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Field: Traffic Prediction and Management Techniques

Machine Learning: Algorithms, Real-World Applications and Research Directions

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Iqbal H. Sarker

Journal: SN Computer Science
Year: 2021
Citations: 5075

In the current age of the Fourth Industrial Revolution (4 IR or Industry 4.0), the digital world has a wealth of data, such as Internet of Things (IoT) data, cybersecurity data, mobile data, business data, social media data, health data, etc. To intelligently analyze these data and develop the corre...

Physical SciencesComputer ScienceArtificial IntelligenceOpen Access
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AI-Based Modeling: Techniques, Applications and Research Issues Towards Automation, Intelligent and Smart Systems

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Iqbal H. Sarker

Journal: SN Computer ScienceYear: 2022Citations: 1064

Abstract Artificial intelligence (AI) is a leading technology of the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR), with the capability of incorporating human behavior and intelligence into machines or systems. Thus, AI-based modeling is the key to build automated, intelligen...

Physical SciencesEngineeringBuilding and ConstructionOpen Access
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Using support vector machine models for crash injury severity analysis

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Zhibin Li, Pan Liu, Wei Wang, Chengcheng Xu

Journal: Accident Analysis & PreventionYear: 2011Citations: 310

The study presented in this paper investigated the possibility of using support vector machine (SVM) models for crash injury severity analysis. Based on crash data collected at 326 freeway diverge areas, a SVM model was developed for predicting the injury severity associated with individual crashes....

Physical SciencesEngineeringSafety, Risk, Reliability and Quality
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Deep Learning-Based Stock Price Prediction Using LSTM and Bi-Directional LSTM Model

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Md. Arif Istiake Sunny, Mirza Mohd Shahriar Maswood, Abdullah G. Alharbi

Journal: 2020 2nd Novel Intelligent and Leading Emerging Sciences Conference (NILES)Year: 2020Citations: 304

In the financial world, the forecasting of stock price gains significant attraction. For the growth of shareholders in a company's stock, stock price prediction has a great consideration to increase the interest of speculators for investing money to the company. The successful prediction of a stock'...

Social SciencesDecision SciencesManagement Science and Operations Research
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Machine Learning: Algorithms, Real-World Applications and Research Directions

Verified

Iqbal H. Sarker

Journal: Preprints.orgYear: 2021Citations: 219

In the current age of the Fourth Industrial Revolution ($4IR$ or Industry $4.0$), the digital world has a wealth of data, such as Internet of Things (IoT) data, cybersecurity data, mobile data, business data, social media data, health data, etc. To intelligently analyze these data and develop the co...

Physical SciencesEngineeringBuilding and ConstructionOpen Access
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A crash prediction method based on bivariate extreme value theory and video-based vehicle trajectory data

Verified

Chen Wang, Chengcheng Xu, Yulu Dai

Journal: Accident Analysis & PreventionYear: 2018Citations: 202

Traditional statistical crash prediction models oftentimes suffer from poor data quality and require large amount of historical data. In this paper, we propose a crash prediction method based on a bivariate extreme value theory (EVT) framework, considering both drivers' perception-reaction failure a...

Physical SciencesEngineeringBuilding and Construction
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A study on road accident prediction and contributing factors using explainable machine learning models: analysis and performance

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Shakil Ahmed, Md Akbar Hossain, Sayan Kumar Ray, Md. Mafijul Islam Bhuiyan et al.

Journal: Transportation Research Interdisciplinary PerspectivesYear: 2023Citations: 170

Road accidents are increasing worldwide and are causing millions of deaths each year. They impose significant financial and economic expenses on society. Existing research has mostly studied road accident prediction as a classification problem, which aims to predict whether a traffic accident may ha...

Physical SciencesEngineeringSafety, Risk, Reliability and QualityOpen Access
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Smart City Data Science: Towards data-driven smart cities with open research issues

Verified

Iqbal H. Sarker

Journal: Internet of ThingsYear: 2022Citations: 156
Social SciencesTransportationHuman Mobility and Location-Based Analysis
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Real-time crash prediction models: State-of-the-art, design pathways and ubiquitous requirements

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Moinul Hossain, Mohamed Abdel‐Aty, Mohammed Quddus, Yasunori Muromachi et al.

