A Dual Attention-Based Recurrent Neural Network for Short-Term Bike Sharing Usage Demand Prediction.pdf

•

0 likes•4 views

https://okokprojects.com/ IEEE PROJECTS 2023-2024 TITLE LIST WhatsApp : +91-8144199666 From Our Title List the Cost will be, Mail Us: okokprojects@gmail.com Website: : https://www.okokprojects.com : http://www.ieeeproject.net Support Including Packages ======================= * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Video Tutorials * Supporting Softwares Support Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * Remote Connectivity * Document Customization * Live Chat Support

A Dual Attention
Network for Short
Usage Demand Prediction
Abstract
Improved network technology and data openness have generated a large
number of trajectory-based data, and trajectory
to provide consecutive and effective development and optimization for
intelligent transportation systems (ITS). Bike
increasingly important in the traffic planning, management, and deployment of
ITS. Therefore, it is crucial to determine how trajectory data are best used to
accurately predict the demand for short
proposed a recurrent neural network (RNN) model based on the dual attention
mechanism to extract spatial and
is able to determine and weight all location features of the data in time series
to learn mutual correlations. The method applied in this paper can effectively
conduct an adaptive combination of local
for trajectory data, in order to effectively predict the trend of short
A Dual Attention-Based Recurrent Neural
Network for Short-Term Bike Sharing
Usage Demand Prediction
Improved network technology and data openness have generated a large
based data, and trajectory-based knowledge graphs help
to provide consecutive and effective development and optimization for
intelligent transportation systems (ITS). Bike-sharing systems (BSS) are
increasingly important in the traffic planning, management, and deployment of
refore, it is crucial to determine how trajectory data are best used to
accurately predict the demand for short-term bike sharing usage. This study
proposed a recurrent neural network (RNN) model based on the dual attention
mechanism to extract spatial and temporal features. The attention mechanism
is able to determine and weight all location features of the data in time series
to learn mutual correlations. The method applied in this paper can effectively
conduct an adaptive combination of local- and global-feature dependencies
for trajectory data, in order to effectively predict the trend of short
Based Recurrent Neural
Term Bike Sharing
Improved network technology and data openness have generated a large
ased knowledge graphs help
to provide consecutive and effective development and optimization for
sharing systems (BSS) are
increasingly important in the traffic planning, management, and deployment of
refore, it is crucial to determine how trajectory data are best used to
term bike sharing usage. This study
proposed a recurrent neural network (RNN) model based on the dual attention
temporal features. The attention mechanism
is able to determine and weight all location features of the data in time series
to learn mutual correlations. The method applied in this paper can effectively
feature dependencies
for trajectory data, in order to effectively predict the trend of short-term bike

sharing usage demand. In addition, this study adopted the random walk
mechanism to maintain local relations between bike stations in the
preprocessing of time series data, which makes it more adaptive to the local
location changes of different stations. Finally, the experimental results show
that the model architecture in this study combined the attention and random
walk mechanisms to achieve better prediction performance.

Travel time prediction plays an important role in the research domain of Advanced Traveler Information Systems (ATIS). Clustering approach can be acted as one of the powerful tools to discover hidden knowledge that can easily be applied on historical traffic data to predict accurate travel time. In our proposed Naïve Clustering Approach (NCA), we partition a set of historical traffic data into several groups (also known as clusters) based on travel time, frequency of travel time and velocity for a specific road segment, day group and time group. In each cluster, data objects are similar to one another and are sufficiently different from data objects of other groups. To choose centroid of a cluster, we introduce a new method namely, Cumulative Cloning Average. For experimental evaluation, comparison is also focused to the forecasting results of other four methods namely, Rule Based method, Naïve Bayesian Classification (NBC) method, Successive Moving Average (SMA) and Chain Average (CA) by using same set of historical travel time estimates. The results depict that the travel time for the study period can be predicted by the proposed strategy with the minimum Mean Absolute Relative Errors (MARE) and Mean Absolute Errors (MAE).

Application Of Long Short Term Memory Networks For Long- And Short-Term Bus T...

