysis of freight transport prognoses results provided by transport system model and neural network

2021 ◽  
Vol 31 (4) ◽  
pp. 239-259
Author(s):  
Vít Malinovský
Keyword(s):  
Neural Network ◽  
Comparative Analysis ◽  
Transport System ◽  
Freight Transport ◽  
System Model

Setting-up an audit system to implement the municipal component of national projects in Russia: The experience of control and accounts bodies

2020 ◽  
Vol 18 (12) ◽  
pp. 2224-2255
Author(s):  
A.I. Mordvintsev ◽  
N.E. Buletova ◽  
R.S. Dubov
Keyword(s):  
Comparative Analysis ◽  
Implementation Process ◽  
System Model ◽  
Audit System ◽  
Municipal Level

Subject. This article discusses the peculiarities of organizing and conducting audit by municipal control and accounts bodies and issues of cooperation between regional and municipal executors of national projects. Objectives. The article aims to identify the main characteristics of audit of the municipal component of national projects. Methods. For the study, we used the methods of comparative analysis, generalization, synthesis, classification, and grouping. Results. The article compares the terms of Control, Audit, and Monitoring, and presents an audit system model to implement the municipal component of national projects, describing individual steps and features of the implementation process. Conclusions. The problems identified in the implementation of the municipal component of national projects are related to the lack of strict centralization of this process and the usage of different mechanisms for the implementation of national projects at the municipal level.

Valid Signature Detection and Verification for Security of Individual Person

2016 ◽  
Vol 1 (1) ◽  
pp. 50-53 ◽  
Author(s):  
Varun Sharma ◽  
Narpat Singh
Keyword(s):  
Neural Network ◽  
Comparative Analysis ◽  
Recent Work ◽  
Research Work ◽  
Early Research ◽  
Individual Person ◽  
Signature Detection ◽  
Online Signature ◽  
The Right ◽  
Handwritten Signature

In the recent research work, the handwritten signature is a suitable field to detection of valid signature from different environment such online signature and offline signature. In early research work, a lot of unauthorized person put the signature and theft the data in illegal manner from organization or industries. So we have to need identify, the right person on the basis of various parameters that can be detected. In this paper, we have proposed two methods namely LDA and Neural Network for the offline signature from the scan signature image. For efficient research, we have focused the comparative analysis in terms of FRR, SSIM, MSE, and PSNR. These parameters are compared with the early work and the recent work. Our proposed work is more effective and provides the suitable result through our method which leads to existing work. Our method will help to find legal signature of authorized use for security and avoid illegal work.

Research on air pollution system based on neural network

2020 ◽  
pp. 1-11
Author(s):  
Zhiqi Jiang ◽  
Xidong Wang
Keyword(s):  
Neural Network ◽  
Air Pollution ◽  
Image Features ◽  
Air Pollutant ◽  
Pollution Monitoring ◽  
System Model ◽  
Process Data ◽  
Deep Convolutional Neural Networks ◽  
Air Pollution Monitoring ◽  
Neural Network Algorithm

This paper conducts in-depth research and analysis on the commonly used models in the simulation process of air pollutant diffusion. Combining with the actual needs of air pollution, this paper builds an air pollution system model based on neural network based on neural network algorithm, and proposes an image classification method based on deep learning and Gaussian aggregation coding. Moreover, this paper proposes a Gaussian aggregation coding layer to encode image features extracted by deep convolutional neural networks. Learn a fixed-size dictionary to represent the features of the image for final classification. In addition, this paper constructs an air pollution monitoring system based on the actual needs of the air system. Finally, this article designs a controlled experiment to verify the model proposed in this article, uses mathematical statistics to process data, and scientifically analyze the statistical results. The research results show that the model constructed in this paper has a certain effect.

