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Exploration of machine learning forecasting methods in M4 competition / Muhammad Halim Hamdan and Shuzlina Abdul-Rahman by Hamdan, Muhammad Halim, Abdul-Rahman, Shuzlina

“…Each technique was replicated, trained and tested accordingly. M4 competition dataset was used in this research, with 100,000 time series data and multiple data frequency, which is enough to replicate the real-world situation. …”
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A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm by Ba-Quttayyan, Bakr Salim Abdullah

“…This research employed a modified version of the Design Science Research Methodology (DSRM), streamlined into five stages: problem identification, theoretical study, framework development, evaluation, and reporting. …”
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Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data by Fanos, Ali Mutar, Pradhan, Biswajeet, Mansor, Shattri, Md Yusoff, Zainuddin, Abdullah, Ahmad Fikri, Jung, Hyung Sup

“…The availability of high-resolution laser scanning data and advanced machine learning algorithms has enabled an accurate potential rockfall source identification. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

“…Generally, medical data is considered high-dimensional and complex data that contains many irrelevant and redundant features. …”
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Securing IoT networks using machine learning-resistant physical unclonable functions (PUFs) on edge devices by Sheikh, Abdul Manan, Islam, Md. Rafiqul, Habaebi, Mohamed Hadi, Zabidi, Suriza Ahmad, Najeeb, Athaur Rahman, Baloch, Mazhar

“…The Internet of Things (IoT) has transformed global connectivity by linking people, smart devices, and data. However, as the number of connected devices continues to grow, ensuring secure data transmission and communication has become increasingly challenging. …”
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Multi-agent reinforcement learning for Bai ethnic traditional dwelling protection in Dali : cultural identity-oriented community relationship optimization and urbanization adaptati... by Xiaohua, Qian, Neilson Ilan, Mersat, Haslina, Hashim, Bemen Wong, Win Keong

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HARC-New Hybrid Method with Hierarchical Attention Based Bidirectional Recurrent Neural Network with Dilated Convolutional Neural Network to Recognize Multilabel Emotions from Text by Islam, Md Shofiqul, Sultana, Sunjida, Debnath, Uttam Kumar, Al Mahmud, Jubayer, Islam, S. M. Jahidul

“…On a variety of datasets, our proposed HARC algorithm solution outperformed traditional machine learning approaches as well as comparable deep learning models by a margin of 1%. …”
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A Novel Path Prediction Strategy for Tracking Intelligent Travelers by Motlagh, Omid Reza Esmaeili

“…The FCM nodes are a novel selection of kinematical factors. Genetic algorithm (GA) is then used to train the FCM to be able to replicate the decisional behaviors of the intelligent traveler. …”
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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis by Rochin Demong, Nur Atiqah, Mohamed Razali, Murni Zarina, Kamaruddin, Juliana Noor, Shamsuddin, Sazwan, Awang, Nor Ain, Kamarudin, Norjuliatie, Wan Othman, Noor Faradilla

“…The increasing demand for servicing codes across faculties has created a growing need for data-driven decision supports in optimizing lecturer allocation and cost efficiency. …”
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Assessment of suitable hospital location using GIS and machine learning by Almansi, Khaled Y. M.

“…Third, an insight into the machine learning models utilized and how their predicted weights affect hospital site suitability mapping was provided. …”
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Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection by Nadheer Abdulridha, Shalash

“…The second agent is a reliability evaluation agent that uses a recursive algorithm to predict the suitability generator based on the frequency and duration reliability indices in each state while the third agent is the storage and transfer of data between the other two agents. …”
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Development of a hybrid machine learning model for rockfall source and hazard assessment using laser scanning data and GIS by Fanos, Ali Mutar

“…This is based on highresolution Light Detection and Ranging (LiDAR) techniques both airborne and terrestrial (ALS and TLS). Different machine learning algorithms (Artificial Neural Network [ANN], K Nearest Neighbor [KNN] and Support Vector Machine [SVM]) were tested individually and with various ensemble models (bagging, voting, and boosting) to detect the probability of the landslide and rockfall occurrences. …”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

“…Afterward evolutionary algorithm (EA) was employed to prioritize test cases based on the rate severity of fault detection per unit test cost. …”
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