Deja Lewis

This document discusses applying long short-term memory networks (LSTM) and multilayer perceptron neural networks (MLP) to predict bus travel times using one year of data from a bus route in Blacksburg, Virginia. The models were tested on travel times between successive stations, including dwell times. Additional models were developed for segments with and without traffic controls. The results showed that LSTM models outperformed MLP models with a lower root mean squared error (RMSE) of 17.69 seconds compared to 18.81 seconds. When splitting the data into controlled and uncontrolled segments, the LSTM model achieved a lower RMSE of 17.33 seconds for controlled segments and 4.28 seconds for uncontrolled segments, outperforming the MLP model.

Performance Evaluation of Efficient Data Dissemination Approach For QoS Enha...

IJCSIS Research Publications

Vehicular ad hoc networks (VANETs) have seen tremendous growth in the last decade, providing a vast range of applications in both military and civilian activities. The temporary connectivity in the vehicles can also increase the driver’s capability on the road. However, such applications require heavy data packets to be shared on the same spectrum without the requirement of excessive radios. Thus, e-client approaches are required which can provide improved data dissemination along with the better quality of services to allow heavy traffic to be easily shared between the vehicles. In this paper, an e-client data dissemination approach is proposed which not only improves the vehicle to vehicle connectivity but also improves the QoS between the source and the destination. The proposed approach is analyzed and compared with the existing state-of-the-art approaches. The effectiveness of the proposed approach is demonstrated in terms of the significant gains attained in the parameters namely, end to end delay, packet delivery ratio, route acquisition time, throughput, and message dissemination rate in comparison with the existing approaches.

Optimal Coverage Path Planningin a Wireless Sensor Network for Intelligent Tr...

IJCNCJournal

With the enhancement of the intelligent and communication technology, an intelligent transportation plays a vital role to facilitate an essential service to many people, allowing them to travel quickly and conveniently from place to place. Wireless sensor networks (WSNs) are well-known for their ability to detect physical significant barriers due to their diverse movement, self-organizing capabilities, and the integration of this mobile node on the intelligent transportation system to gather data in WSN contexts is becoming more and more popular as these vehicles proliferate. Although these mobile devices might enhance network performance, however it is difficult to design a suitable transportation path with the limited energy resources with network connectivity. To solve this problem, we have proposed a novel itinerary planning schema data gatherer (IPS-DG) model. Furthermore, we use the path planning module (PPM) which finds the transportation path to travel the shortest distance. We have compared our results under different aspect such as life span, energy consumption, and path length with Low Energy Adaptive Clustering Hierarchy (LEACH), Multi-Hop Weighted Revenue (MWR), Single-Hop Data Gathering Procedure (SHDGP). Our model outperforms in terms of energy usage, shortest path, and longest life span of with LEACH, MWR, SHDGP routing protocols.

Optimal Coverage Path Planning in a Wireless Sensor Network for Intelligent T...

IJCNCJournal

Cooperative positioning and tracking in disruption tolerant networks

JPINFOTECH JAYAPRAKASH

This document proposes methods for positioning and tracking mobile devices in disruption tolerant networks (DTNs) where fixed reference points are sparse. It proposes PulseCounting, a decentralized cooperative method that uses step counts and orientations from an accelerometer and compass to estimate location. Location estimates are refined during encounters when nodes exchange information. It also proposes ProbTracking, a probabilistic method that uses a Markov chain to determine the most probable movement trajectory based on partial location information exchanged between nodes. The methods were implemented on Android phones and tested on a university campus with an average positioning error of 9m compared to GPS.

Location and Mobility Optimized On-demand Geographical Multipath Routing Prot...

Eswar Publications

The advancement of science and technology had made mobile ad hoc network an important tool to access network of next generation. Recently, numerous multipath routing protocols for mobile ad hoc network are reported in literature. Each routing methods works based on their salient feature, but failed to control congestion, energy efficiency, overhead packets, signal stability during data transmission which leads to edge effect, signal decay and bottleneck situation of the bandwidth consumption. In this paper a novel approach havely Geographical Distance based Ad Hoc On-demand Distance Vector Routing (GD-AOMDV), which selects the path based on transmission distance value to limit and control the congestion and control overheads has been proposed. The salient feature of the proposed model is that it establishes a relationship between path distance and MANET design parameters including transmission range, consumption of energy and bandwidth. The accuracy of the proposed scheme is analyzed and validated with the experimental results in respect to various flow using NS2 simulations.