Prediction of sports attendance: A comparative analysis

2020 ◽  
pp. 175433712098313
Author(s):  
Mehmet Şahin ◽  
Murat Uçar
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Comparative Analysis ◽  
National Football League ◽  
Relevant Literature ◽  
Performance Evaluations ◽  
Influential Factor ◽  
Gradient Boosting ◽  
Home Team ◽  
Machine Learning Methods

In this study, a comparative analysis for predicting sports attendance demand is presented based on econometric, artificial intelligence, and machine learning methodologies. Data from more than 20,000 games from three major leagues, namely the National Basketball Association (NBA), National Football League (NFL), and Major League Baseball (MLB), were used for training and testing the approaches. The relevant literature was examined to determine the most useful variables as potential regressors in forecasting. To reveal the most effective approach, three scenarios containing seven cases were constructed. In the first scenario, each league was evaluated separately. In the second scenario, the three possible combinations of league pairings were evaluated, while in the third scenario, all three leagues were evaluated together. The performance evaluations of the results suggest that one of the machine learning methods, Gradient Boosting, outperformed the other methods used. However, the Artificial Neural Network, deep Convolutional Neural Network, and Decision Trees also provided productive and competitive predictions for sports games. Based on the results, the predictions for the NBA and NFL leagues are more satisfactory than the predictions of the MLB, which may be caused by the structure of the MLB. The results of the sensitivity analysis indicate that the performance of the home team is the most influential factor for all three leagues.

Rail Transport Corridors of the Organisation for Co-operation of Railways

2021 ◽  
Vol 65 (191) ◽  
pp. 65-73
Author(s):  
Mirosław Antonowicz
Keyword(s):  
Emerging Markets ◽  
Transport System ◽  
Freight Transport ◽  
Continuous Operation ◽  
Rail Transport ◽  
Operational Parameters ◽  
Member States ◽  
One Belt One Road ◽  
Global Transport ◽  
International Transport

International transport corridors are part of the global transport system and are an important part of the activities of the Organisation for Co-operation of Railways2. The development activities in the Eurasian space are aimed at modernising and developing rail transport by upgrading the technical and operational parameters of the corridors in order to improve the competitiveness of railways in freight transport in Asia and Europe. These corridors are widely used to plan and organise the routing of container trains in international traffic between the OSJD member states. Today, nearly 300 container trains are in continuous operation. The aim of the article is to present the activities to date in the development of corridors, their role and importance in rail transport in the area of the member states of the Organisation for Co-operation of Railways. The article presents issues related to the development and freight transport on 13 international rail transport corridors from the Eurasian railway area. New corridor solutions were highlighted, as well as the New Silk Road3 which is part of China’s broader so-called One Belt, One Road Initiative concept. It is a global infrastructure plan developed in China and implemented in more than 100 countries, mainly in countries referred to as emerging markets. Keywords: international transport corridor, rail transport corridor, indicators for transport corridors, New Silk Road

scholarly journals Characteristics Analysis of Freight Mode Choice Model According to the Introduction of a New Freight Transport System

2019 ◽  
Vol 11 (4) ◽  
pp. 1209 ◽  
Author(s):  
Seungjin Shin ◽  
Hong-Seung Roh ◽  
Sung Hur
Keyword(s):  
Travel Time ◽  
Transport System ◽  
Choice Model ◽  
Stated Preference ◽  
Statistical Significance ◽  
Explanatory Power ◽  
Service Level ◽  
Freight Transport ◽  
Transport Cost ◽  
Transport Mode

The purpose of this study is to identify the characteristics of freight mode choices made by shippers and carriers with the introduction of a new freight transport system. We set an area in which actual freight transport takes place as the analysis scope and performed a survey of the shippers and carriers that transport containers to identify their stated preference (SP) regarding the new freight mode. The SP survey was carried out through an experimental design and this study considered the three factors of transport time, transport cost, and service level. This study compared and analyzed the models by distance using an individual behavior model. The results of estimating the model showed that the explanatory power of the model classified by distance and the individual parameters have statistical significance. The hit ratio was also high, which confirms that the model was estimated properly. In addition, the range of elasticity and the value of travel time analyzed using the model were evaluated to be appropriate compared to previous studies. The findings of the elasticity analysis show that strategies for reducing the transport cost are effective to increase the demand for the new transport mode. The value of travel time of freight transport was found to be higher than the current value generally applied in Korea. Considering that the value of travel time currently used is based on road freight transport, further research is required to apply a new value of travel time that reflects the characteristics of the new transport mode in the future.

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