Journal: Accident Analysis & PreventionYear: 2019Citations: 151

Proactive traffic safety management systems can monitor traffic conditions in real-time, identify the formation of unsafe traffic dynamics, and implement suitable interventions to bring unsafe conditions back to normal traffic situations. Recent advancements in artificial intelligence, sensor fusion...

Physical SciencesEngineeringBuilding and ConstructionOpen Access
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BHyPreC: A Novel Bi-LSTM Based Hybrid Recurrent Neural Network Model to Predict the CPU Workload of Cloud Virtual Machine

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Md. Ebtidaul Karim, Mirza Mohd Shahriar Maswood, Sunanda Das, Abdullah G. Alharbi

Journal: IEEE AccessYear: 2021Citations: 111

With the advancement of cloud computing technologies, there is an ever-increasing demand for the maximum utilization of cloud resources. It increases the computing power consumption of the cloud’s systems. Consolidation of cloud’s Virtual Machines (VMs) provides a pragmatic approach to reduce the en...

Physical SciencesComputer ScienceInformation SystemsOpen Access
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Road Accident Analysis and Prediction of Accident Severity by Using Machine Learning in Bangladesh

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Md. Farhan Labib, Ahmed Sady Rifat, Md. Mosabbir Hossain, Amit Kumar Das et al.

Year: 2019Citations: 109

In recent years, the road accident has become a global problem and marked as the ninth prominent cause of death in the world. Due to the enormous number of road accidents every year, it has become a major problem in Bangladesh. It is entirely inadmissible and saddening to allow its citizen to kill b...

Physical SciencesEngineeringBuilding and Construction
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Advances in Crowd Analysis for Urban Applications Through Urban Event Detection

Verified

M. Shamim Kaiser, Khin Lwin, Mufti Mahmud, Donya Hajializadeh et al.

Journal: IEEE Transactions on Intelligent Transportation SystemsYear: 2017Citations: 108

The recent expansion of pervasive computing technology has contributed with novel means to pursue human activities in urban space. The urban dynamics unveiled by these means generate an enormous amount of data. These data are mainly endowed by portable and radio-frequency devices, transportation sys...

Social SciencesTransportationHuman Mobility and Location-Based AnalysisOpen Access
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Micro-simulation modelling for traffic safety: A review and potential application to heterogeneous traffic environment

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Shoaib Mahmud, Luís Ferreira, Md. Shamsul Hoque, Ahmad Tavassoli

Journal: IATSS ResearchYear: 2018Citations: 105

This paper critically reviews micro-simulation modelling applications for traffic safety evaluation with respect to the use of different simulation tools, the application of surrogate safety indicators under different aspects of road environments and crash considerations. General input variables use...

Physical SciencesEngineeringControl and Systems EngineeringOpen Access
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A review on neural network techniques for the prediction of road traffic accident severity

Verified

Md. Ebrahim Shaik, Md. Milon Islam, Quazi Sazzad Hossain

Journal: Asian Transport StudiesYear: 2021Citations: 96

The occurrence rate of death and injury due to road traffic accidents is rising increasingly globally day by day. For several decades, the focus of research has been on getting a deeper understanding of the significant factors that influence the risk of road traffic fatalities. In today's modern wor...

Physical SciencesEngineeringBuilding and ConstructionOpen Access
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HSIC Bottleneck Based Distributed Deep Learning Model for Load Forecasting in Smart Grid With a Comprehensive Survey

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Md. Akhtaruzzaman, Mohammad Kamrul Hasan, S. Rayhan Kabir, Siti Norul Huda Sheikh Abdullah et al.

Journal: IEEE AccessYear: 2020Citations: 96

Load forecasting is a vital part of smart grids for predicting the required electrical power using artificial intelligence (AI). Deep learning is broadly used for load forecasting in the smart grid using the artificial neural network (ANN). Generally, computing the deep learning in the smart grid re...

Physical SciencesEngineeringElectrical and Electronic EngineeringOpen Access
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