Prediction of Future Terrorist Activities Using Deep Neural Networks by M. Irfan Uddin, Nazir Zada, Furqan Aziz, Yousaf Saeed, Asim Zeb, Syed Atif Ali Shah, Mahmoud Ahmad Al-Khasawneh, Marwan Mahmoud

“…The performance of the DNN is compared with NN and the three machine learning algorithms, and it is demonstrated that the performance in DNN is more than 95% in terms of accuracy, precision, recall, and F1-Score, while ANN and traditional machine learning algorithms have achieved a maximum of 83% accuracy. …”
Get full text

Novel and Efficient Randomized Algorithms for Feature Selection by Zigeng Wang, Xia Xiao, Sanguthevar Rajasekaran

“…Feature selection is a crucial problem in efficient machine learning, and it also greatly contributes to the explainability of machine-driven decisions. …”
Get full text

Analisis Kinerja Intrusion Detection System Berbasis Algoritma Random Forest Menggunakan Dataset Unbalanced Honeynet BSSN by Kuni Inayah, Kalamullah Ramli

“…Hasil analisis menunjukkan bahwa pemodelan IDS based on machine learning memiliki rata-rata nilai akurasi lebih dari 90%, nilai presisi 91%, nilai recall 90%, dan F1-score 90%. …”
Get full text

Joint Distribution pada Weighted Majority Vote (WMV) untuk Peningkatan Kinerja Sentiment Analysis Tersupervisi pada Dataset Twitter by Bagus Setya Rintyarna

“…Ada dua pendekatan yang umum digunakan dalam teknik sentiment analysis yaitu pendekatan berbasis machine learning (ML) dan pendekatan berbasis sentiment lexicon (SL). …”
Get full text

Exploring small-scale optimization coupling learning approaches for enterprises’ financial health forecasts by Lin Zhu, Zhihua Zhang, M. James C. Crabbe

“…Most data-driven financial health forecasts are based on the direct use of small-scale machine learning. In this study, we proposed the idea of optimization coupling learning to improve these machine learning models in financial health forecasting. …”
Get full text

A Research: Investigation of Financial Applications with Blockchain Technology by Mohammed Ali Mohammed Mohammed, Fuat Türk

“…This article delves into applying machine learning techniques for predicting cryptocurrency prices, mainly focusing on Bitcoin, Ethereum, and Binance Coin. …”
Get full text

Empirical Analysis of Financial Statement Fraud of Listed Companies Based on Logistic Regression and Random Forest Algorithm by Xinchun Liu

“…In this paper, two machine learning algorithms, decision tree and random forest, are used to detect the company's financial data. …”
Get full text

Comparative Analysis of Shear Strength Prediction Models for Reinforced Concrete Slab–Column Connections by Sarmed Wahab, Nasim Shakouri Mahmoudabadi, Sarmad Waqas, Nouman Herl, Muhammad Iqbal, Khurshid Alam, Afaq Ahmad

“…This research focuses on a comprehensive comparative analysis of shear strength prediction in slab–column connections, integrating machine learning, design codes, and finite element analysis (FEA). …”
Get full text

An Alternative Method for Traffic Accident Severity Prediction: Using Deep Forests Algorithm by Jing Gan, Linheng Li, Dapeng Zhang, Ziwei Yi, Qiaojun Xiang

“…These models gradually evolved from linear to nonlinear forms and from traditional statistical regression models to current popular machine learning models. Recently, a machine learning algorithm called Deep Forests based on the decision tree ensemble has aroused widespread concern, which was proposed for the first time by a research team of Nanjing University. …”
Get full text

Enhancing Photovoltaic Module Fault Diagnosis with Unmanned Aerial Vehicles and Deep Learning-Based Image Analysis by J. Jerome Vasanth, S. Naveen Venkatesh, V. Sugumaran, Vetri Selvi Mahamuni

“…During the machine learning phase, feature selection from the extracted features was carried out using the J48 decision tree algorithm. …”
Get full text

A Prediction Method of Electromagnetic Environment Effects for UAV LiDAR Detection System by Min Huang, Dandan Liu, Liyun Ma, Jingyang Wang, Yuming Wang, Yazhou Chen

“…This paper proposes a Stacking fusion model based on machine learning to predict electromagnetic environment effects. …”
Get full text

Prediction and optimization of acoustic absorption performance of quasi-Helmholtz acoustic metamaterials based on LightGBM algorithm by Jianxin Xu, Weikang Mao, Xiaoqian Yu, Bingfei Liu

“…The results of this study show that the acoustic performance of quasi-Helmholtz acoustic metamaterials can be predicted and optimized using machine learning methods. The study in this paper combines the method of machine learning with acoustic problems to provide a fast method for predicting the absorption performance of acoustic metamaterials.…”
Get full text

Federated learning based reference evapotranspiration estimation for distributed crop fields. by Muhammad Tausif, Muhammad Waseem Iqbal, Rab Nawaz Bashir, Bayan AlGhofaily, Alex Elyassih, Amjad Rehman Khan

“…Efforts have been made to simplify the (ETo) estimation using machine learning models. The existing approaches are limited to a single specific area. …”
Get full text

Pengukuran Performa Apache Spark dengan Library H2O Menggunakan Benchmark Hibench Berbasis Cloud Computing by Aminudin Aminudin, Eko Budi Cahyono

“…Agar di dalam Apache Spark mampu melakukan proses machine learning, maka di dalam paper ini akan dilakukan eksperimen yaitu dengan mengintegrasikan Apache Spark yang bertindak sebagai lingkungan pemrosesan data yang besar dan konsep parallel komputing akan dikombinasikan dengan library H2O yang khusus untuk menangani pemrosesan data menggunakan algoritme machine learning. …”
Get full text

Research for SARIMA and PatchTSMixer Models on the IEA Monthly Statistics Dataset by Hu Yuwei

“…However, a significant gap exists in comparing the predictive performance of traditional machine learning methods with advanced deep learning models using real-world datasets. …”
Get full text

Speckle Noise Removal by Energy Models with New Regularization Setting by Bo Chen, Jinbin Zou, Weiqiang Zhang

Get full text

A survey of security threats in federated learning by Yunhao Feng, Yanming Guo, Yinjian Hou, Yulun Wu, Mingrui Lao, Tianyuan Yu, Gang Liu

“…Abstract Federated learning is a distributed machine learning paradigm that emerged as a solution to the need for privacy protection in artificial intelligence. …”
Get full text

The Social Construction of Categorical Data: Mixed Methods Approach to Assessing Data Features in Publicly Available Datasets by Theresa Willem, Alessandro Wollek, Theodor Cheslerean-Boghiu, Martha Kenney, Alena Buyx

“…ObjectiveThis study aimed to explore categorical data’s effects on machine learning model outputs, rooted the effects in the data collection and dataset publication processes, and proposed a mixed methods approach to examining datasets’ data categories before using them for machine learning training. …”
Get full text

Collaboration of clustering and classification techniques for better prediction of severity of heart stroke using deep learning by T. Swathi Priyadarshini, Mohd Abdul Hameed

“…Our research aims to present a comprehensive study of machine learning algorithms and deep learning advancements in medical field systems for decision making. …”
Get full text

Enhancing the Efficiency of Routing Strategies in WSNs Using Live Streaming Algorithms by Hayder Jasim Alhamdane, Mohsen Nickray

“… The application of machine learning in wireless sensor networks (WSN) has attracted much attention. …”
Get full text