A Novel Dynamic Dispatching Method for Bicycle-Sharing System

Mao, Dianhui; Hao, Zhihao; Wang, Yalei; Fu, Shuting

doi:10.3390/ijgi8030117

Cited by 9 publications

(6 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For food transactions safety, a blockchain-based food transaction system has been developed in [ 12 ] to ensure the transparency of the transactions, with the effectiveness of this system also verified in [ 13 ]. For food quality and safety, a blockchain-based visualization method according to [ 14 , 15 ] has been proposed to trace the source of problematic products and observe the flow of related risks [ 16 ]. The data in the blockchain can provide a basis for precise regulations, but there is currently a lack of suitable data analysis methods to maximize the effect of the data recorded in the blockchain.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

A Novel Method for Food Market Regulation by Emotional Tendencies Predictions from Food Reviews Based on Blockchain and SAEs

Hao

Wang

Mao

et al. 2021

Foods

Self Cite

View full text Add to dashboard Cite

As a part of food safety research, researches on food transactions safety has attracted increasing attention recently. Food choice is an important factor affecting food transactions safety: It can reflect consumer preferences and provide a basis for market regulation. Therefore, this paper proposes a food market regulation method based on blockchain and a deep learning model: Stacked autoencoders (SAEs). Blockchain is used to ensure the fairness of transactions and achieve transparency within the transaction process, thereby reducing the complexity of the trading environment. In order to enhance the usability, relevant Web pages have been developed to make it more friendly and conduct a security analysis for using blockchain. Consumers’ reviews after the transactions are finished can be used to train SAEs in order to perform emotional tendencies predictions. Compared with different advanced models for predictions, the test results show that SAEs have a better performance. Furthermore, in order to provide a basis for the formulation of regulation strategies and its related policies, case studies of different traders and commodities have also been conducted, proving the effectiveness of the proposed method.

show abstract

Section: Theoretical Backgroundmentioning

confidence: 99%

A Novel Method for Food Market Regulation by Emotional Tendencies Predictions from Food Reviews Based on Blockchain and SAEs

Hao

Wang

Mao

et al. 2021

Foods

Self Cite

View full text Add to dashboard Cite

show abstract

“…Accurate prediction of bicycle rental demand is an important prerequisite for public bicycle dispatching and PBS system rebalancing [15,22]. In [16], Mimura et al proposed a time-series generation model to predict the number of bicycle transfers per hour and the bicycle rental demand.…”

Section: Related Workmentioning

confidence: 99%

Dynamic Bicycle Dispatching of Dockless Public Bicycle-sharing Systems Using Multi-objective Reinforcement Learning

Chen

et al. 2021

ACM Trans. Cyber-Phys. Syst.

View full text Add to dashboard Cite

As a new generation of Public Bicycle-sharing Systems (PBS), the Dockless PBS (DL-PBS) is an important application of cyber-physical systems and intelligent transportation. How to use artificial intelligence to provide efficient bicycle dispatching solutions based on dynamic bicycle rental demand is an essential issue for DL-PBS. In this article, we propose MORL-BD, a dynamic bicycle dispatching algorithm based on multi-objective reinforcement learning to provide the optimal bicycle dispatching solution for DL-PBS. We model the DL-PBS system from the perspective of cyber-physical systems and use deep learning to predict the layout of bicycle parking spots and the dynamic demand of bicycle dispatching. We define the multi-route bicycle dispatching problem as a multi-objective optimization problem by considering the optimization objectives of dispatching costs, dispatch truck's initial load, workload balance among the trucks, and the dynamic balance of bicycle supply and demand. On this basis, the collaborative multi-route bicycle dispatching problem among multiple dispatch trucks is modeled as a multi-agent and multi-objective reinforcement learning model. All dispatch paths between parking spots are defined as state spaces, and the reciprocal of dispatching costs is defined as a reward. Each dispatch truck is equipped with an agent to learn the optimal dispatch path in the dynamic DL-PBS network. We create an elite list to store the Pareto optimal solutions of bicycle dispatch paths found in each action, and finally get the Pareto frontier. Experimental results on the actual DL-PBS show that compared with existing methods, MORL-BD can find a higher quality Pareto frontier with less execution time.

show abstract

“…The heat map will show different results over time. In order to measure this, we built a 3D model similar to [39,40]. Figure 7 shows the results of the heat map changes from June to December 2016.…”

Section: An Example Of Using Aquatic Products Datamentioning

confidence: 99%

A Novel Visual Analysis Method of Food Safety Risk Traceability Based on Blockchain

Hao

Mao

Zhang

et al. 2020

IJERPH

Self Cite

View full text Add to dashboard Cite

Current food traceability systems have a number of problems, such as data being easily tampered with and a lack of effective methods to intuitively analyze the causes of risks. Therefore, a novel method has been proposed that combines blockchain technology with visualization technology, which uses Hyperledger to build an information storage platform. Features such as distribution and tamper-resistance can guarantee the authenticity and validity of data. A data structure model is designed to implement the data storage of the blockchain. The food safety risks of unqualified detection data can be quantitatively analyzed, and a food safety risk assessment model is established according to failure rate and qualification deviation. Risk analysis used visual techniques, such as heat maps, to show the areas where unqualified products appeared, with a migration map and a force-directed graph used to trace these products. Moreover, the food sampling data were used as the experimental data set to test the validity of the method. Instead of difficult-to-understand and highly specialized food data sets, such as elements in food, food sampling data for the entire year of 2016 was used to analyze the risks of food incidents. A case study using aquatic products as an example was explored, where the results showed the risks intuitively. Furthermore, by analyzing the reasons and traceability processes effectively, it can be proven that the proposed method provides a basis to formulate a regulatory strategy for regions with risks.

show abstract

A Novel Dynamic Dispatching Method for Bicycle-Sharing System

Cited by 9 publications

References 31 publications

A Novel Method for Food Market Regulation by Emotional Tendencies Predictions from Food Reviews Based on Blockchain and SAEs

A Novel Method for Food Market Regulation by Emotional Tendencies Predictions from Food Reviews Based on Blockchain and SAEs

Dynamic Bicycle Dispatching of Dockless Public Bicycle-sharing Systems Using Multi-objective Reinforcement Learning

A Novel Visual Analysis Method of Food Safety Risk Traceability Based on Blockchain

Contact Info

Product

Resources

About