Handover Algorithm based VLP using Mobility Prediction Database for Vehicular...

IJECEIAES

This paper proposes an improved handover algorithm method for vehicle location prediction (VLP-HA) using mobility prediction database. The main advantage of this method is the mobility prediction database is based on real traffic data traces. Furthermore, the proposed method has the ability to reduce handover decision time and solve resource allocation problem. The algorithm is simple and can be computed very rapidly; thus, its implementation for a high-speed vehicle is possible. To evaluate the effectiveness of the proposed method, QualNet simulation is carried out under different velocity scenarios. Its performance is compared with conventional handover method. The superiority of the proposed method over conventional handover method in deciding the best handover location and choosing candidate access points is highlighted by simulation. It was found that VLP-HA has clearly reduced handover delay by 45% compared to handover without VLP, give high accuracy, hence low complexity algorithm.

1) The document proposes a new energy-aware tree-based routing protocol for wireless sensor networks called Fast Convergence and Quick Route Updates Based Energy Aware Tree-Based Routing Protocol. 2) The protocol uses AODV routing to select paths based on distance and residual energy of sensor nodes. It performs load balancing to increase network lifetime. 3) The protocol was tested in NS-2 simulator and showed improvements in network lifetime, throughput, data loss and delay compared to existing models.

A Fast Convergence and Quick Route Updates Based Energy Aware Tree-Based Rout...

iosrjce

IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.

APPLICABILITY OF CROWD SOURCING TO DETERMINE THE BEST TRANSPORTATION METHOD B...

IJDKP

Traffic is one of the most significant problem in Sri Lanka. Valuable time can be saved if there is a proper way to predict the traffic and recommend the best route considering the time factor and the people’s satisfaction on various transportation methods. Therefore, in this research using location awareness applications installed in mobile devices, data related to user mobility were collected by using crowdsourcing techniques and studied. Based on these observations an algorithm has been developed to overcome the problem. By using this, the best transportation method can be predicted as the results of the research. Therefore, people can choose what will be the best time slots & transportation methods when planning journeys. Throughout this research it has been proven that for the Sri Lankan context, the data mining concepts together with crowdsourcing can be applied to determine the best transportation method.

APPLICABILITY OF CROWD SOURCING TO DETERMINE THE BEST TRANSPORTATION METHOD B...

IJDKP

COVERAGE OPTIMIZED AND TIME EFFICIENT LOCAL SEARCH BETWEENNESS ROUTING FOR HE...

ijcsa

The document proposes a Local Search and Enhanced Betweenness Routing (LS-EBR) model for wireless sensor networks used for health monitoring. The LS-EBR model aims to improve routing efficiency by increasing sensor node coverage and minimizing routing time. It uses a local search algorithm based on greedy forwarding to route packets to neighboring nodes that are closest to the destination while also considering the reliability of sensor nodes. An enhanced betweenness routing algorithm is also used to measure energy consumption and select routes that consider both routing overhead and remaining energy of sensor nodes. Simulation results showed the LS-EBR model achieved higher coverage and improved routing efficiency compared to opportunistic routing.

Certain Analysis on Traffic Dataset based on Data Mining Algorithms

IRJET Journal

The document analyzes a traffic accident dataset using data mining algorithms to identify patterns and relationships that can provide safe driving suggestions. It applies association rule mining, classification using naive Bayes, and k-means clustering. The analysis finds that human factors like being drunk or collision type have a stronger effect on accident fatality than environmental factors. Clustering identifies regions with higher or lower fatality rates. Integrating additional data could enable more testing and safety suggestions.

Trajectory improves data delivery in urban vehicular networks

Papitha Velumani

This document discusses how using vehicle trajectory data can improve data delivery in urban vehicular networks. Existing algorithms for data delivery have relied on coarse-grained mobility patterns, but analyzing vehicle trace data from Shanghai and Shenzhen reveals strong spatiotemporal regularity in vehicle mobility. The proposed system develops accurate trajectory predictions using multiple order Markov chains trained on historical vehicle trace data. Routing algorithms are then proposed that take advantage of the predicted probabilistic trajectories to achieve significantly higher delivery ratios and lower costs compared to existing algorithms.

