A risk assessment based optimization method for route selection of hazardous liquid railway network

2018 ◽  
Vol 110 ◽  
pp. 217-229 ◽  
Author(s):  
Haoran Zhang ◽  
Meng Yuan ◽  
Yongtu Liang ◽  
Bohong Wang ◽  
Wan Zhang ◽  
...  
Author(s):  
Muhammad Ghifari Arfananda ◽  
◽  
Surya Michrandi Nasution ◽  
Casi Setianingsih ◽  
◽  
...  

The rapid development of information and technology, the city of Bandung tourism has also increased. However, tourists who visit the city of Bandung have problems with a limited time when visiting Bandung tourist attractions. Traffic congestion, distance, and the number of tourist destinations are the problems for tourists travel. The optimal route selection is the solution for those problems. Congestion and distance data are processed using the Simple Additive Weighting (SAW) method. Route selection uses the Floyd-Warshall Algorithm. In this study, the selection of the best route gets the smallest weight with a value of 5.127 from the Algorithm process. Based on testing, from two to five tourist attractions get an average calculation time of 3 to 5 seconds. This application is expected to provide optimal solutions for tourists in the selection of tourist travel routes.


Algorithms ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 163
Author(s):  
Yaru Li ◽  
Yulai Zhang ◽  
Yongping Cai

The selection of the hyper-parameters plays a critical role in the task of prediction based on the recurrent neural networks (RNN). Traditionally, the hyper-parameters of the machine learning models are selected by simulations as well as human experiences. In recent years, multiple algorithms based on Bayesian optimization (BO) are developed to determine the optimal values of the hyper-parameters. In most of these methods, gradients are required to be calculated. In this work, the particle swarm optimization (PSO) is used under the BO framework to develop a new method for hyper-parameter optimization. The proposed algorithm (BO-PSO) is free of gradient calculation and the particles can be optimized in parallel naturally. So the computational complexity can be effectively reduced which means better hyper-parameters can be obtained under the same amount of calculation. Experiments are done on real world power load data,where the proposed method outperforms the existing state-of-the-art algorithms,BO with limit-BFGS-bound (BO-L-BFGS-B) and BO with truncated-newton (BO-TNC),in terms of the prediction accuracy. The errors of the prediction result in different models show that BO-PSO is an effective hyper-parameter optimization method.


Marine Policy ◽  
2018 ◽  
Vol 88 ◽  
pp. 11-22 ◽  
Author(s):  
Stephen J. Newman ◽  
Joshua I. Brown ◽  
David V. Fairclough ◽  
Brent S. Wise ◽  
Lynda M. Bellchambers ◽  
...  

Author(s):  
Bing Yi ◽  
Renkai Sun ◽  
Long Liu ◽  
Yongfeng Song ◽  
Yinggui Zhang

Abstract It is a challenge for the dynamic inspection of railway route for freight car transporting cargo that out-of-gauge. One possible way is using the inspection frame installed in the inspection train to simulate the whole procedure for cargo transportation, which costs a lot of manpower and material resources as well as time. To overcome the above problem, this paper proposes an augmented reality (AR) based dynamic inspection method for visualized railway routing of freight car with out-of-gauge. First, the envelope model of the dynamic moving train with out-of-gauge cargo is generated by using the orbital spectrum of the railway, and the envelope model is matched with a piece of homemade calibration equipment located on the position of the railway that needs to be inspected. Then, the structure from motion (SFM) algorithm is used to reconstruct the environment where the virtual envelope model occludes the buildings or equipment along the railway. Finally, the distance function is adopted to calculate the distance between the obstacle and the envelope of the freight car with out-of-gauge, determining whether the freight car can pass a certain line. The experimental results show that the proposed method performs well for the route selection of out-of-gauge cargo transportation with low cost, high precision, and high efficiency. Moreover, the digital data of the environments along the railway and the envelope of the freight car can be reused, which will increase the digitalization and intelligence for route selection of out-of-gauge cargo transportation.


Chemosphere ◽  
1989 ◽  
Vol 19 (1-6) ◽  
pp. 615-622 ◽  
Author(s):  
Henk Heida ◽  
Martin Van Den Berg ◽  
Kees Olie

2018 ◽  
Vol 2 (2) ◽  
pp. 127-132
Author(s):  
Sapto Priyanto

The Government through the National Railway Master Plan has launched the development of the Airport Railway Network and Services to facilitate passenger mobility, one of which is the construction of the Adi Soemarmo Airport train. In April 2017 a groundbreaking project for the development of the Adi Soemarmo Airport, Boyolali District by the President of the Republic of Indonesia was scheduled to be operational in 2019. This study uses a discrete choice model to express the opportunities of each passenger to use the airport train. The research instruments were prepared using predictor variables developed from service dimensions according to Gaspers. The sample used was 200 respondents with random sampling techniques. The data collected is processed using a binary logical regression model because the response variable is in the form of a dichotomy. The results showed the accuracy of the train schedule and affordability of train fares affect the willingness to use airport trains.


Sign in / Sign up

Export Citation Format

Share Document