Predicting the Success of Suicide Terrorist Attacks using different Machine Learning Algorithms-Reference-Cited by-同舟云学术

Predicting the Success of Suicide Terrorist Attacks using different Machine Learning Algorithms

Published:2022-12-17 Issue: Volume: Page:
ISSN:
Container-title:2022 25th International Conference on Computer and Information Technology (ICCIT)
language:
Short-container-title:

Author:

Hossain Md. Junayed¹,Abdullah Sheikh Md.¹,Barkatullah Mohammad¹,Miah M. Saef Ullah²,Sarwar Talha Bin²,Monir Md Fahad¹

Affiliation:

1. Independent University, Bangladesh,Computer Science and Engineering,Dhaka,Bangladesh

2. Universiti Malaysia Pahang,Faculty of Computing,Pekan,Malaysia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10054512/10054643/10055100.pdf?arnumber=10055100

Reference20 articles.

1. MissForest--non-parametric missing value imputation for mixed-type data

2. An Empirical Study of Suicide Terrorism: A Global Analysis

3. A review of feature selection methods with applications;jovi?;2015 38th International Convention on Information and Communication Technology Electronics and Microelectronics (MIPRO),2015

4. An Improved SMOTE Imbalanced Data Classification Method Based on Support Degree

5. A Densely Interconnected Convolutional Neural Network-Based Approach to Identify COVID-19 from Chest X-ray Images

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Smart Surveillance System for Facemask Detection Using Custom CNN—BIDNet;IEEE Access;2024

2. Repercussion of Image Compression on Satellite Image Classification using Deep Learning Models;2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall);2023-10-10

3. Exploring the Efficacy of BERT in Bengali NLP: A Study on Sentiment Analysis and Aspect Detection;IEEE EUROCON 2023 - 20th International Conference on Smart Technologies;2023-07-06

4. Impact of COVID-19 Lockdowns on Air Quality in Bangladesh: Analysis and AQI Forecasting with Support Vector Regression;2023 4th International Conference for Emerging Technology (INCET);2023-05-26

5. Predicting Short-Term Energy Demand in the Smart Grid: A Deep Learning Approach for Integrating Renewable Energy Sources in Line with Sdgs 7, 9, and 13;2023