Map as a Service: A Framework for Visualising and Maximising Information Retu...

M H

This document proposes a distributed mapping service framework called Map as a Service (MaaS) for extracting and visualizing information from wireless sensor networks. MaaS utilizes distributed computation to map sensor data and generate visualizations locally within the network instead of relying on a central node. This improves efficiency by reducing communication overhead compared to centralized approaches. The framework uses inductive and deductive models along with domain knowledge to accurately map sensor modalities to a spatial context. It can map multiple sensor types simultaneously and dynamically adapt mappings in response to environmental changes.

Real time path planning based on hybrid-vanet-enhanced transportation system

Pvrtechnologies Nellore

The document presents a real-time path planning algorithm for vehicles based on a hybrid vehicular ad hoc network (VANET) and cellular network system. The algorithm aims to improve both the overall road network utilization and reduce the average vehicle travel cost. It first establishes a communication framework using VANETs, cellular networks, vehicles, roadside units and a traffic server. It then proposes a path planning algorithm based on Lyapunov optimization that considers both network performance and driver preferences like travel time and distance. Simulation results show the algorithm can efficiently find alternative paths for vehicles to bypass congestions while reducing travel costs.

Enhancing Traffic Prediction with Historical Data and Estimated Time of Arrival

IRJET Journal

This document proposes a methodology to enhance traffic prediction accuracy by combining historical traffic data, real-time traffic updates, and estimated time of arrival (ETA) information. The methodology utilizes machine learning techniques, ARIMA modeling, nonparametric methods, and deep neural networks to analyze the data. While the methodology lays out a framework for collecting raw traffic congestion data from online maps and transportation departments, the research focuses on establishing a theoretical model rather than conducting empirical experiments. The goal is to develop a comprehensive solution for traffic prediction by leveraging different data sources and analytical techniques.

21 9149 simulation analysis for consistent path identification edit septian

IAESIJEECS

As the demand for Mobile Ad hoc Network (MANET) applications grows, so does their use of many essential services where node consistent and stability of the communication paths are of great importance. In this scheme, we propose Simulation Analysis for Consistent Path Identification to Refine the Network Lifetime (CPIR). This technique offers more stable path and transmits the data through the consistent nodes. This article is focused on protecting the route from the inconsistent node in mobile communications to improve the network performance and reduce the energy consumption in the network. The simulation results demonstrate that CPIR provided reduce the energy utilization and improved both the longer lifetimes and increased number of packets delivered.

Vol 11 No 1 - March 2014

ijcsbi

Energy- Aware QoS Based Routing Protocols for Heterogeneous WSNs: A Survey ...............................1 Sridevi S., Rumeniya G. and Usha M. Optimization of Outsourcing ICT Projects in Public Organizations; Case Study: Public Center of Iranian ICT Studies ................................................................................................................................................. 20 Majid Nili Ahmadabadi, Abbas Bagheri and Fariba Abolghasemi An Optimized CBIR Using Particle Swarm Optimization Algorithm ......................................................... 40 Subhakala S., Bhuvana S. and Radhakrishnan R. Study of Satisfaction Assessment Techniques for Textual Requirements .............................................. 56 K. S. Divya, R. Subha and Dr. S. Palaniswami Survey of MAC Protocols for Heterogeneous Traffic in Wireless Sensor Networks ............................... 67 Sridevi S., Priyadharshini R. and Usha M. Harnessing Social Media for Business Success. Case Study of Zimbabwe ............................................... 80 Musungwini Samuel, Zhou Tinashe Gwendolyn, Zhou Munyaradzi and Ruvinga Caroline Quality Platforms for Innovation and Breakthrough................................................................................ 90 Dr. Hima Gupta Development of Virtual Experiment on Waveform Conversion Using Virtual Intelligent SoftLab ...... 107 Bhaskar Y. Kathane

A new approach in position-based routing Protocol using learning automata for...

ijasa

This document summarizes a research paper that proposes a new position-based routing protocol called PBLA (Position-Based routing protocol using Learning Automata) for vehicular ad hoc networks (VANETs) in urban scenarios. PBLA uses learning automata and traffic information to initially find the best and shortest path to a mobile destination. It has two phases: a learning phase where vehicles learn traffic patterns on streets to assign costs; and a routing phase where the shortest path is found using Dijkstra's algorithm and packets are forwarded between intersections greedily. The performance of PBLA is evaluated against GPSR and GPCR protocols in a simulated urban road network, showing it can efficiently route packets in high mobility V

Energy-efficient data-aggregation for optimizing quality of service using mo...

IJECEIAES

Quality of service (QoS) is essential for carrying out data transmission using resource-constrained sensor nodes in wireless sensor network (WSN). The introduction of mobile agent-based data aggregation is reported to offer energy efficiency; however, it has limitations, especially using a single mobile agent, where QoS optimization is not feasible. A review of existing studies showcases some dedicated attempts to use a mobile agent-based approach and address QoS enhancements. However, they were never combined studied. Therefore, this paper introduces a unique concept of retaining maximum QoS performance during data aggregation using a single mobile agent. The model introduces a unique communication framework, transmission provisioning using exceptional routine management, and simplified energy modeling. The proposed model has aimed for a lower delay and faster data aggregation speed with lower consumption of transmittance energy. The implementation and assessment of the model are carried out considering the challenging environment of WSN with multiple scales of data priority. The proposed model also contributes to evolving out with simplified communication vectors in a highly decentralized method. MATLAB's simulation outcome shows that the proposed system offers better delay performance, optimal energy management, and faster response time than existing schemes.

Time Orient Multi Attribute Sensor Selection Technique For Data Collection In...

inventionjournals

International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.

Reducing Latency in African NRENS Using Performance-Based LISP/SDN Traffic En...

csandit

Active topology measurements on the African Internet have showed that over 75% of the intraAfrica traffic destined for Africa's National Research and Education Net- works (NRENs) uses intercontinental links, resulting in high latencies and data transmission costs. The goal of this work is to investigate how latency-based path selection using Locator/Identifier Separation Protocol (LISP) and Software Defined Networking (SDN) in NRENs can be used to reduce inter-NREN latencies. We present aspects of an experimental prototype implementation for realtime topology probes to discover lower-latency remote gateways and dynamic configuration of end-to-end Internet paths. Simulation results indicate that ranking remote ingress gateways, and dynamic configuration of end-to-end paths between gateways can lower the average latency for inter-NREN traffic exchange.

REDUCING LATENCY IN AFRICAN NRENS USING PERFORMANCE-BASED LISP/SDN TRAFFIC EN...

cscpconf

This document summarizes a study that investigates using LISP and SDN techniques to reduce latency for traffic between African National Research and Education Networks (NRENs). It presents an experimental prototype that ranks remote gateways and dynamically configures end-to-end paths based on latency measurements to lower average latency. Simulation results on the prototype topology indicate that this performance-based traffic engineering approach can reduce inter-NREN latencies compared to static default routing.

Approximation of regression-based fault minimization for network traffic

TELKOMNIKA JOURNAL

This research associates three distinct approaches for computer network traffic prediction. They are the traditional stochastic gradient descent (SGD) using a few random samplings instead of the complete dataset for each iterative calculation, the gradient descent algorithm (GDA) which is a well-known optimization approach in deep learning, and the proposed method. The network traffic is computed from the traffic load (data and multimedia) of the computer network nodes via the Internet. It is apparent that the SGD is a modest iteration but can conclude suboptimal solutions. The GDA is a complicated one, can function more accurate than the SGD but difficult to manipulate parameters, such as the learning rate, the dataset granularity, and the loss function. Network traffic estimation helps improve performance and lower costs for various applications, such as an adaptive rate control, load balancing, the quality of service (QoS), fair bandwidth allocation, and anomaly detection. The proposed method confirms optimal values out of parameters using simulation to compute the minimum figure of specified loss function in each iteration.

Mining data for traffic detection system

ijccsa

This document discusses a system for mining traffic data using GPS-enabled mobile phones in a mobile cloud infrastructure. The system has three main components: a client interface on mobile devices, a server process, and cloud storage. The client filters GPS data from mobile devices to identify motorized transportation modes. This data is sent to the server, which uses distance-based clustering to group devices on the same vehicle. The clustered data and historical data are stored in the cloud for traffic detection. This mobile cloud approach reduces burdens on mobile devices and servers while leveraging cloud resources.

Feasibility Analysis of Directional-Location Aided Routing Protocol for Vehic...

IJCSIS Research Publications

Vehicular Ad-hoc Network (VANET) is a multi-hop wireless ad-hoc network created by using mobile vehicles to transmit safety message for vehicle drivers. Since vehicles are mobile so they change their location frequently, therefore; robust data delivery is a challenging task in the VANET. Due to frequently network topology change characteristic, selection of a routing protocol in VANET is challenging task. In this paper performance of location-based routing protocols Directional- Location Aided Routing (D-LAR), Location-Aided Routing (LAR) and DIrectional Routing (DIR) are analyzed to decide best routing protocol for VANET. LAR protocol limits the route discovery area in the forward direction using GPS technology and DIR protocol uses direction information from the baseline drawn from the source and destination node. The D-LAR protocol uses concepts of the both LAR and DIR protocols. Using greedy forwarding approach D-LAR protocol selects next hop forwarding node in the forward direction of the communication range. Feasibility of D-LAR protocol has justified through simulation in NS2 using routing metrics such as node distribution at the border area of the communication range R, expected one hop distance ࡱ൫ࡺ(࢔, ࢘)൯ , expected hop counts E(H) between source and destination node, expected delay E(delay), routing overhead and packet loss. Through simulation work, it has shown D-LAR protocol performs better as compared to LAR and DIR protocol.

Distributed State Estimation With Deep Neural Networks for Uncertain Nonlinea...

OKOKPROJECTS

Distributed Inference in Resource-Constrained IoT for Real-Time Video Surveil...

OKOKPROJECTS

Similar to A Dual Attention-Based Recurrent Neural Network for Short-Term Bike Sharing Usage Demand Prediction.pdf

K017346572

IOSR Journals

A Fast Convergence and Quick Route Updates Based Energy Aware Tree-Based Rout...

iosrjce

APPLICABILITY OF CROWD SOURCING TO DETERMINE THE BEST TRANSPORTATION METHOD B...

IJDKP

APPLICABILITY OF CROWD SOURCING TO DETERMINE THE BEST TRANSPORTATION METHOD B...

IJDKP

COVERAGE OPTIMIZED AND TIME EFFICIENT LOCAL SEARCH BETWEENNESS ROUTING FOR HE...

ijcsa

Certain Analysis on Traffic Dataset based on Data Mining Algorithms

IRJET Journal

Trajectory improves data delivery in urban vehicular networks

Papitha Velumani

Map as a Service: A Framework for Visualising and Maximising Information Retu...

M H

Real time path planning based on hybrid-vanet-enhanced transportation system

Pvrtechnologies Nellore

Enhancing Traffic Prediction with Historical Data and Estimated Time of Arrival

IRJET Journal

21 9149 simulation analysis for consistent path identification edit septian

IAESIJEECS

Vol 11 No 1 - March 2014

ijcsbi

A new approach in position-based routing Protocol using learning automata for...

ijasa

Energy-efficient data-aggregation for optimizing quality of service using mo...

IJECEIAES

Time Orient Multi Attribute Sensor Selection Technique For Data Collection In...

inventionjournals

Reducing Latency in African NRENS Using Performance-Based LISP/SDN Traffic En...

csandit

REDUCING LATENCY IN AFRICAN NRENS USING PERFORMANCE-BASED LISP/SDN TRAFFIC EN...

cscpconf

Approximation of regression-based fault minimization for network traffic

TELKOMNIKA JOURNAL

Mining data for traffic detection system

ijccsa

Feasibility Analysis of Directional-Location Aided Routing Protocol for Vehic...

IJCSIS Research Publications

Similar to A Dual Attention-Based Recurrent Neural Network for Short-Term Bike Sharing Usage Demand Prediction.pdf (20)